Jekyll2021-08-05T22:30:32+00:00https://srconstantin.github.io/feed.xmlSarah ConstantinTrained in math and machine learning, currently trying to solve technological problems and make sense of our world.Are Cancer Cells More Negatively Charged?2021-08-05T00:00:00+00:002021-08-05T00:00:00+00:00https://srconstantin.github.io/2021/08/05/electric-charge<p>Are cancer cells more negatively charged than healthy cells? Does this hold across cancer types and tissues?</p>
<p>If so, this could prove extremely useful as a broad-spectrum cancer treatment. Simply bond something toxic to cancer cells (such as a chemotherapy drug) to a positively charged nanoparticle, and you can deliver targeted drugs that kill cancer cells but not healthy cells.</p>
<p><strong>Electrophoretic Mobility</strong></p>
<p>Cells in suspension in an electrolyte solution like saline normally have a negative surface charge and can therefore be induced to flow along an electrochemical gradient.</p>
<p>Cell electrophoretic mobility – the ratio of cell velocity to electric field strength, in cm^2 V^(-1) s^(-1) – depends on the cell cycle stage, peaking around mitosis. So you might expect all rapidly dividing cells, including tumor cells, to have high electrophoretic mobility more of the time.[1][4]</p>
<p>In samples from healthy patients and patients with chronic lymphocytic leukemia, n = 19, electrophoretic mobility did not significantly differ between cancer and normal lymphocytes.[2]</p>
<p>In a study of blood cells taken from 700 patients (some healthy, some with various diseases including both blood cancers and solid tumors), all cancers significantly _reduced _the electrophoretic mobility of red blood cells, indicating that the RBCs became less negatively charged. Benign tumors had no effect.[3]</p>
<p>Leukaemic mouse lymphocytes in saline had significantly lower electrophoretic mobility than normal mouse lymphocytes.[5]</p>
<p>In a study of multiple human tumor samples, epithelial tumor cells did not have higher electrophoretic mobility than normal cells, but connective tissue tumor cells (sarcomas and myomas) did.[6]</p>
<p>Another study on different cell lines found that an epithelial cancer cell line (HeLa) was not significantly different in electrophoretic mobility than normal cells, but that a carcinoma cell line (Ehrlich ascites tumor) had significantly higher electrophoretic mobility.[7]</p>
<p>At physiologic pH, breast cancer cells have higher electrophoretic mobility (and thus more negative surface charge) than healthy fibroblasts.[13]</p>
<p>Hamster kidney and liver tumor cells, which are carcinomas, have significantly higher electrophoretic mobility than their healthy counterparts. The MCIM sarcoma becomes more electrophoretically mobile as it gets closer to metastasis.[14]</p>
<p>Solid tumor cells are also less adhesive than healthy cells from the same tissue type; this is what you would expect if they were more negatively charged and thus repelled each other electrostatically more. Blood cells, healthy or cancerous, are already not very adhesive, and accordingly they are more electrostatically mobile.[14]</p>
<p><strong>Electrically Charged Nanoparticle Aggregation</strong></p>
<p>Electrophoresis may not be an accurate way to measure cell surface charge. Voltages necessary to move cells are high, which will change cell function. An alternative method is to create charged nanoparticles and observe which cells they cluster around.</p>
<p>Iron oxide nanoparticles can be given a positive or negative electric charge. If these are introduced into cell culture suspension and they bind to the cells, the bound cells can be captured by applying a magnetic field to one side of the vessel.</p>
<p>Positive nanoparticle binding (as measured by % of cells captured by a magnetic field) is increasing with glucose concentration and lactic acid concentration, and decreasing with concentration of glycolysis inhibitors like DCA and 3BP, suggesting that cells undergoing glycolysis are more negatively charged.[8] Out of 22 cancer cell culture lines and 4 healthy cell lines, all cancer samples had over 50% capture by a magnetic field when mixed with positive nanoparticles; no healthy cell lines had any capture by a magnetic field when mixed with positive nanoparticles.[8]</p>
<p>Positively charged iron oxide nanoparticles, but not negatively charged ones, were observed to aggregate around cancer cells in buffer solution. At high cell concentrations, 99% of cells can by captured by attracting the positively charged nanoparticles in a magnetic field. If blood is spiked with cancer cells, over 70% of the cancer cells can be captured in the same way.[9]</p>
<p>In a mouse model of sarcoma[9], taking a blood sample and mixing it with positive iron oxide nanoparticles and then capturing cells with a magnetic field results in 75.8 circulating tumor cells per 100 uL being captured in the sarcoma mouse, while no cells were captured in healthy controls.</p>
<p>Zinc oxide nanoparticles have a positive surface charge at physiologic pH. These particles have a cytotoxic effect in vitro on multiple cancer cell lines, and in particular cancer cells of lymphocytic lineage are 28-35 times as susceptible to death when treated with ZnO nanoparticles than their non-cancerous counterparts. This is a specificity ratio much higher than that for conventional chemotherapeutic drugs.[10]</p>
<p>Positively charged gold nanoparticles adhere 117 times more strongly to the surface of HeLa cancer cells than negatively charged gold nanoparticles.[11]</p>
<p>Positively charged magnetite nanoparticles have higher uptake into breast cancer cells than negatively charged nanoparticles; but there is no charge-based difference in uptake on healthy embryonic cord cells.[12]</p>
<p><strong>References</strong></p>
<p>[1]Akagi, Takanori, and Takanori Ichiki. “Cell electrophoresis on a chip: what can we know from the changes in electrophoretic mobility?.” <em>Analytical and bioanalytical chemistry</em> 391.7 (2008): 2433-2441.</p>
<p>[2]Lichtman, Marshall A., and Robert I. Weed. “Electrophoretic mobility and N-acetyl neuraminic acid content of human normal and leukemic lymphocytes and granulocytes.” <em>Blood</em> 35.1 (1970): 12-22.</p>
<p>[3]Rottino, Antonio, and John Angers. “The electrophoretic mobility of erythrocytes in carcinoma and other diseases.” <em>Cancer research</em> 21.10 (1961): 1445-1449.</p>
<p>[4]Mayhew, E. “Cellular electrophoretic mobility and the mitotic cycle.” <em>The Journal of general physiology</em> 49.4 (1966): 717-725.</p>
<p>[5]Cook, G. M. W., and W. Jacobson. “The electrophoretic mobility of normal and leukaemic cells of mice.” <em>Biochemical Journal</em> 107.4 (1968): 549-557.</p>
<p>[6]Vassar, Philip S. “Electrophoretic mobility of human tumour cells.” <em>Nature</em> 197.4873 (1963): 1215-1216.</p>
<p>[7]Simon-Reuss, I., et al. “Electrophoretic studies on some types of mammalian tissue cell.” <em>Cancer research</em> 24.11 Part 1 (1964): 2038-2043.</p>
<p>[8]Chen, Bingdi, et al. “Targeting negative surface charges of cancer cells by multifunctional nanoprobes.” <em>Theranostics</em> 6.11 (2016): 1887.</p>
<p>[9]Li, Zhiming, Jun Ruan, and Xuan Zhuang. “Effective capture of circulating tumor cells from an S180-bearing mouse model using electrically charged magnetic nanoparticles.” <em>Journal of nanobiotechnology</em> 17.1 (2019): 1-9</p>
<p>[10]Rasmussen, John W., et al. “Zinc oxide nanoparticles for selective destruction of tumor cells and potential for drug delivery applications.” <em>Expert opinion on drug delivery</em> 7.9 (2010): 1063-1077..</p>
<p>[11]Peter, Beatrix, et al. “Interaction of positively charged gold nanoparticles with cancer cells monitored by an in situ label-free optical biosensor and transmission electron microscopy.” <em>ACS applied materials & interfaces</em> 10.32 (2018): 26841-26850.</p>
<p>[12]Osaka, Tetsuya, et al. “Effect of surface charge of magnetite nanoparticles on their internalization into breast cancer and umbilical vein endothelial cells.” <em>Colloids and Surfaces B: Biointerfaces</em> 71.2 (2009): 325-330.</p>
<p>[13]Dobrzyńska, Izabela, Elżbieta Skrzydlewska, and Zbigniew A. Figaszewski. “Changes in electric properties of human breast cancer cells.” <em>The Journal of membrane biology</em> 246.2 (2013): 161-166.</p>
<p>[14]Abercrombie, M., and E. J. Ambrose. “The surface properties of cancer cells: a review.” <em>Cancer research</em> 22.5 Part 1 (1962): 525-548.</p>Are cancer cells more negatively charged than healthy cells? Does this hold across cancer types and tissues?Interesting rTMS Results in Healthy People2021-08-05T00:00:00+00:002021-08-05T00:00:00+00:00https://srconstantin.github.io/2021/08/05/rTMS<p><strong>Introduction</strong></p>
<p>This is an overview of selected research on repetitive transcranial magnetic stimulation, or rTMS, which involves applying a coil that produces a rapidly fluctuating magnetic field to the outside of the head, thereby stimulating the surface of the brain beneath the coil.</p>
<p>RTMS is an approved treatment for depression and has been investigated for various other psychiatric disorders, but it’s particularly intriguing that it also seems to have effects on healthy people that include cognitive improvements above the “normal” baseline.</p>
<p><strong>Summary, by Type of Intervention</strong></p>
<p>Note: stimulation of <1 Hz is generally thought to have an inhibitory effect on a brain region, while stimulation of >5 Hz is thought to have an excitatory effect.</p>
<p>I only include results that have been observed in at least two studies and not been disconfirmed.</p>
<p>I focus on studies in healthy subjects, and on improvements rather than impairments.</p>
<p><strong>Left Dorsolateral Prefrontal Cortex, Inhibitory</strong></p>
<ul>
<li>Increased accuracy on working memory tasks (2)</li>
</ul>
<p><strong>Left Dorsolateral Prefrontal Cortex, Excitatory</strong></p>
<ul>
<li>Reduced addiction symptoms (2)</li>
<li>Reduced stress response to criticism (3)</li>
<li>Reduced pain (2)</li>
<li>Reduced reaction times on cognitive tasks (6)</li>
<li>Reduced impulsivity (2)</li>
</ul>
<p><strong>Right Dorsolateral Prefrontal Cortex, Inhibitory</strong></p>
<ul>
<li>Reduced costly reciprocal fairness signaling (ultimatum game, dictator game, trade-back game with reputation) (3)</li>
<li>Increased risk-taking behavior (2)</li>
</ul>
<p><strong>Right Dorsolateral Prefrontal Cortex, Excitatory</strong></p>
<ul>
<li>Reduced reaction times on cognitive tasks (4)</li>
<li>Increased startle & distraction by threats (2)</li>
</ul>
<p><strong>Bilateral Dorsomedial Prefrontal Cortex, Excitatory</strong></p>
<ul>
<li>Increased empathy and comfort with social interaction (3)</li>
<li>Improved fear extinction/phobia recovery (2)</li>
</ul>
<p><strong>Left Inferior Frontal Cortex, Inhibitory</strong></p>
<ul>
<li>Improved performance on abstract reasoning tasks such as syllogisms and artificial grammar (2)</li>
</ul>
<p><strong>M1, Excitatory</strong></p>
<ul>
<li>Reduced pain (2)</li>
</ul>
<p><strong>Right Temporoparietal Junction, Inhibitory</strong></p>
<ul>
<li>Reduced ingroup bias (2)</li>
</ul>
<p><strong>Left Inferior Parietal Lobule, Excitatory</strong></p>
<ul>
<li>Improved reading accuracy (2)</li>
</ul>
<p><strong>Right Inferior Parietal Lobule, Excitatory</strong></p>
<ul>
<li>Improved accuracy and reaction time on numerical estimation and calculation tasks (2)</li>
</ul>
<p><strong>Right Inferior Parietal Lobule, Inhibitory</strong></p>
<ul>
<li>Shorter reaction time in bottom-up processing and visual perception tasks (4)</li>
<li>Reduced startle response to pain and loud noises (2)</li>
</ul>
<p><strong>Analogic Reasoning</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[6]
</td>
<td>Left DLPFC
</td>
<td>During test
</td>
<td>1 Hz
</td>
<td>Magstim Rapid2 Stimulator and 70mm figure-eight coil
</td>
<td>Improved response time (10% faster) on geometric shape based analogy questions
</td>
<td>16
</td>
</tr>
</table>
<p><strong>Addiction</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[6]
</td>
<td>DLPFC (F3)
</td>
<td>5 days/week for 4 weeks, 30 min/day
</td>
<td>15 hz
</td>
<td>Magpro R30 with Cool-b80 figure-8 coil
</td>
<td>9/16 patients seeking treatment for cocaine use tested negative for cocaine at end of study. Big significant drops in depression and anxiety scales.
</td>
<td>20
</td>
</tr>
<tr>
<td>[27]
</td>
<td>Left DLPFC
</td>
<td>13 min, twice daily for a week followed by weekly for 8 weeks
</td>
<td>15 Hz
</td>
<td>MagPro R30
</td>
<td>Significant drops in cocaine craving & gambling severity scores in gambling and cocaine addicts.
</td>
<td>7
</td>
</tr>
<tr>
<td>[44]
</td>
<td>Medial PFC and anterior cingulate cortex
</td>
<td>15 minute sessions, every weekday for 3 weeks
</td>
<td>1 Hz, 10 Hz
</td>
<td>H7 coil and Magstim Rapid
</td>
<td>Significant reduction in preference for cocaine over monetary reward, among cocaine addicts in a lab environment, compared to low-frequency and sham.
</td>
<td>18
</td>
</tr>
</table>
<p><strong>Blame, Character Judgment, Intentionality Attribution</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[35]
</td>
<td>Left and right temporoparietal junction
</td>
<td>10 min
</td>
<td>1 Hz
</td>
<td>MagStim Rapid2
</td>
<td>Right TPJ inhibition increases perception of hostile intentionality in stories
</td>
<td>23
</td>
</tr>
<tr>
<td>[36]
</td>
<td>Right temporoparietal junction
</td>
<td>25 min
</td>
<td>1 Hz
</td>
<td>MagStim Super Rapid
</td>
<td>Right TPJ inhibition causes study subjects to attribute less moral blame to stories in which harm was attempted but failed.
</td>
<td>20
</td>
</tr>
<tr>
<td>[47]
</td>
<td>DMPFC
</td>
<td>During testing
</td>
<td>1 Hz
</td>
<td>Magstim Rapid 2 with butterfly coil
</td>
<td>Increased tendency to rate someone as “trustworthy” when both “good” and “bad” actions were attributed to them.
</td>
<td>20
</td>
</tr>
<tr>
<td>[48]
</td>
<td>DMPFC, right DLPFC
</td>
<td>During testing
</td>
<td>10 Hz
</td>
<td>Magstim Rapid 2 with butterfly coil
</td>
<td>Right DLPFC stimulation decreased the number of faces rated “trustworthy.” DMPFC stimulation eliminated the tendency to rate faces as more trustworthy if accompanied by “beautiful” vs. “ugly” adjectives.
</td>
<td>20
</td>
</tr>
</table>
<p><strong>Bottom-Up Processing</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[61]
</td>
<td>P3 and P4 sites (inferior parietal lobule)
</td>
<td>During test
</td>
<td>1 Hz
</td>
<td>Magstim Rapid 2 and butterfly coil
</td>
<td>Right parietal rTMS, but not left, reduced reaction times in searching for an X among many X’s that has a particular angle orientation, but not for searching for a non-X line among other X’s. Right IPL rTMS improves bottom-up perception.
</td>
<td>28
</td>
</tr>
</table>
<p><strong>Criticism</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[48]
</td>
<td>Left DLPFC
</td>
<td>One 20-min session
</td>
<td>20 Hz
</td>
<td>Magstim + figure-eight coil
</td>
<td>Significantly reduced salivary cortisol increase in response to negative/critical feedback, compared to sham stimulation.
</td>
<td>30
</td>
</tr>
<tr>
<td>[60]
</td>
<td>Left and right DLPFC
</td>
<td>One 20-min session
</td>
<td>20 Hz
</td>
<td>
</td>
<td>Significantly increased heart rate variability in response to negative/critical feedback after left DLPFC but not right DLPFC stimulation.
</td>
<td>38
</td>
</tr>
<tr>
<td>[105]
</td>
<td>Left DLPFC
</td>
<td>20 min
</td>
<td>20 Hz
</td>
<td>Magstim Rapid 2, figure eight coil
</td>
<td>Reduced cortisol response to negative/critical feedback in treated vs. sham
</td>
<td>75
</td>
</tr>
</table>
<p><strong>Delusions</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[14]
</td>
<td>Left DLPFC (F3 and F4)
</td>
<td>13 sessions in 3 weeks, 37 min each
</td>
<td>10 hz
</td>
<td>Magstim Rapid and figure-8 coil
</td>
<td>One patient being treated for depression developed his first-ever psychotic symptoms; agitated, anxious, felt observed & persecuted.
</td>
<td>1
</td>
</tr>
</table>
<p><strong>Deductive Reasoning</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[59]
</td>
<td>Right and left inferior frontal cortex (BA 45)
</td>
<td>10 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid with figure-8 coil, Brainsight
</td>
<td>Right IFC stimulation increased the “belief-bias” effect, worsening accuracy at syllogism evaluation when conclusions are logically valid but unrealistic. Left IFC stimulation removed the belief-bias effect; subjects performed a bit worse on “believable” syllogisms, and better on “unbelievable” ones.
</td>
<td>72
</td>
</tr>
</table>
<p><strong>Empathy</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[15]
</td>
<td>Bilateral medial PFC
</td>
<td>15 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid and Haut-coil
</td>
<td>Increased self-reported empathy in low-EQ, decreased self-reported empathy in high-EQ patients. No change in cognitive empathy.
</td>
<td>16
</td>
</tr>
<tr>
<td>[41]
</td>
<td>Dorsal medial prefrontal cortex
</td>
<td>During test
</td>
<td>1 Hz
</td>
<td>Magstim Rapid 2 with figure-8 coil & Brainstem
</td>
<td>Significantly (2x) more likely to misidentify anger and fear in facial expressions than controls, but not happiness or neutral.
</td>
<td>19
</td>
</tr>
<tr>
<td>[52]
</td>
<td>Right TPJ
</td>
<td>During test
</td>
<td>1 Hz
</td>
<td>Magstim Super Rapid, figure-eight coil, Brainsight
</td>
<td>rTMS to the right TPJ increases the rate of irritation after watching a sad video and decreases the rate of compassion/sympathy.
</td>
<td>
</td>
</tr>
<tr>
<td>[10]
</td>
<td>Bilateral dorsomedial prefrontal cortex; 7 cm anterior to M1
</td>
<td>15 min per session; 30 10-second trains and a 20 second rest period, for two weeks, 5 days per week
</td>
<td>5 Hz
</td>
<td>HAUTcoil and Magstim Rapid
</td>
<td>Significantly increased “social relatedness” and reduced “fantasizing” in treatment but not sham groups a month later, in autistic subjects
</td>
<td>28
</td>
</tr>
<tr>
<td>[32]
</td>
<td>Bilateral medial PFC
</td>
<td>15 min each weekday for 2 weeks
</td>
<td>5 Hz
</td>
<td>
</td>
<td>6 months later, autistic subject showed greater ease with eye contact, more comfortable around others, more physically affectionate, more considerate of others
</td>
<td>1
</td>
</tr>
<tr>
<td>[86]
</td>
<td>Medial prefrontal cortex
</td>
<td>During testing
</td>
<td>10 Hz
</td>
<td>Magstim Rapid 2, figure-8 coil, Brainsight
</td>
<td>Compared to control site & sham, reduced reaction times in identifying emotions in the test condition; increased smiles while looking at happy faces & frowns while looking at angry, sad, or disgusted faces
</td>
<td>16
</td>
</tr>
<tr>
<td>[104]
</td>
<td>Right DLPFC
</td>
<td>15 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid 2, figure 8 coil
</td>
<td>Compared to a control site, reduced reaction times at cognitive but not affective theory of mind tasks
</td>
<td>28
</td>
</tr>
</table>
<p><strong>Focus/Attention</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[72]
</td>
<td>Left DLPFC
</td>
<td>20 min
</td>
<td>10 Hz
</td>
<td>Magstim figure-8 coil
</td>
<td>Reduced reaction time in both congruent & incongruent conditions of a Stroop task; no change in interference effect, no effect on mood
</td>
<td>28
</td>
</tr>
<tr>
<td>[75]
</td>
<td>Right DLPFC
</td>
<td>20 min
</td>
<td>10 Hz
</td>
<td>
</td>
<td>Reduced reaction time relative to sham in both congruent and incongruent conditions of a Stroop task; no effect on mood
</td>
<td>20
</td>
</tr>
<tr>
<td>[78]
</td>
<td>Left DLPFC
</td>
<td>5 daily sessions
</td>
<td>10 Hz
</td>
<td>
</td>
<td>In healthy elderly subjects, significantly reduced reaction times (but no change in accuracy) in active but not sham stimulation on the Stroop task.
</td>
<td>16
</td>
</tr>
<tr>
<td>[80]
</td>
<td>Left DLPFC
</td>
<td>7 consecutive days
</td>
<td>10 Hz
</td>
<td>Magstim high speed, figure-8 coil
</td>
<td>Significantly reduced reaction time on both congruent & incongruent conditions of a Stroop task
</td>
<td>25
</td>
</tr>
<tr>
<td>[89]
</td>
<td>Left and right DLPFC
</td>
<td>During testing
</td>
<td>20 Hz
</td>
<td>Softaxic navigation
</td>
<td>Significantly reduced reaction time on action-naming task in older adults but not an object-naming task
</td>
<td>13
</td>
</tr>
<tr>
<td>[92]
</td>
<td>Right DLPFC
</td>
<td>20 min
</td>
<td>10 Hz
</td>
<td>MagStim + figure-8 coil
</td>
<td>Increased psychomotor speed, relative to sham control and left DLPFC, with right DLPFC stimulation
</td>
<td>36
</td>
</tr>
</table>
<p><strong>Grammar</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[24]
</td>
<td>Inferior frontal cortex; BA 44/45
</td>
<td>20 min
</td>
<td>1 Hz
</td>
<td>Magstim figure-8 coil
</td>
<td>Increased accuracy and decreased response time after stimulation in an artificial grammar learning task.
</td>
<td>25
</td>
</tr>
</table>
<p><strong>Hypnotic Suggestibility</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[13]
</td>
<td>Left DLPFC (F3 and F4)
</td>
<td>20 min
</td>
<td>1 Hz
</td>
<td>?
</td>
<td>Significantly (p = 0.002) increased intensity of hypnotic suggestion vs. sham. Cohen’s d =0.6
</td>
<td>23
</td>
</tr>
<tr>
<td>[26]
</td>
<td>Left DLPFC and right DLPFC
</td>
<td>4 sessions of 5 min each
</td>
<td>1 Hz
</td>
<td>Magstim Rapid 2
</td>
<td>right DLPFC stimulation, but not left, increased hypnotic suggestibility (Cohen’s d = 0.37)
</td>
<td>38
</td>
</tr>
</table>
<p><strong>Impulsivity</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[56]
</td>
<td>cerebellum
</td>
<td>10 min
</td>
<td>1 Hz
</td>
<td>Magpro X100 with B-65 butterfly coil
</td>
<td>Raises accuracy of BPD patients on an affective go/no-go task (measure of impulsivity) to the level of healthy controls.
</td>
<td>17
</td>
</tr>
<tr>
<td>[79]
</td>
<td>Left DLPFC
</td>
<td>3 blocks, 2.5 min each, before testing
</td>
<td>10 Hz
</td>
<td>Magstim 200 + figure 8 coil
</td>
<td>Significantly improved performance on a continuous performance task, a measure of impulsivity and response inhibition. Significant increase in negative affect relative to sham.
</td>
<td>17
</td>
</tr>
<tr>
<td>[90]
</td>
<td>Right DLPFC
</td>
<td>10 sessions
</td>
<td>10 Hz
</td>
<td>Magstim Rapid 2 and double air film coil
</td>
<td>No effect on a go/no-go task in alcoholics
</td>
<td>80
</td>
</tr>
<tr>
<td>[91]
</td>
<td>Right DLPFC
</td>
<td>10 sessions
</td>
<td>10 Hz
</td>
<td>
</td>
<td>Improves performance in a go/no-go task in bulimics
</td>
<td>39
</td>
</tr>
<tr>
<td>[102]
</td>
<td>Left DLPFC
</td>
<td>30 min
</td>
<td>1 Hz
</td>
<td>Magstim with figure-8 coil
</td>
<td>In a gambling game, DLPFC inhibition made players more likely to make choices with better short-term but worse long-term options.
</td>
<td>64
</td>
</tr>
</table>
<p><strong>Memory</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[11]
</td>
<td>Midline parietal site centered on the precuneus
</td>
<td>During test
</td>
<td>5 Hz, but not 1 Hz or 10 Hz
</td>
<td>Magstim Rapid Stimulator & 8-coil
</td>
<td>Improved accuracy & reaction time on a delayed matching task
</td>
<td>44
</td>
</tr>
<tr>
<td>[12]
</td>
<td>Right DLPFC
</td>
<td>10 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid Stimulator & 8-coil
</td>
<td>Improved accuracy (by 30%) in healthy patients and by 15% in memory impaired patients
</td>
<td>108
</td>
</tr>
<tr>
<td>[65]
</td>
<td>Left DLPFC
</td>
<td>15 min, every weekday for 2 weeks
</td>
<td>10 Hz
</td>
<td>Magstim Super Rapid + Brainsight
</td>
<td>No effect compared to sham stimulation on n-back performance in healthy subjects
</td>
<td>20
</td>
</tr>
<tr>
<td>[66]
</td>
<td>Left middle occipital gyrus, BA 19
</td>
<td>During testing
</td>
<td>5 Hz
</td>
<td>Magstim Super Rapid
</td>
<td>Increased accuracy and reduced reaction time in delayed matching task after sleep deprivation, compared to controls.
</td>
<td>33
</td>
</tr>
<tr>
<td>[82]
</td>
<td>Right or left DLPFC
</td>
<td>During testing
</td>
<td>10 Hz
</td>
<td>Magstim Super Rapid
</td>
<td>Significant improvement in reaction time (p=0.01) but not accuracy on a memory task
</td>
<td>32
</td>
</tr>
<tr>
<td>[94]
</td>
<td>Left anterior temporal lobe
</td>
<td>10 min
</td>
<td>1 Hz
</td>
<td>Magpro with butterfly coil
</td>
<td>36% reduction in false memories (falsely saying they remembered having seen words previously) vs. sham
</td>
<td>28
</td>
</tr>
<tr>
<td>[95]
</td>
<td>Left inferior frontal cortex
</td>
<td>During testing
</td>
<td>7 Hz
</td>
<td>Cadwell + round coil; Brainsight
</td>
<td>Significantly increased accuracy in recognition memory for words relative to right inferior frontal cortex & left parietal cortex
</td>
<td>12
</td>
</tr>
<tr>
<td>[96]
</td>
<td>Left DLPFC
</td>
<td>During memory encoding
</td>
<td>Theta bursts: 3 at 50 Hz
</td>
<td>Magpro X & cooled figure-8 coil
</td>
<td>Significantly higher accuracy in recognition memory task
</td>
<td>18
</td>
</tr>
<tr>
<td>[112]
</td>
<td>Left DLPFC
</td>
<td>22.5 min
</td>
<td>TBS at 50 Hz, HF-rTMS at 20 Hz
</td>
<td>Magstim Rapid 2, figure 8 coil, Brainsight
</td>
<td>Both TBS and high-frequency rTMS mproved accuracy and reaction time in 3-back task relative to sham
</td>
<td>60
</td>
</tr>
</table>
<p><strong>Mood</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[8]
</td>
<td>Right DLPFC (F4)
</td>
<td>20 min
</td>
<td>1 Hz
</td>
<td>Neopulse
</td>
<td>Reduced self-reported anxiety 0-65 min after treatment
</td>
<td>12
</td>
</tr>
<tr>
<td>[30]
</td>
<td>Left and right PFC
</td>
<td>20 min
</td>
<td>5 Hz
</td>
<td>Cadwell High Speed Magnetic Stimulator
</td>
<td>Left prefrontal cortex stimulation made subjects more sad; right prefrontal cortex stimulation made subjects more happy
</td>
<td>10
</td>
</tr>
<tr>
<td>[68]
</td>
<td>Right parietal cortex (P4)
</td>
<td>20 min
</td>
<td>2 Hz
</td>
<td>Neopulse
</td>
<td>Reduced depressive mood in healthy subjects, less avoidance of angry faces
</td>
<td>8
</td>
</tr>
<tr>
<td>[29]
</td>
<td>Right DLPFC
</td>
<td>20 min/day, 5 days/wk, for 2 weeks
</td>
<td>10 Hz
</td>
<td>?
</td>
<td>reduced affective instability and anger in BPD patients
</td>
<td>11
</td>
</tr>
</table>
<p><strong>Moral Decisionmaking (Helping, Sharing, Punishing, etc)</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[50]
</td>
<td>Right DLPFC
</td>
<td>15 minutes
</td>
<td>1 Hz
</td>
<td>MagPro X100, butterfly coil, Eximia 2.3 MRI-guided positioning system
</td>
<td>rTMS group was more likely than sham group to choose “utilitarian” answers in moral dilemmas like the trolley problem. (70% vs 56%)
</td>
<td>24
</td>
</tr>
<tr>
<td>[57]
</td>
<td>Right DLPFC
</td>
<td>
</td>
<td>1 Hz
</td>
<td>
</td>
<td>Right DLPFC stimulation, but not left DLPFC or sham, increased tendency to accept low offers in the Ultimatum Game (45% vs 15%). No difference in perceived unfairness.
</td>
<td>52
</td>
</tr>
<tr>
<td>[58]
</td>
<td>Right DLPFC
</td>
<td>15 min
</td>
<td>1 Hz
</td>
<td>
</td>
<td>Right DLPFC stimulation, compared to sham and left DLPFC stimulation, reduces the amount people share in a trust game with reputation, but not in the anonymous condition.
</td>
<td>87
</td>
</tr>
<tr>
<td>[87]
</td>
<td>Right and left DLPFC
</td>
<td>
</td>
<td>1 Hz
</td>
<td>MagPro R30, figure 8 coil, MRI navigation
</td>
<td>Participants played the Ultimatum Game and then the Dictator Game. Right DLPFC was more likely than the other two groups to give unfair offers in the dictator game, whether in response to fair or unfair offers.
</td>
<td>46
</td>
</tr>
<tr>
<td>[97]
</td>
<td>Right DLPFC
</td>
<td>12 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid with figure-8 coil
</td>
<td>Participants were significantly faster to accept unfair offers in the Ultimatum Game with true vs sham stimulation, but no less likely to rate the offers as unfair
</td>
<td>7
</td>
</tr>
<tr>
<td>[98]
</td>
<td>Right DLPFC
</td>
<td>40 sec
</td>
<td>5Hz theta bursts of 50 Hz pulses for 40 sec
</td>
<td>Magventure
</td>
<td>Stimulated vs. placebo participants were significantly more likely (60% vs 45%) to penalize unfair opponents in the Ultimatum Game by presenting them with a bad offer next time.
</td>
<td>19
</td>
</tr>
<tr>
<td>[37]
</td>
<td>Right TPJ
</td>
<td>20 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid, figure-8 coil
</td>
<td>Decreased tendency to pay to punish outgroup members more harshly than ingroup members (soccer fandoms)
</td>
<td>36
</td>
</tr>
<tr>
<td>[38]
</td>
<td>DLPFC
</td>
<td>30 min
</td>
<td>1 Hz
</td>
<td>
</td>
<td>Reduced punishment for culpable criminal acts but not reduced blame
</td>
<td>66
</td>
</tr>
<tr>
<td>[99]
</td>
<td>Left DLPFC, BA46
</td>
<td>During testing
</td>
<td>10 Hz
</td>
<td>Magstim Rapid 2, figure-8 coil, Brainsight
</td>
<td>Significantly more likely (relative to control & sham) to be willing to help in hypothetical social situation
</td>
<td>25
</td>
</tr>
<tr>
<td>[100]
</td>
<td>Right DLPFC & DMPFC
</td>
<td>During testing
</td>
<td>50 Hz cTBS
</td>
<td>
</td>
<td>Inhibiting right DLPFC increased generosity in an ultimatum game to high SES players, Cohen’s d 0.95; inhibiting DMPFC increased generosity to low SES players.
</td>
<td>58
</td>
</tr>
<tr>
<td>[101]
</td>
<td>Right TPJ
</td>
<td>During testing
</td>
<td>50 Hz cTBS
</td>
<td>Magstim Rapid2, BrainVoyager neuronavigation from MRI images
</td>
<td>Sham-stimulated subjects share more in a trust game with “ingroup” than “outgroup” players; TPJ inhibited subjects don’t, they share more with the outgroup
</td>
<td>22
</td>
</tr>
</table>
<p><strong>Numerical & Quantitative Reasoning</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[65]
</td>
<td>Inferior parietal lobule, left and right
</td>
<td>10 min
</td>
<td>5 Hz
</td>
<td>Magstim Super Rapid
</td>
<td>Untreated or control patients tend to underestimate the midpoint between two large numbers. Right IPL stimulation reduces the error.
</td>
<td>14
</td>
</tr>
<tr>
<td>[92]
</td>
<td>Left anterior temporal lobe
</td>
<td>15 min
</td>
<td>1 Hz
</td>
<td>Medtronic MagPro
</td>
<td>Significantly improved ability to guess the number of shapes without counting (savant-like skill)
</td>
<td>12
</td>
</tr>
<tr>
<td>[103]
</td>
<td>Intraparietal sulcus, left and right
</td>
<td>10 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid w/ Brainsight
</td>
<td>Right IPL stimulation, relative to sham, speeded up reaction times on a number and dot estimation task; left IPL stimulation slowed it down.
</td>
<td>36
</td>
</tr>
<tr>
<td>[106]
</td>
<td>Left and right supramarginal gyrus
</td>
<td>During testing
</td>
<td>10 Hz
</td>
<td>Magstim Rapid2 w/ Brainsight
</td>
<td>Right SMG stimulation reduced reaction time on a mental arithmetic task; left SMG stimulation increased it
</td>
<td>20
</td>
</tr>
</table>
<p><strong>Pain</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[73]
</td>
<td>Right M1, right DLPFC
</td>
<td>15 min
</td>
<td>10 Hz
</td>
<td>MagProX100, figure-8 coil
</td>
<td>Both right M1 and DLPFC stimulation, relative to sham, reduced sensitivity to cold pain, but not heat pain or cold/heat detection
</td>
<td>52
</td>
</tr>
<tr>
<td>[74]
</td>
<td>Left DLPFC
</td>
<td>10 sessions, 20 minutes/session
</td>
<td>10 Hz
</td>
<td>NeoPulse NeoTonus with a solid coil
</td>
<td>Significantly more pain improvement (p<0.01, 20% drop) with real vs. sham stimulation in fibromyalgia patients
</td>
<td>20
</td>
</tr>
<tr>
<td>[76]
</td>
<td>M1 contralateral to pain side
</td>
<td>3 sessions, 3 weeks apart: sham, hotspot, and neuronavigated
</td>
<td>10 Hz
</td>
<td>MagPro X100 and Excimia neuronavigation system
</td>
<td>Significantly reduced (17%, p < 0.0001) pain score in chronic neuropathic pain patients
</td>
<td>66
</td>
</tr>
<tr>
<td>[77]
</td>
<td>Left DLPFC
</td>
<td>10 daily sessions
</td>
<td>10 Hz
</td>
<td>Neuronetics Neopulse with figure-8 coil & Brainsight
</td>
<td>Reduced pain in neuropathic chronic pain patients relative to sham
</td>
<td>4
</td>
</tr>
</table>
<p><strong>Perceptual Illusions</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[32]
</td>
<td>Cerebellum
</td>
<td>20 min
</td>
<td>1 Hz
</td>
<td>Neotonus
</td>
<td>Illusion of falling or drifting
</td>
<td>1
</td>
</tr>
<tr>
<td>[64]
</td>
<td>Right inferior parietal lobule
</td>
<td>10 min
</td>
<td>1 Hz
</td>
<td>
</td>
<td>Illusion of time dilation
</td>
<td>10
</td>
</tr>
<tr>
<td>[84]
</td>
<td>Right anterior temporal lobe
</td>
<td>5 days/week for two weeks
</td>
<td>1 Hz
</td>
<td>Cadwell
</td>
<td>A patient with post-head-injury music hallucinations was treated with rTMS
</td>
<td>1
</td>
</tr>
<tr>
<td>[88]
</td>
<td>M1
</td>
<td>During testing
</td>
<td>1 Hz
</td>
<td>
</td>
<td>Motor cortex inhibition increases the “sense of effort” in a force-matching task
</td>
<td>10
</td>
</tr>
</table>
<p><strong>Phobias and Fear Conditioning</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[43]
</td>
<td>Medial PFC
</td>
<td>20 min
</td>
<td>10 Hz
</td>
<td>Medtronic MagPro X100 with round coil
</td>
<td>Increased reductions in anxiety and avoidance of heights after an exposure therapy program, relative to sham stimulation.
</td>
<td>39
</td>
</tr>
<tr>
<td>[45]
</td>
<td>Medial PFC
</td>
<td>20 min
</td>
<td>10 Hz
</td>
<td>Medtronic MagPro X100 with round coil
</td>
<td>More rapid extinction of a conditioned fear eyeblink startle response & skin conduction response when the conditioned stimulus was removed, than with sham stimulation.
</td>
<td>85
</td>
</tr>
<tr>
<td>[71]
</td>
<td>Intraparietal sulcus
</td>
<td>During test
</td>
<td>1 Hz
</td>
<td>Magventure Magpro 100
</td>
<td>Reduced blink startle response in reaction to predictable and unpredictable scary stimuli (loud sounds)
</td>
<td>25
</td>
</tr>
</table>
<p><strong>Planning & Sequencing</strong></p>
<table>
<tr>
<td>[29]
</td>
<td>Right DLPFC
</td>
<td>20 min/day, 5 days/wk, for 2 weeks
</td>
<td>10 Hz
</td>
<td>?
</td>
<td>Significant improvement at 3 months in the Tower of London task
</td>
<td>11
</td>
</tr>
</table>
<p><strong>Reading</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[62]
</td>
<td>Left inferior parietal lobule (P3 and P4)
</td>
<td>10 min
</td>
<td>5 Hz
</td>
<td>Magstim Super Rapid with figure-8 coil
</td>
<td>Left IPL stimulation, but not right or control or supratemporal gyrus, reduced errors in reading non-words in normal readers
</td>
<td>10
</td>
</tr>
<tr>
<td>[63]
</td>
<td>Left inferior parietal lobule (P3 and P4)
</td>
<td>10 min
</td>
<td>5 Hz
</td>
<td>Magstim Super Rapid with figure-8 coil
</td>
<td>Left IPL stimulation increased non-word reading accuracy in dyslexics
</td>
<td>10
</td>
</tr>
<tr>
<td>[83]
</td>
<td>Left and right DLPFC
</td>
<td>During testing
</td>
<td>15 Hz
</td>
<td>Magstim Super Rapid with figure-8 coil
</td>
<td>Reduced reaction times for sentence comprehension tasks but decreased accuracy in interpreting idiomatic sentences.
</td>
<td>14
</td>
</tr>
</table>
<p><strong>Risk Aversion</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[29]
</td>
<td>Right DLPFC
</td>
<td>6 min
</td>
<td>1 Hz
</td>
<td>Nexstim MRI-assisted device
</td>
<td>Increased rate of hitting the ceiling in a ball game where the aim is to get as close as possible without touching the ceiling. Cohen’s d = 0.98
</td>
<td>12
</td>
</tr>
<tr>
<td>[98]
</td>
<td>Right DLPFC
</td>
<td>15 min
</td>
<td>1 Hz
</td>
<td>Magstim, figure-8 coil
</td>
<td>Increased high-risk choices and worse overall performance in a gambling task, relative to sham and left DLPFC
</td>
<td>27
</td>
</tr>
</table>
<p><strong>Self-Other Discrimination</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[5]
</td>
<td>Right inferior parietal lobule
</td>
<td>20 min, before test
</td>
<td>1 Hz
</td>
<td>Magstim Rapid Stimulator
</td>
<td>Increased tendency to identify images of others’ faces as own
</td>
<td>8
</td>
</tr>
<tr>
<td>[34]
</td>
<td>M1, primary motor cortex
</td>
<td>20 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid 2
</td>
<td>Rubber hand illusion was strengthened, only when stimulation was on the opposite side’s motor cortex
</td>
<td>32
</td>
</tr>
<tr>
<td>[52][53]
</td>
<td>Right temporoparietal junction
</td>
<td>30 min/day for 3 weeks
</td>
<td>1 Hz
</td>
<td>Magstim Super Rapid
</td>
<td>50% of subjects with depersonalization disorder had at least a 25% improvement on a severity score, especially in symptoms related to “anomalous body experiences” (50% mean improvement, p = 0.008)
</td>
<td>12
</td>
</tr>
<tr>
<td>[54]
</td>
<td>Right temporoparietal junction (MNI coordinates (62, -34, 30)
</td>
<td>During testing
</td>
<td>Theta burst stimulation, triplets at 30 Hz (inhibitory)
</td>
<td>Magpro x100 with MC-B70 butterfly coil
</td>
<td>Decreased the sense of agency relative to control stimulation
</td>
<td>15
</td>
</tr>
<tr>
<td>[65]
</td>
<td>Posterior parietal cortex
</td>
<td>During testing
</td>
<td>Theta burst stimulation, triplets at 50 Hz (inhibitory)
</td>
<td>Magstim 200
</td>
<td>Decreased phantom sensations in spinal cord injury patients during session
</td>
<td>5
</td>
</tr>
<tr>
<td>[70]
</td>
<td>Inferior parietal cortex (MNI coordinates (44, -54, 38)
</td>
<td>During testing
</td>
<td>10 Hz
</td>
<td>Magstim Rapid, custom figure-8 coil, Brainsight
</td>
<td>Reduced sense of agency in participant-controlled movements on computer screen
</td>
<td>14
</td>
</tr>
</table>
<p><strong>Social Attention</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[69]
</td>
<td>Posterior parietal cortex
</td>
<td>During test
</td>
<td>10 Hz, dual pulse (inhibitory)
</td>
<td>Two Magstim Mode 200
</td>
<td>Increased reaction time when distracted by pointing hands in a task involving a pointing arrow
</td>
<td>14
</td>
</tr>
</table>
<p><strong>Sensory Perception</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[3]
</td>
<td>Index finger region of primary somatosensory cortex
</td>
<td>During test
</td>
<td>5 Hz
</td>
<td>Magstim Rapid Stimulator & 8-coil
</td>
<td>Improved tactile acuity; lowered discrimination threshold
</td>
<td>33
</td>
</tr>
<tr>
<td>[21]
</td>
<td>Index finger region of primary somatosensory cortex
</td>
<td>During test
</td>
<td>50 Hz bursts for 2 s every 10 s, for 3 min
</td>
<td>Magstim Rapid & 8-coil
</td>
<td>Improved tactile acuity
</td>
<td>23
</td>
</tr>
</table>
<p><strong>Spatial Estimation</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[52]
</td>
<td>Right temporoparietal junction
</td>
<td>20 sec
</td>
<td>Trains of 3 pulses at 50 Hz, delivered at 5 Hz, for 20 seconds
</td>
<td>Magstim model 200 Monopulse
</td>
<td>Inhibitory rTPJ stimulation, but not sham or control, increased the error rate for judging the angle of a rod off the vertical.
</td>
<td>22
</td>
</tr>
</table>
<p><strong>Task Switching</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[31]
</td>
<td>Right DLPFC
</td>
<td>20 min
</td>
<td>10 Hz
</td>
<td>Magstim Rapid Stimulator & 8-coil
</td>
<td>Reduced reaction time (20% faster) on a task switching task
</td>
<td>22
</td>
</tr>
</table>
<p><strong>Time Discounting</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[40]
</td>
<td>Medial prefrontal cortex
</td>
<td>During testing
</td>
<td>10 Hz
</td>
<td>Magstim Rapid 2 with double cone coil
</td>
<td>Significantly increased preference for larger delayed rewards and decreased preference for small immediate rewards.
</td>
<td>24
</td>
</tr>
</table>
<p><strong>Time Estimation</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[67]
</td>
<td>Superior parietal cortex (Pz)
</td>
<td>15 min
</td>
<td>1 Hz
</td>
<td>Neuro-Ms Stimulator
</td>
<td>Significantly reduced error in estimating 9-second time intervals (but not shorter)
</td>
<td>23
</td>
</tr>
<tr>
<td>[111]
</td>
<td>Superior parietal cortex
</td>
<td>
</td>
<td>1 Hz
</td>
<td>Neuro-Ms stimulator
</td>
<td>Increased error in 4 and 9 second time intervals,
</td>
<td>20
</td>
</tr>
</table>
<p><strong>Threat Perception</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[68]
</td>
<td>Right posterior parietal cortex (P4)
</td>
<td>20 min
</td>
<td>1 Hz
</td>
<td>Mag-Pro X100 with butterfly coil
</td>
<td>Compared to sham or left PPC controls, right PPC inhibition increases reaction time on a visual search task in response to a scary (loud sound) distractor but not a neutral distractor.
</td>
<td>26
</td>
</tr>
<tr>
<td>[85]
</td>
<td>Right DLPFC
</td>
<td>20 min
</td>
<td>10 Hz
</td>
<td>Magstim with figure-8 coil & MRI guidance
</td>
<td>No effect on mood or anxiety; treated subjects showed more reaction-time impairment when distracted by an angry face in a cueing task, but not a neutral face. The higher anxiety was at baseline, the more rTMS increased attentional bias to threat.
</td>
<td>28
</td>
</tr>
<tr>
<td>[109]
</td>
<td>Intraparietal sulcus
</td>
<td>During testing
</td>
<td>1 Hz
</td>
<td>MagPro 100 & Cool-B65 A/P coil
</td>
<td>Compared to sham stimulation or no stimulation, rTMS reduced the startle response to electric shocks
</td>
<td>19
</td>
</tr>
<tr>
<td>[110]
</td>
<td>Right DLPFC
</td>
<td>During testing
</td>
<td>10 Hz
</td>
<td>MagPro 100 & Cool-B65 A/P coil
</td>
<td>Compared to sham stimulation, increased startle response to electric shocks
</td>
<td>24
</td>
</tr>
</table>
<p><strong>Visual Search/Perception</strong></p>
<table>
<tr>
<td><strong>Reference</strong>
</td>
<td><strong>Brain Location</strong>
</td>
<td><strong>Treatment Duration</strong>
</td>
<td><strong>Frequency</strong>
</td>
<td><strong>Machine</strong>
</td>
<td><strong>Result</strong>
</td>
<td><strong>N</strong>
</td>
</tr>
<tr>
<td>[81]
</td>
<td>P3 and P4 sites (posterior parietal cortex)
</td>
<td>During test
</td>
<td>1 Hz
</td>
<td>Magstim Rapid, Figure-8 Coil
</td>
<td>Right, but not left or sham, parietal rTMS improved reaction times when a distractor is present on a visual search task.
</td>
<td>8
</td>
</tr>
<tr>
<td>[107]
</td>
<td>Left posterior parietal cortex
</td>
<td>10 min
</td>
<td>1 Hz
</td>
<td>Magstim Rapid 2, Figure-8 coil
</td>
<td>Left, but not right, posterior parietal cortex rTMS reduced reaction times in a visual search task for picking out a mirror image letter from a field of letters
</td>
<td>88
</td>
</tr>
<tr>
<td>[108]
</td>
<td>Right posterior parietal cortex
</td>
<td>
</td>
<td>1 Hz
</td>
<td>Magstim Super Rapid, Figure 8 coil
</td>
<td>Compared to control stimulation at the vertex, right PPC stimulation reduced reaction times in a visual detection task with low-frequency Gabor filters
</td>
<td>36
</td>
</tr>
<tr>
<td>[113]
</td>
<td>Right intraparietal sulcus
</td>
<td>8 min
</td>
<td>1 Hz
</td>
<td>NeoTonus with Brainsight and MRI guidance
</td>
<td>Compared to sham stimulation and left IPS stimulation, right IPS stimulation significantly reduced errors in identifying the color and shape of figures briefly flashed in peripheral vision.
</td>
<td>24
</td>
</tr>
</table>
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<p>[63]Costanzo, Floriana, et al. “How to improve reading skills in dyslexics: the effect of high frequency rTMS.” <em>Neuropsychologia</em> 51.14 (2013): 2953-2959.</p>
<p>[64]Peatfield, Nicholas, and Lorella Battelli. “rTMS to right inferior parietal lobule dilates the subjective experience of time.” <em>Journal of Vision</em> 13.9 (2013): 316-316.</p>
<p>[65]Gaudeau-Bosma, Christian, et al. “Effect of two weeks of rTMS on brain activity in healthy subjects during an n-back task: a randomized double blind study.” <em>Brain stimulation</em> 6.4 (2013): 569-575.</p>
<p>[66]Luber, Bruce, et al. “Extended remediation of sleep deprived-induced working memory deficits using fMRI-guided transcranial magnetic stimulation.” <em>Sleep</em> 36.6 (2013): 857-871.</p>
<p>[67]Rocha, Kaline, et al. “Low-frequency rTMS stimulation over superior parietal cortex medially improves time reproduction and increases the right dorsolateral prefrontal cortex predominance.” <em>International Journal of Neuroscience</em> 129.6 (2019): 523-533.</p>
<p>[68]van Honk, Jack, et al. “Reductions in phenomenological, physiological and attentional indices of depressive mood after 2 Hz rTMS over the right parietal cortex in healthy human subjects.” <em>Psychiatry Research</em> 120.1 (2003): 95-101.</p>
<p>[69]Porciello, Giuseppina, et al. “rTMS-induced virtual lesion of the posterior parietal cortex (PPC) alters the control of reflexive shifts of social attention triggered by pointing hands.” <em>Neuropsychologia</em> 59 (2014): 148-156.</p>
<p>[70]Ritterband-Rosenbaum, Anina, et al. “10 Hz rTMS over right parietal cortex alters sense of agency during self-controlled movements.” <em>Frontiers in human neuroscience</em> 8 (2014): 471.</p>
<p>[71]Balderston, Nicholas L., et al. “Low-frequency parietal repetitive transcranial magnetic stimulation reduces fear and anxiety.” <em>Translational psychiatry</em> 10.1 (2020): 1-10.</p>
<p>[72]Vanderhasselt, Marie-Anne, et al. “The influence of rTMS over the left dorsolateral prefrontal cortex on Stroop task performance.” <em>Experimental brain research</em> 169.2 (2006): 279-282.</p>
<p>[73]Nahmias, Frédéric, et al. “Diffuse analgesic effects of unilateral repetitive transcranial magnetic stimulation (rTMS) in healthy volunteers.” <em>PAIN®</em> 147.1-3 (2009): 224-232.</p>
<p>[74]Short, E. Baron, et al. “Ten sessions of adjunctive left prefrontal rTMS significantly reduces fibromyalgia pain: a randomized, controlled pilot study.” <em>Pain</em> 152.11 (2011): 2477-2484.</p>
<p>[75]Vanderhasselt, Marie-Anne, et al. “The influence of rTMS over the right dorsolateral prefrontal cortex on top-down attentional processes.” <em>Brain research</em> 1137 (2007): 111-116.</p>
<p>[76]Ayache, S. S., et al. “Analgesic effects of navigated motor cortex rTMS in patients with chronic neuropathic pain.” <em>European Journal of Pain</em> 20.9 (2016): 1413-1422.</p>
<p>[77]Borckardt, Jeffrey J., et al. “A pilot study investigating the effects of fast left prefrontal rTMS on chronic neuropathic pain.” <em>Pain Medicine</em> 10.5 (2009): 840-849.</p>
<p>[78]Kim, Sang Hee, et al. “Effects of five daily high-frequency rTMS on Stroop task performance in aging individuals.” <em>Neuroscience research</em> 74.3-4 (2012): 256-260.</p>
<p>[79]Hwang, Ji Hee, et al. “Acute high-frequency rTMS of the left dorsolateral prefrontal cortex and attentional control in healthy young men.” <em>Brain research</em> 1329 (2010): 152-158.</p>
<p>[80]Li, Yanmin, et al. “The effects of high-frequency rTMS over the left DLPFC on cognitive control in young healthy participants.” <em>PloS one</em> 12.6 (2017): e0179430.</p>
<p>[81]Hodsoll, John, Carmel Mevorach, and Glyn W. Humphreys. “Driven to less distraction: rTMS of the right parietal cortex reduces attentional capture in visual search.” <em>Cerebral Cortex</em> 19.1 (2009): 106-114.</p>
<p>[82]Preston, Gilbert, et al. “Effects of 10 Hz rTMS on the neural efficiency of working memory.” <em>Journal of cognitive neuroscience</em> 22.3 (2010): 447-456.</p>
<p>[83]Rizzo, Silvia, Marco Sandrini, and Costanza Papagno. “The dorsolateral prefrontal cortex in idiom interpretation: An rTMS study.” <em>Brain research bulletin</em> 71.5 (2007): 523-528.</p>
<p>[84]Cosentino, G., et al. “A case of post-traumatic complex auditory hallucinosis treated with rTMS.” <em>Neurocase</em> 16.3 (2010): 267-272.</p>
<p>[85]Vanderhasselt, Marie-Anne, et al. “The effects of high frequency rTMS on negative attentional bias are influenced by baseline state anxiety.” <em>Neuropsychologia</em> 49.7 (2011): 1824-1830.</p>
<p>[86]Balconi, Michela, and Ylenia Canavesio. “High-frequency rTMS improves facial mimicry and detection responses in an empathic emotional task.” <em>Neuroscience</em> 236 (2013): 12-20.</p>
<p>[87]Müller-Leinß, Jan-Martin, et al. “Retaliation or selfishness? An rTMS investigation of the role of the dorsolateral prefrontal cortex in prosocial motives.” <em>Social neuroscience</em> 13.6 (2018): 701-709.</p>
<p>[88]Takarada, Yudai, et al. “Inhibition of the primary motor cortex can alter one’s “sense of effort”: effects of low-frequency rTMS.” <em>Neuroscience research</em> 89 (2014): 54-60.</p>
<p>[89]Cotelli, Maria, et al. “Action and object naming in physiological aging: an rTMS study.” <em>Frontiers in aging neuroscience</em> 2 (2010): 151.</p>
<p>[90]Schluter, Renée S., Ruth J. van Holst, and Anna E. Goudriaan. “Effects of ten sessions of high frequency repetitive Transcranial magnetic stimulation (HF-rTMS) add-on treatment on impulsivity in alcohol use disorder.” <em>Frontiers in neuroscience</em> 13 (2019): 1257.</p>
<p>[91]Guillaume, Sebastien, et al. “Improving decision‐making and cognitive impulse control in bulimia nervosa by rTMS: An ancillary randomized controlled study.” <em>International Journal of Eating Disorders</em> 51.9 (2018): 1103-1106.</p>
<p>[92]Baeken, Chris, et al. “Impact of one HF-rTMS session on fine motor function in right-handed healthy female subjects: a comparison of stimulation over the left versus the right dorsolateral prefrontal cortex.” <em>Neuropsychobiology</em> 65.2 (2012): 96-102.</p>
<p>[93]Snyder, Allan, et al. “Savant-like numerosity skills revealed in normal people by magnetic pulses.” <em>Perception</em> 35.6 (2006): 837-845.</p>
<p>[94]Gallate, Jason, et al. “Reducing false memories by magnetic pulse stimulation.” <em>Neuroscience letters</em> 449.3 (2009): 151-154.</p>
<p>[95]Köhler, Stefan, et al. “Effects of left inferior prefrontal stimulation on episodic memory formation: a two-stage fMRI—rTMS study.” <em>Journal of cognitive neuroscience</em> 16.2 (2004): 178-188.</p>
<p>[96]Demeter, Elise, et al. “Short theta burst stimulation to left frontal cortex prior to encoding enhances subsequent recognition memory.” <em>Cognitive, Affective, & Behavioral Neuroscience</em> 16.4 (2016): 724-735.</p>
<p>[97]Van’t Wout, Mascha, et al. “Repetitive transcranial magnetic stimulation over the right dorsolateral prefrontal cortex affects strategic decision-making.” <em>Neuroreport</em> 16.16 (2005): 1849-1852.</p>
<p>[98]Knoch, Daria, et al. “Disruption of right prefrontal cortex by low-frequency repetitive transcranial magnetic stimulation induces risk-taking behavior.” <em>Journal of Neuroscience</em> 26.24 (2006): 6469-6472.</p>
<p>[99]Balconi, Michela, and Ylenia Canavesio. “High-frequency rTMS on DLPFC increases prosocial attitude in case of decision to support people.” <em>Social neuroscience</em> 9.1 (2014): 82-93.</p>
<p>[100]Christov-Moore, Leonardo, et al. “Increasing generosity by disrupting prefrontal cortex.” <em>Social Neuroscience</em> 12.2 (2017): 174-181.</p>
<p>[101]Fujino, Junya, et al. “Role of the right temporoparietal junction in intergroup bias in trust decisions.” Human brain mapping 41.6 (2020): 1677-1688.</p>
<p>[102]Essex, Brian G., et al. “The impact of the posterior parietal and dorsolateral prefrontal cortices on the optimization of long-term versus immediate value.” <em>Journal of Neuroscience</em> 32.44 (2012): 15403-15413.</p>
<p>[103]Cappelletti, Marinella, et al. “rTMS over the intraparietal sulcus disrupts numerosity processing.” <em>Experimental Brain Research</em> 179.4 (2007): 631-642.</p>
<p>[104]Kalbe, Elke, et al. “Dissociating cognitive from affective theory of mind: a TMS study.” <em>cortex</em> 46.6 (2010): 769-780.</p>
<p>[105]Pulopulos, Matias M., et al. “The effect of HF-rTMS over the left DLPFC on stress regulation as measured by cortisol and heart rate variability.” <em>Hormones and Behavior</em> 124 (2020): 104803.</p>
<p>[106]Klichowski, Michal, and Gregory Kroliczak. “Mental shopping calculations: a transcranial magnetic stimulation study.” <em>Frontiers in Psychology</em> 11 (2020).</p>
<p>[107]Mangano, Giuseppa Renata, et al. “Repetitive transcranial magnetic stimulation over the left parietal cortex facilitates visual search for a letter among its mirror images.” <em>Neuropsychologia</em> 70 (2015): 196-205.</p>
<p>[108]Elkin-Frankston, Seth, Richard J. Rushmore, and Antoni Valero-Cabré. “Low frequency transcranial magnetic stimulation of right posterior parietal cortex reduces reaction time to perithreshold low spatial frequency visual stimuli.” <em>Scientific reports</em> 10.1 (2020): 1-9.</p>
<p>[109]Balderston, Nicholas L., et al. “Low-frequency parietal repetitive transcranial magnetic stimulation reduces fear and anxiety.” <em>Translational psychiatry</em> 10.1 (2020): 1-10.</p>
<p>[110]Balderston, Nicholas L., et al. “Mechanistic link between right prefrontal cortical activity and anxious arousal revealed using transcranial magnetic stimulation in healthy subjects.” <em>Neuropsychopharmacology</em> 45.4 (2020): 694-702.</p>
<p>[111]Manaia, Fernanda, et al. “The role of low-frequency rTMS in the superior parietal cortex during time estimation.” <em>Neurological Sciences</em> 40.6 (2019): 1183-1189.</p>
<p>[112]Wu, Xingqi, et al. “Improved cognitive promotion through accelerated magnetic stimulation.” <em>Eneuro</em> 8.1 (2021).</p>
<p>[113]Esterman, Michael, Timothy Verstynen, and Lynn C. Robertson. “Attenuating illusory binding with TMS of the right parietal cortex.” <em>Neuroimage</em> 35.3 (2007): 1247-1255.</p>IntroductionHow To Be An Educated Layman2021-06-09T00:00:00+00:002021-06-09T00:00:00+00:00https://srconstantin.github.io/2021/06/09/Educated-Layman<p>Doing business development for new initiatives at Nanotronics is kind of like being an “educated layman” for a living. My blog is also a pretty good example of an “educated layman”’s thinking about a variety of issues. So I plausibly know what I’m talking about here, and may have useful advice for other people looking to succeed at being “educated laymen.”</p>
<p>What does being an “educated layman” mean, to me?</p>
<p>Basically, an “expert” or “specialist” is someone who has spent their whole life studying or working on a specific narrow topic. If it’s an academic topic, they’ll typically have a PhD in that topic.</p>
<p>An “educated layman” is someone who is not an expert, but who, in a discussion with experts about their field of specialization, can contribute useful ideas.</p>
<p>An “educated layman” will typically <em>know less stuff</em> than any expert does about their field of expertise, but can still contribute good ideas that no expert has thought of.</p>
<p>How is that possible? Usually, because the “educated layman” brings a different perspective, or a toolkit from another field, or has an unusual set of priorities that the expert community hasn’t been optimizing for.</p>
<p>There are a couple standard examples I’ve encountered where it’s useful to be an “educated layman.”</p>
<ol>
<li>
<p>Making decisions about whether/how to apply a new technology. If I’m investigating how XYZ tech might fit in with my own company’s work, or a customer’s work, then I don’t need to know nearly as much as the specialists who spend their lives <em>creating</em> XYZ tech. I just need to know inputs and outputs – how much does it cost, what does it require, what results does it produce – and just enough about how the tech works to be able to make some generalizations about that beyond the specific reported examples in the published literature.</p>
</li>
<li>
<p>Making medical decisions as a patient. In order to decide what treatment you should get, you don’t need to know all the things a doctor needs to know. You don’t need to be able to actually <em>perform</em> the treatment. You don’t need to know about all the different diseases a doctor might encounter. You need to know about <em>your</em> disease, and how safe/effective different treatments are for that disease. You may actually have more time to read the literature on your specific disease than your doctor does, especially if it’s a rare disease. And, you may have different incentives than your doctor. The treatment that’s actually best for you may not be popular among clinicians, for reasons that don’t apply to you (like high risk of side effects in a patient population you’re not part of.) So it’s possible for an “educated layman” patient to have a good idea that an “expert” doesn’t have.</p>
</li>
<li>
<p>Managing experts. You don’t need to know how to do their jobs in order to propose useful ideas that they haven’t thought of. You have a high-level view of what everyone is working on and what goal it’s for, and they have a tendency to get hyperfocused on the specific task at hand. You can ask a “dumb” question like “how does this task impact our overall goal?” and very quickly find out “whoops, it doesn’t help at all, maybe it’s time to quit working on this sub-project.” You can be a fresh set of eyes, and a “North Star” to keep everyone oriented towards the overall mission.</p>
</li>
<li>
<p>Importing a highly general “toolkit” or technology to a field where it hasn’t penetrated yet. I see this very often with statistics or computer automation. A stats/ML/computers person can often very easily create a ton of value just by importing the techniques they’re familiar with to a field where nobody has heard of them. You need domain knowledge to do this effectively, but not as <em>much</em> domain knowledge as the experts have. Just enough to check whether the technology you introduce is actually making the field’s problems better rather than worse.</p>
</li>
</ol>
<p>Being an “educated layman” in the sense I’m talking about presupposes that you believe there’s actual value in a field and its experts to begin with. If you think the whole business is bunk, like, say, astrology, then you’d have no reason to teach yourself enough of the technical details of astrology to converse intelligently with astrologers.</p>
<p>You can think a “field” or community of expertise is flawed, biased, or just missing some context that you have, and still consider it valuable enough to dialogue with and learn from. <em>This</em> is the context in which it can be worth “tooling up” in a field enough to function as an “educated layman.” You’ll be hoping to make a contribution as a non-expert – so, definitionally, you believe that the field is “missing” something that you can provide – but you’ll also be learning from and collaborating with experts very heavily.</p>
<p>Being an “educated layman” is in this way very different from the kind of anti-expert view you see in, say, Nassim Taleb’s opinions about social science. He doesn’t think there’s <em>any</em> real knowledge in contemporary social science, so he doesn’t bother to learn their specialized lingo. He dismisses them, and they dismiss him.</p>
<p>That’s fine, if you’re confident there’s nothing there. This post is for situations when you <em>do</em> think there’s something there – even if you’re skeptical about some parts.</p>
<p>I’m most confident in my ability to do the “educated layman” thing in biology and medicine, since I’ve been doing it the longest there.</p>
<p>Really, there’s no such thing as reaching “educated layman” status in something as broad as “biology” as a whole. What you can do is tool up to the point of being able to have discussions with experts <em>in a super-specific question</em>. And I’ve done it in enough specific biological or medical topics to be pretty confident in my ability to do it again on a new topic, assuming there’s the right kind and distribution of available literature.</p>
<p>What do I mean by that?</p>
<p>The ideal scientific literature on a topic, for the purposes of self-study, is:</p>
<ul>
<li>Not so huge that you can’t read literally all the published studies that attempt to answer the question, after you’ve restricted attention to certain kinds of sufficiently good study designs</li>
<li>Not so tiny or low-quality that you come out of the self-study process knowing no more than you’d get from a couple of anecdotes or opinion pieces</li>
<li>“Simple” enough, or close enough to what you already understand, that you’re confident you can summarize, for each paper you read, what the experimenters or paper authors did, why they expected their methods to answer the question, what results they got, and what features of the study design and results make you more or less confident in the conclusion.</li>
</ul>
<p>It’s harder to self-teach enough to know what’s going on, in subjects that have heavily nested prerequisites you didn’t study in school (for me, that’s chemistry and physics). I can almost always read a biology or social-science paper, if I have my trusty Google handy and a place to take notes. I can <em>sometimes</em> read engineering or experimental-physics papers, but not always, and I can’t read chemistry or theoretical physics papers at all. There’s also an intermediate stage of “I bet I could learn the prerequisites, but it would take a while and I haven’t gotten around to it yet”, which is roughly where I am with a lot of computational genetics.</p>
<p>It’s also hard to self-teach in subjects where 3D awareness of where things are is important, so learning from text or diagrams is difficult. For instance, if you’re researching “which of these surgical techniques works best for this condition?” you may run into problems noticing when two different anatomy phrases are actually referring to the same thing, if you’re just black-boxing the anatomy and don’t have a spatial model of where anything is. (Though YouTube videos demonstrating medical, laboratory, and industrial procedures are a huge help for understanding things that are hard to visualize from text.)</p>
<p>In my experience, more time reading stuff does matter. Both at the micro and macro scales.</p>
<p>On the micro scale – I am way more able to contribute in a meeting with an expert if I’ve done at least an hour of prep first than if I haven’t. The difference is striking.</p>
<p>On the macro scale – I get way worse feedback from knowledgable people when I propose ideas about topics I’ve spent less total time self-teaching (like economics) than topics I’ve spent more total time self-teaching (like biology.) I’m more likely to be reinventing the wheel, looking at only part of the story, or just plain stuck in economics; I’m more likely to be able to come up with something actionable and novel, or at least something that’s not obviously terrible, in biology. This despite the fact that I’ve taken almost an undergrad major’s worth of economics classes, and no biology classes since high school. I think avid reading is a bigger factor than formal classes, at least in my case – possibly simply because, over an adult lifetime, “self-study” reading can add up to more hours of focused attention than formal education.</p>
<p>Basically, I think, in order to be a good “educated layman”, you have to put in the time, and focus on what’s easier to do as a non-expert.</p>
<p>What you’re missing, as an “educated layman”, is apprenticeship with a “master.” You will not know how to actually <em>do</em> lab procedures, so you will not know how they tend to fail in ways that aren’t captured in the published papers. You will not necessarily be able to replicate the results in papers if the “secret sauce” is unwritten and passed from lab tech to lab tech. You will not know the field’s gossip about who is worth listening to and who isn’t.</p>
<p>Your strength, as an “educated layman”, is the ability to drill down and learn <em>everything</em> about the one question within the field that you care about, which will often be different from what most experts in the field care about. Your lack of embeddedness in the community can actually be helpful, because by aggregating <em>everything</em> in the one slice of data you care about, you can generate ideas that aren’t correlated with the field’s biases.</p>
<p>Some of these ideas will be bunk because you’re missing part of the picture; listen to those criticisms; but some will survive skeptical examination, and that’s where you add value.</p>Doing business development for new initiatives at Nanotronics is kind of like being an “educated layman” for a living. My blog is also a pretty good example of an “educated layman”’s thinking about a variety of issues. So I plausibly know what I’m talking about here, and may have useful advice for other people looking to succeed at being “educated laymen.”Do High-Performing Investment Firms Drive Out Low Performers?2021-06-09T00:00:00+00:002021-06-09T00:00:00+00:00https://srconstantin.github.io/2021/06/09/Investment-Turnover<p>In the last post, I found evidence for the claim that a minority of investment firms seek out <em>more information</em> than others, and that firms in this “infovore” minority see above-average returns on investments.</p>
<p>In other words, the median financial investment firm is doing <em>less research</em> than is optimal, in terms of economic self-interest.</p>
<p>Is this a social problem that we should care about even if we don’t work at investment firms?</p>
<p>Does it indicate that there’s pervasive <em>malinvestment</em> into bad projects, and <em>underinvestment</em> into good projects?</p>
<p>Well, not exactly.</p>
<p>First of all, there’s the issue that “good” from my perspective as a person who lives on Planet Earth, does not necessarily line up exactly with “profitable for its investors.”</p>
<p>But I’m not too worried about that issue. If an investor is failing to do enough research to maximize his own profits, it’s very unlikely that he’s doing enough research to invest in companies with the most “positive externalities” or “public benefit.” Benefits and harms to third parties are harder to find good information about than financial returns, and investors have less incentive to seek out that information. So “investors don’t do enough research to maximize profits” probably means they <em>also</em> don’t do enough research to maximally make the world a better place.</p>
<p>The more critical issue is about turnover and competition.</p>
<p>Maybe the majority of investment firms are Terrible At Investing (to dramatize the situation a bit), but they are also small and go out of business quickly, while the few firms that are Good At Investing stick around year after year and grow large. In such a situation, most investment capital is <em>not</em> tied up in unprofitable projects; the bad investors may be more numerous but the good investors control more of the resources. (Or, the good investors are <em>trending towards</em> controlling most of the resources in the long run.)</p>
<p>This is a testable hypothesis. It makes certain predictions.</p>
<ul>
<li>High-performing investment firms survive longer than low-performing investment firms.</li>
<li>High-performing investment firms have more money under management than low-performing investment firms.</li>
<li>High-performing investment firms get more inflows (new investment dollars from clients) than low-performing investment firms.</li>
</ul>
<p><strong>Survival</strong></p>
<p>The available data confirms the hypothesis that high-performing investment firms usually survive longer than low-performing ones.</p>
<p>Most hedge funds don’t live long. The median hedge fund only lasts a few years. And survival probabilities consistently correlate with performance, as measured by market returns. Bad hedge funds, it seems, do tend to go out of business faster than good ones, and in relatively short time frames.</p>
<p>Commodity trading advisors (CTAs) also have short lifespans, with median survival of 4.42 years, and they too survive longer when their returns are higher.</p>
<p>Mutual funds live longer, with a median lifespan of about 12-17 years. In most, but not all, studies, they too have higher survival probabilities when they perform better. But malinvestment can persist longer in poorly-performing mutual funds. (In fact, mutual funds as a class usually underperform index funds without dying out, which indicates persistent malinvestment.)</p>
<p><em>Commodity Trading Funds</em></p>
<p>In a sample of 1504 commodity trading funds (CTAs) between 1990 and 2003, median survival was 4.42 years. Mean monthly return correlated positively with survival, p<0.0001. Above-median return firms survived an median of 6.16 years, while below-median return firms survived an average of 3.25 years.[1]</p>
<p>The hazard ratio associated with median return was 0.88, i.e. for each 1% additional percentage point of monthly return, there’s a reduction of 11.20% of the risk of failure.[1]</p>
<p>In a sample of 1053 CTAs, each 1% additional percentage point of annual alpha, or risk-adjusted return in the CAPM model, corresponds to a 9.6% reduced risk of firm failure.[4]</p>
<p><em>Hedge Funds</em></p>
<p>In a dataset of 3491 hedge funds located in the Asia Pacific region, a probit model for the probability of failure of a firm found a negative relationship with mean firm performance, (-0.39, p<0.01), indicating that better-performing firms survive longer. The hazard ratio for mean return is 0.52, indicating that each 1% increase in annual returns corresponds to a halving of the annual risk of firm failure.[2]</p>
<p>Assets under management also have a slight negative correlation (-0.01, p<0.01) with probability of failure, indicating that larger firms survive longer.[2]</p>
<p>In a sample of 5827 hedge funds, firm returns correlate negatively (p<0.01) with the probability of firm liquidation. Each 1% increase in average return corresponds to a 7% reduction in the rate of failure.[3]</p>
<p>In a dataset of 1091 hedge funds and commodity trading advisor funds, 1971-1998, in a probit multivariate model predicting probability of firm failure, there was a significant negative association between a firm’s CAPM alpha (or market risk-adjusted performance) and its probability of failure. A 1% increase in a hedge fund’s annual alpha corresponds to a 18.7% lower risk of failure, in a Cox proportional hazards model. [4]</p>
<p>In a database of 2776 hedge funds, 1990-2001, the median survival time was 5.5 years. In a chi-squared test, there was a significant (p<0.001) positive association between survival time and both amount under management and average monthly return. The hazard ratio associated with mean monthly return was 0.899; that is, a 1% increase in monthly return corresponds to a 10% lower risk of liquidation.[5]</p>
<p>In a dataset of 1222 hedge funds, 1985-2005, mean survival was around 4-6 years, and failure probability was negatively correlated (p<0.01) with return in the past year or in the previous year. Mean return was associated with a hazard ratio of 0.726, or each 1% increase in mean return corresponds to a 27.4% lower risk of firm failure.[6]</p>
<p>In a dataset of 6943 hedge funds over the period 1963-2005, 64% of the hedge funds survived for less than 5 years, 25% survived 10-30 years, and 11% survived more than 30 years. Median survival was 5 years. The probability of failure in a year was negatively correlated (coefficient -0.034, p<0.001) with performance. Every 1% increase in monthly performance corresponds to a 3.6% decrease in the hazard rate of firm failure.[7]</p>
<p>Larger hedge funds’ failure risk is more sensitive to performance; in firms with >$100M under management, each 1% increase in monthly performance corresponds to a 6% decrease in hazard rate. That is, small firms have a high failure rate whether they’re good or bad, but large firms are much more likely to survive if they’re good than if they’re bad.[7]</p>
<p><em>Mutual Funds</em></p>
<p>In a dataset of 2375 UK mutual funds, over the period 1972-1995, median survival was 16.7 years, and hazard rate correlated negatively (t = -3.180) with market return.[8]</p>
<p>In a dataset of 1057 Spanish mutual funds, over the period 2006-2016, median survival is 17 years. Survival does <em>not</em> correlate with returns in the past year or three years.[9]</p>
<p>In a dataset of mutual funds, 1980-2000, median survival was 12 years. Survival was significantly associated with fund performance; a 1% increase in Sharpe ratio was associated with a 2% reduction of risk of fund liquidation.[10]</p>
<p><strong>Size</strong></p>
<p>It appears that better-performing funds cannot generally grow their amount under management to “take over” the market. The most inclusive datasets show that as funds grow, their returns worsen.</p>
<p>In a sample of 924 hedge funds listed in a commercial dataset between 1994 and 1996, average returns were positively correlated (coeff = 0.090) with the amount of assets under management.[11]</p>
<p>In a sample of 4327 hedge funds in a commercial dataset from 1994-2003, there is a weak positive correlation between asset sizes and returns. In a linear regression, the correlation coefficient of log assets on mean annualized returns was 0.0036 (p = 0.0048). There is a much stronger negative correlation between firm size and variance in returns, and correspondingly a positive correlation between firm size and Sharpe ratio (which is mean excess return divided by standard deviation of return).[12]</p>
<p>The largest hedge funds are not listed at all in the commercially available hedge fund databases. When unlisted hedge funds are included, firm size correlates <em>negatively</em> with firm returns (coefficient = -0.03, t-value = -2.17)[13]</p>
<p>In a sample of 7417 hedge funds from commercial datasets, 1994-2008, the two smallest size quintiles have significantly higher average abnormal returns than the two largest size quintiles, and there is a negative correlation (-0.25) between average risk-adjusted returns and amount under management.[14]</p>
<p><strong>Inflows</strong></p>
<p>New inflows of investment (in institutional or individual investors) do correlate positively with fund performance, indicating that investors reward good performance and punish bad performance. However, this incentive tends to be focused on the low end of performance (investors punish the lowest performing funds, but don’t reward the highest performing funds) and focused on short-term results.</p>
<p>Hedge fund performance and inflows correlate positively. The top quintile of hedge funds by performance, measured by excess returns, gets 0.2% more investment a year by wealthy individuals, and 0.15% more investment a year by institutional investors; by contrast, the bottom-performing quintile of hedge funds <em>loses</em> 0.05% per year from institutional investors and loses 0.17% per year from wealthy individuals.[15]</p>
<p>Growth in amount under management correlates positively (0.32) with firm returns, out of a sample of 5827 hedge funds.[3]</p>
<p>In a dataset of 1392 hedge funds, 1979-2000, cash inflows correlate well with returns in the previous quarter. A 1% increase in returns in the most recent quarter corresponds to an 0.25% expected increase in cash inflows.[12]</p>
<p>Hedge funds are required to file Form D with the SEC, disclosing their number of new investors and size of offering. Using this dataset, there were 22,800 hedge funds that filed Form D between 2009 and 2014, only 17% of which were listed in the commercial databases used in other studies of hedge funds. Net flows greatly differ based on prior quarter performance: the bottom quintile performers in the previous quarter had net cashflow of -10.2%, while the top quintile performers had net cashflow of 27.2%. Inflows correlate strongly (p<0.01) positively with high returns and anticorrelate with the standard deviation of returns. Outflows are positively correlated (p <0.05) with low returns. Fund death is significantly (p<0.01) negatively correlated with fund returns.[16]</p>
<p>If you look at the above-median cashflow funds as an “investment portfolio” (the funds that investors increased their holdings in) and the below-median cashflow funds as the “divestment portfolio” (the funds that investors decreased their holdings in, the difference between these portfolios (either equal-weighted or cash-flow weighted) actually <em>underperforms</em> the market,by at least 1% per quarter in subsequent quarters. In other words, investors reward short-term good performance and punish short-term bad performance, but this isn’t generally predictive of long-term results. Good short-run performance is <em>not</em> predictive of good long-run performance, so the cash-flow weighted “investment portfolio” underperforms an equal-weighted strategy. By contrast, bad short-run performance <em>is</em> predictive of bad long-run performance, so the cash-flow weighted “divestment portfolio” outperforms an equal-weighted strategy.[17]</p>
<p>86% of all negative cash flows are from investors divesting from the bottom-decile performing hedge funds, which also have very high (>22%) rates of liquidation within two years. Investors are good at driving out the very worst hedge funds, but not at picking persistent winners. Investors tend to invest the most in the largest funds, which have medium returns, and neglect the smaller funds that comprise the top and bottom performers. There is persistence in winners, but investors aren’t exploiting it; a portfolio that just invested in last quarter’s above-median hedge funds would have outperformed the actual cash flow allocations of investors.[17]</p>
<p>Similarly, in corporate bond mutual funds, their outflows are more sensitive to bad performance than their inflows are to good performance.[18]</p>
<p><strong>Conclusions</strong></p>
<p>It seems that of our three hypotheses, one is true, one is false, and one is mixed.</p>
<ul>
<li>Do high-performing investment firms survive longer than low-performing investment firms?
<ul>
<li>Yes, they do.</li>
</ul>
</li>
<li>Do high-performing investment firms have more money under management than low-performing investment firms?
<ul>
<li>No; the correlation between size and performance may even be negative.</li>
</ul>
</li>
<li>Do high-performing investment firms get more inflows (new investment dollars from clients) than low-performing investment firms?
<ul>
<li>Yes, but this is generally an asymmetric relationship; investors “punish” especially low-performing firms but don’t “reward” especially high-performing firms.</li>
</ul>
</li>
</ul>
<p>In a world where a minority of exceptionally good investors and investment firms perform <em>much</em> better than the mediocre majority, do we see the exceptionally good investors “driving out” the mediocre ones?</p>
<p>The picture is mixed, but it seems that no, on the whole, we do not. The below-average firms do die sooner than average, but the best firms don’t necessarily grow to “take over.” And new firms, mostly mediocre, will enter the market to fill the gap when the worst of the last batch have gone out of business. “Bad investors”, in the long term, remain a substantial percent of the market, even if they have higher turnover than “good investors.”</p>
<p>So yes, we can conclude that a substantial fraction of investment dollars are being allocated by “bad investors.”</p>
<p>One model of why “good investors” don’t drive out “bad investors” is that there are diminishing returns to scale.</p>
<p>A small firm may show great investment returns because it knows about a handful of good investment opportunities; if you give that firm more money to manage, it doesn’t necessarily know more good things to do with the money, so its returns will drop. To the extent institutional investors know this, they will be reluctant to reward especially-high-performing firms with more inflows. This would explain the picture we see.</p>
<p>On this model, “allocate more resources to the smartest existing investors” isn’t going to reduce the amount of malinvestment in the system as a whole, nor will it even necessarily be profitable.</p>
<p>That’s the bad news. The good news is that the model predicts that there’s “room” for many more small, smart investors to enter the market, and that they’ll be more likely than average to stick around, even if they have trouble growing very big.</p>
<p>This <em>would</em> decrease the total amount of malinvestment, albeit slowly, because new, small, smart investors would compete with the exceptionally bad investors (who tend to fail early).</p>
<p><strong>References</strong></p>
<p>[1]Gregoriou, Greg N., et al. “Survival of commodity trading advisors: 1990–2003.” <em>Journal of Futures Markets: Futures, Options, and Other Derivative Products</em> 25.8 (2005): 795-816.</p>
<p>[2]Chen, Jianguo, Martin Young, and Mui Kuen Yuen. “HEDGE FUND FACTORS AND SURVIVAL ANALYSIS: EVIDENCE FROM ASIA PACIFIC.”</p>
<p>[3]Gupta, Jairaj, Adrien Becam, and Andros Gregoriou. “Does Size Matter in Predicting Hedge Funds’ Liquidation?.” <em>European Financial Management (Forthcoming)</em> (2017).</p>
<p>[4]Goetzmann, William N., Stephen J. Brown, and James M. Park. “Conditions for survival: Changing risk and the performance of hedge fund managers and CTAs.” <em>Yale School of Management Working Paper No. F-59</em> (1997).</p>
<p>[5]Gregoriou, Greg N. “Hedge fund survival lifetimes.” <em>Journal of Asset Management</em> 3.3 (2002): 237-252.</p>
<p>[6]Baba, Naohiko, and Hiromichi Goko. “Survival analysis of hedge funds.” <em>Institute for Monetary and Economic Studies and Financial Markets Department</em> 6 (2006).</p>
<p>[7]Nhogue Wabo, Blanche Nadege. <em>Hedge funds and Survival analysis</em>. Diss. Université d’Ottawa/University of Ottawa, 2013.</p>
<p>[8]Lunde, Asger, Allan Timmermann, and David Blake. “The hazards of mutual fund underperformance: A Cox regression analysis.” <em>Journal of Empirical Finance</em> 6.2 (1999): 121-152.</p>
<p>[9]Barberà-Mariné, M. Glòria, Laura Fabregat-Aibar, and Antonio Terceño. “Investment objectives and factors that influence the disappearance of Spanish mutual funds.” <em>Journal of Business Economics and Management</em> 21.1 (2020): 255-276</p>
<p>[10]Keenan, Alexander J. <em>The CAPM and the duration of poorly performing mutual funds</em>. No. 2001-04. Working Paper, 2001..</p>
<p>[11]Liang, Bing. “On the performance of hedge funds.” <em>Financial Analysts Journal</em> 55.4 (1999): 72-85.</p>
<p>[12]Ammann, Manuel, and Patrick Moerth. “Impact of fund size on hedge fund performance.” <em>Journal of Asset Management</em> 6.3 (2005): 219-238.</p>
<p>[13]Barth, Daniel, et al. “The hedge fund industry is bigger (and has performed better) than you think.” <em>OFR WP</em> (2020): 20-01.</p>
<p>[14]Teo, Melvyn. “Does size matter in the hedge fund industry?.” <em>Available at SSRN 1331754</em> (2009).</p>
<p>[15]Sinclair, Andrew, and Chuyi Zhang. “Do Wealthy Investors Benefit from Access to Hedge Funds?.” <em>Available at SSRN 3779042</em> (2021).</p>
<p>[16]Jorion, Philippe, and Christopher Schwarz. <em>Who are the smartest investors in the room? Evidence from US hedge funds solicitation</em>. Working paper, University of California at Irvine, 2015.</p>
<p>[17]Baquero, Guillermo, and Marno Verbeek. “A portrait of hedge fund investors: Flows, performance and smart money.” ERIM Report Series Reference No. ERS-2005-068-F&A (2005).</p>
<p>[18]Goldstein, Itay, Hao Jiang, and David T. Ng. “Investor flows and fragility in corporate bond funds.” <em>Journal of Financial Economics</em> 126.3 (2017): 592-613.</p>In the last post, I found evidence for the claim that a minority of investment firms seek out more information than others, and that firms in this “infovore” minority see above-average returns on investments.Does It Pay To Do More Research?2021-03-08T00:00:00+00:002021-03-08T00:00:00+00:00https://srconstantin.github.io/2021/03/08/does-it-pay-to-do-more-research<p><strong>The Hypothesis</strong></p>
<p>Do investors profit from spending more time and effort researching and analyzing their decisions? Does it pay to be an “infovore” who seeks out an unusual amount of information?</p>
<p>It’s pretty obvious, and well-confirmed by the literature, that the <em>least</em> info-seeking investors do poorly. In stock markets, for instance, individual investors (e.g. day traders) get worse returns than institutional investors. Institutional investors have full-time professionals on staff and access to expensive information sources; individual investors typically know far less.</p>
<p>The interesting question is whether being unusually info-seeking correlates with having <em>higher</em> than median returns, not whether being unusually ignorant correlates with having lower than median returns. Do the most information-seeking investors earn the highest returns?</p>
<p><strong>Motivation</strong></p>
<p>This Venkat Rao <a href="https://twitter.com/vgr/status/1277262959828283392">thread </a>claims that a major problem with society is that too many “rich people” are “lazy” when they make resource allocation decisions.</p>
<blockquote>
<p>The word “invest” has 2 distinct meanings in relation to capital:
Invest (1): Spend money to build a capability. Example: a bridge, a factory, a mansion.</p>
<p>Invest (2): Spend money to acquire a formal stake in an existing capability. Example: stock, bond, lien.</p>
<p>2 now dominates 1.</p>
<p>The two are coupled. For example, you invest (2) in my company so I can invest (1) in a new factory. Instead of shareholder value or a dividend, you might claim a share of the output at a good price for example (offtakes, kinda like futures).</p>
<p>…</p>
<p>It’s a moral hazard to purely invest (2) in money-in-money-out (MIMO) ways. You have no interest in how black box works. All knowledge risk lies with investee. If your MIMO deal is not honored you can’t tell fraud apart from real problems. You can’t judge whether to grant relief.</p>
<p>This is the definition of dumb money. Of course most real investment (2) does informally include some appreciation of the underlying investment (1), but not in any way that is operationally specific. Few investors who play for even controlling stakes actually desire control.</p>
<p>Control in finance has come to mean “control of the board and ability to hire/fire top executives”, which is increasingly just too shallow to address the complexity of modern principal-agent relations. Money _wants _to be stupid because the rich don’t want to do invest (1) work.</p>
<p>Financialization, “shareholder value” as a disease, etc, all have their tools in a single psychological problem: the rich are really lazy. They don’t want to put in the work to make their money smart. They want to either swarm opportunities via imitation, or rely on “analysts.”</p>
<p>There is a lot of bullshit conservative sermonizing about how the poor deserve their fates because they don’t work hard and that’s why the economy suffers etc. This is not only not the problem, it’s not even true. Most economic problems arise from the rich not working hard enough.</p>
<p>If you have 10s of millions of dollars, it <em>matters</em> how hard you, PERSONALLY, think about where to put it. Even a single degree of delegation causes huge principal-agent distortions. To the extent that some wealth creation opportunities need concentrated capital, the rich must think.</p>
<p>Some rich do think and work hard but they think wide and shallow for “highest ROIC” (where the I is investment (2), not investment (1)) opportunities. They rarely think deep about how a particular investment (2) will drive the invest (1). They don’t care about the meaning of the money.</p>
<p>There is something deeply nihilistic, stupid, fearful, and acting-dead about this. If the only difference between 2 investments for you is return rates, and you are not curious about the futures implied by investing in either, you’re kinda dumb and boring.</p>
<p>…</p>
<p>This whole point is why I’m not a socialist. I don’t think it matters much who “owns” the capital. Whether it is a workers’ co-op or a fat-cat single rich person, the question is how hard they think.</p>
</blockquote>
<p>There’s a lot in this thread, a lot of it resonates with me, and I think it’s worth taking seriously enough to actually unpack the claims and investigate whether they’re literally <em>true.</em></p>
<p>As I see it, Venkat is making two separate claims.</p>
<p>One is about the relationship between “investment (1)” and “investment (2)”, between constructing physical objects that produce value, and the abstracted process of spending money to turn it into more money.</p>
<p>He seems to believe, and I share the same intuition, that the world would be a better place if more people who had the means to invest in big projects did so because they wanted those projects to exist, not just because they wanted the revenue stream.</p>
<p>Elon Musk <em>wants to go to Mars</em>; he’s also trying to structure his companies to be profitable, but I’m pretty sure he would count it a failure if he made a bunch of money but humanity never became a multiplanetary species. That’s the kind of thing Venkat is talking about.</p>
<p>It’s natural, for kids at least, or for people imagining what they’d do with wealth vastly greater than their own, to think “If I ever have money, I’ll use it to do something <em>awesome</em>.” You could make the world a better place, make your mark on history, or even just have a spectacularly good time.</p>
<p>Venkat seems to be claiming that a.) the people who actually <em>have</em> that much money rarely want to spend it on things they personally find awesome, and b.) it would be better for the world if they did.</p>
<p>I share this intuition, but I don’t really know how I’d go about testing it. Since there’s almost no public data about the psychology of rich investors, we have to rely on anecdote; and while a consultant like Venkat has met many rich investors, he’s seen a very selective picture of how they think and spend their time. My own experience with rich investors is even more limited.</p>
<p>As for how the world would be different if investors put money into projects that they valued for reasons other than revenue, I’m not sure how to seriously answer the question without an incredibly broad theory of economics and ethics.</p>
<p>But Venkat is also making a narrower, more tractable claim: “the rich are really lazy.” That is, investors do not “think hard” about where to put their money. In more neutral terms, investors underinvest in information-gathering and analysis.</p>
<p>This is a testable hypothesis, at least if you only think about the financial self-interest of investors. If the investors who are <em>most</em> inclined to investigate/research/seek information are also earning the highest returns, then most investors are irrationally <em>neglecting</em> research by comparison.</p>
<p>If investors tend to “underthink” relative to what would be economically rational, then they are <em>certainly</em> underthinking relative to Venkat’s socially beneficial ideal, which includes not only considering the effect of an investment on your bank account, but also its effect on the rest of the world.</p>
<p><strong>Conclusions From The Literature</strong></p>
<p>Most of the evidence I could find comes from investments on public markets, since of course there’s far more data on the stock performance of publicly traded companies. I am less confident about what this means about private equity or venture capital investment.</p>
<p>Overall, engaging in more research into company fundamentals, and being in some sense “better at formal analysis”, <em>does</em> correlate reliably with higher returns.</p>
<ul>
<li>Hedge funds that make more in-person site visits to portfolio companies have higher returns. Site-visitors have annual returns 6.1 percentage points higher than non-visitors.</li>
<li>Investment firms that download more SEC filings have higher returns. Downloaders (of any files) have annual returns 1.5 percentage points higher than non-downloaders.</li>
<li>Financial analysts who download SEC filings make more accurate forecasts than non-downloaders, and the longer they spend reading SEC filings, the more accurate their forecasts.</li>
<li>“Buy-side analysis” refers to the research and forecasting performed in-house by employees of investment firms. Mutual funds whose investment decisions more closely track the recommendations of their analysts have higher returns.</li>
<li>Mutual fund managers who score higher on the Cognitive Reflection Test (a measure of how good people are at avoiding intuitive-but-wrong answers; strongly correlated with IQ) have funds with higher Sharpe ratios (the same returns, but less risk) than their low-scoring peers. That is, roughly, being less prone to “jump to conclusions” is associated with better investment performance.</li>
<li>Angel investors who do more due diligence have a significantly higher proportion of their investments become “home runs”, defined as investments where the investor receives returns of at least 100% upon exit of the company.</li>
</ul>
<p>Strikingly, the biggest downloader of public financial documents is Renaissance Technologies, whose <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3504766">66% annual returns over the past 30 years</a> dwarf anything else in the financial markets.</p>
<p>It seems to be the case that spending more time and effort on fact-finding that relates to fundamentals (reading financial documents, visiting factory sites, engaging in due diligence) and listening more closely to the employees who specialize in such research, is profitable – and thus that most firms underinvest in it.</p>
<p>By contrast, “imitative information-seeking”, all things equal, seems to anticorrelate with investment returns and forecasting accuracy.</p>
<ul>
<li>Investment analysts who change their forecasts the most in response to changes in other analysts’ published forecasts have worse performance.</li>
<li>Investment firms tend to perform worse if their portfolios closely track changes in published financial analyst recommendations.</li>
<li>Investment firms that tend to buy stocks that have been in the news recently, have worse performance than investment firms that are less correlated with the news cycle.</li>
</ul>
<p>Basically, the evidence available to me suggests that Venkat is right. Institutional investors <em>do</em> perform better when they do more investigation into company fundamentals, and worse when they focus more on how other people perceive a company. The median institutional investor would make more money if they were more investigative and less imitative.</p>
<p><strong>Information Seeking by Investment Analysts</strong></p>
<p>Investment analysts who download more publicly available data about firms tend to make more accurate price forecasts. Financial analysts whose recommendations correlate closely with the average of other financial analysts’ recommendations tend to perform worse than the contrarians. This suggests that analysts who are good at research and do more of it make better predictions.</p>
<p>Strangely, financial analysis firm <em>rankings</em> were found to anticorrelate with the use of internal library resources at the firm (in a study published in 1997, when written information resources were mostly in hard copy.)</p>
<p>Financial analysts who download more publicly available data about firms from EDGAR, the SEC database, perform better. Only 24% of analysts made an EDGAR download within a day before issuing a new recommendation update. Those that did, had a 3.7% reduction in forecast error. Spending more time reading reports also corresponds to better accuracy – each 1% increase in time spent reading files corresponded to an 0.8% increase in forecast accuracy.[1]</p>
<p>However, analysts that base their recommendations more on public consensus tend to perform worse. A measure of Reliance on Public Information (RPI) can be calculated for financial analysts based on the sensitivity of their recommendations to public variables like price momentum, earnings surprise, average turnover, change in consensus recommendation, and change in consensus earnings forecast. A portfolio that follows stock recommendations of analysts in quintile 1 of RPI (the least reliant on public information) produces an average monthly return of 1.83%, or 22% a year. Data was collected on 3480 analysts over the period 1993-2006; returns were calculated over the 31 days following a new recommendation. Low-RPI analysts tend to recommend buying larger firms (factor loading -0.19, p<0.05), while high-RPI analysts tend to recommend shorting larger firms (factor loading (-0.21, p<0.05), and more high-priced firms (-0.29, p<0.05).[2]</p>
<p>A 1997 survey of 100 securities analysts from the largest UK and US investment firms found that firm ranking <em>negatively</em> correlated (p<0.001) with the frequency that respondents answered that their staff checks the internal library.[3]</p>
<p><strong>Information Seeking by Investment Funds and Fund Performance</strong></p>
<p><em>Use of Public Information</em></p>
<p>Firms that download more publicly available files about their investments generally perform better than firms that do not. Also, “short sellers” who make leveraged bets against firms earn more profit when they trade immediately after public news about a firm, suggesting that they are profiting from making better use of publicly available information than most investors.</p>
<p>On the other hand, firms whose investment choices are more closely correlated with the public advice of analysts generally perform worse.</p>
<p>Hedge funds that access more SEC filings online perform better. The most frequent downloader of all is Renaissance Technologies. Firms that download files have on average 1.5% higher annualized returns than firms that don’t.[4]</p>
<p>Users who download files from EDGAR, the official website where SEC filings are stored, can be traced to IP addresses corresponding either to institutional investors (e.g. Goldman Sachs, Morgan Stanley) or to individual “retail” investors. There is no correlation between a firm’s future stock performance and how much its filings were downloaded by “retail” investors, but there is a positive correlation (p<0.01) between a firm’s future performance and how much its files were downloaded by institutional investors, and also a positive correlation (p<0.01) between a firm’s institutional-investor downloads and its subsequent change in holdings among those investors, particularly when the 10K filings have a positive overall “tone”, suggesting that institutional investors do in fact invest more in firms when the firms’ publicly available data is favorable.[4]</p>
<p>Short selling does not increase immediately before news about a stock is published, but does increase after, suggesting that short sellers are making their decisions on the basis of public news rather than anticipating that news. Moreover, the returns on short sales are more than twice as high on days when there is news about a stock, which also suggests that short sellers are making better use of public information than other investors.[5]</p>
<p>Short-selling in the COVID-19 pandemic was more profitable for investors who had previously held a short position in any healthcare stock before, suggesting that investors with more familiarity with healthcare were more able to understand what was going on with COVID-19 and how it would affect stock prices.[6]</p>
<p>Reliance on Public Information (RPI) is a measure of how sensitive an investor’s holdings are to changes in public information, in this case changes in analysts’ recommendations. RPI is negatively correlated (r = -0.17) with Carhart 4-factor alpha, in a sample of 1696 mutual funds.[7] Better funds use more private as opposed to public information.</p>
<p>Also, if you construct a measure “RPI_σ” to represent the coefficients from regressing the change in a mutual fund’s % holdings on the change in the standard deviation of analysts’ recommendations, and compare the RPI_σ of 1220 mutual funds to their fund performance, the correlation is significantly negative (p<0.05). [8]</p>
<p>A measure (PTMC, Propensity to Trade with Media Coverage) of a mutual fund’s tendency to trade stocks more when they’re in the news, negatively correlates with fund performance. Over the period 1993-2002, stocks purchased by top-quintile PTMC funds lost 0.17% monthly in CAPM-adjusted alpha, while stocks purchased by bottom-quintile PTMC funds gained 0.46% monthly. The difference is still significant for Fama-French three-factor adjusted alpha and Carhart 4-factor adjusted alpha.[9]</p>
<p><em>Use of Private Information</em></p>
<p>Private research by an investment firm – site visits to portfolio companies, interviews with portfolio CEOs, and in-house analysts estimating stock values – _does _correspond to higher returns. Investment firms that engage in more in-house research activities, or weight in-house research more heavily in investment decisions, tend to perform better.</p>
<p>About ⅙ of hedge funds make site visits to the companies they invest in. Among 2469 Chinese hedge funds over the period 2012-2017, and CSMAR data on corporate site visits in China, 15.43% of hedge fund managers visited at least one company site. Funds that made site visits had significantly (p<0.01) higher returns, CAPM alpha, Sharpe ratio, and volatility than funds that didn’t. Mean annual returns were 21.4% for funds that did site visits, vs. 15.3% for funds that did not.[10]</p>
<p>Female fund managers and managers with a graduate degree are more likely to make site visits. 11% of male managers made site visits, while 33% of female managers did. 12% of managers with graduate degrees made site visits, vs. 9% of managers without graduate degrees.[10]</p>
<p>Chinese mutual funds between 2006-2016 were more likely to make trades on stocks if they had recently made a site visit, indicating that site visits did indeed provide them with decision-relevant information. A portfolio of stocks that were bought by a mutual fund after a site visit had above-market returns after adjusting for Fama-French factors, indicating that mutual funds are successfully using site visits to identify good investments.[11]</p>
<p>Fund managers who report (in a questionnaire) rating conversations with company executives as “very important” to their investment decisions perform significantly better (p <0.05) than fund managers who rate conversations with executives as “not important.”[12]</p>
<p>The added value of buy-side research – that is, the work of investment analysts doing proprietary research for investment firms – can be evaluated by measuring the “buy-side alpha” logged in a private database for an investment firm. All investment analysts at this firm use the same baseline algorithm for valuing stocks; then, their individual research prices some stocks higher or lower than the algorithm would predict. This difference is called the “buy-side alpha.” In the month following portfolio formation, it turns out, the “buy-side alpha” does correlate with actual stock performance.</p>
<p>Stocks with top-quintile buy-side alphas are rated significantly <em>lower</em> by sell-side analysts than stocks with bottom-quintile buy-side alphas (p<0.01), and have higher book-to-market ratios (p <0.01). A portfolio based on buying stocks each month that had seen upgrades in buy-side alpha would earn 1.19% monthly, or an expected 15% per year, while a portfolio based on buying stocks whose buy-side alphas had been downgraded would earn 0.61% monthly, or an expected 7.6% yearly. This is a significant difference, and continues to be significant after adjusting for risk, while the advantage of buying stocks recommended by sell-side analysts is no longer significant after risk adjustment.[13]</p>
<p>Moreover, the mutual funds included in this database did buy stocks more when their buy-side analysts rated them higher, and sell stocks more when their buy-side analysts rated them lower. The regression coefficient of firm investment on buy-side analyst ratings is significantly positive, p<0.01, even when controlling for sell-side analysts’ ratings.[13]</p>
<p>Finally, the risk-adjusted quarterly returns of mutual funds correlate positively (p<0.01) with the sensitivity of their investment decisions to buy-side analyst recommendations, but returns do _not _correlate with the sensitivity to sell-side analyst recommendations. In other words, it pays to rely on (private) buy-side research, but not to rely on (public) sell-side analysis.[13]</p>
<p><strong>Fund Manager Cognitive Characteristics and Fund Performance</strong></p>
<p>84 fund managers from 267 mutual funds were given a battery of online cognitive tests, and their test results were compared to their publicly available fund performance. The abnormal returns of funds (over their benchmark) did <em>not</em> correlate with fund managers’ performance on the Cognitive Reflection Test, their score on a Theory of Mind test, or their self-reported competitiveness. Ambiguity tolerance was positively (p<0.005) associated with abnormal returns.[14]</p>
<p>Unsurprisingly, higher risk tolerance among fund managers in an experimental setting correlated positively with higher volatility in their funds (p<0.005), while a perfect score of 5 on the Cognitive Reflection Test (which 30% of the fund managers got) was negatively correlated with volatility (p<0.05).[14]</p>
<p>Together, these two facts imply that risk-adjusted performance (i.e. Sharpe ratio) is higher for fund managers who get perfect scores on the CRT.</p>
<p>Performance on the CRT by fund managers also has a strong positive correlation (0.51, p<0.005) with performance on the Advanced Progressive Matrices test, a measure of fluid intelligence. [14]</p>
<p><strong>Information Seeking by Venture Capital and Investment Performance</strong></p>
<p>In a survey of 128 angel investors investing in 1038 new ventures, firms that exited were classified as losing money (Failures), producing an internal rate of return of 0-99%, and exiting at 100% gains or greater (Home Runs). ⅔ of investments were failures, and 20% were home runs. The number of home run exits of an investor correlated positively (0.24, p<0.05) with the investor’s propensity to engage in due diligence.[15]</p>
<p><strong>Limitations and Conclusions</strong></p>
<p>The data we have about the benefits of site visits comes entirely from the Chinese markets, which may not be representative of other investment markets. For instance, checking on a factory to make sure its production is as good as it reports may be more important in a lower-trust environment.</p>
<p>We also are short of data on investment performance in private equity in general, and particularly in the individual characteristics and decision processes of private equity investors that are predictive of fund performance.</p>
<p>Despite these limitations, we do seem to see consistent results pointing towards positive correlations between higher information-seeking activities by investors and higher investment returns, across investment categories.</p>
<p><strong>References</strong></p>
<p>[1]Gibbons, Brian, Peter Iliev, and Jonathan Kalodimos. “Analyst information acquisition via EDGAR.” <em>Management Science</em> (2020).</p>
<p>[2]Ali, Usman, et al. <em>Analysts’ use of public information and the profitability of their recommendation revisions</em>. Working Paper, Yale University, 2008.</p>
<p>[3]Baldwin, Nancy Sadler, and Ronald E. Rice. “Information‐seeking behavior of securities analysts: Individual and institutional influences, information sources and channels, and outcomes.” <em>Journal of the American Society for Information Science</em> 48.8 (1997): 674-693.</p>
<p>[4]Crane, Alan, Kevin Crotty, and Tarik Umar. “Do hedge funds profit from public information.” <em>Rice University</em> (2018).</p>
<p>[5]Engelberg, Joseph E., Adam V. Reed, and Matthew C. Ringgenberg. “How are shorts informed?: Short sellers, news, and information processing.” <em>Journal of Financial Economics</em> 105.2 (2012): 260-278.</p>
<p>[6]Schattmann, Levy, Jan-Oliver Strych, and P. Joakim Westerholm. “Information Processing Skills of Short Sellers: Empirical Evidence from the COVID-19 Pandemic.” <em>Available at SSRN 3763198</em> (2021).</p>
<p>[7]Kacperczyk, Marcin, and Amit Seru. “Fund manager use of public information: New evidence on managerial skills.” <em>The Journal of Finance</em> 62.2 (2007): 485-528.</p>
<p>[8]Abdesaken, Gerald. “On the precision of public information and mutual fund performance.” <em>Journal of Asset Management</em> 16.2 (2015): 85-100.</p>
<p>[9]Fang, Lily H., Joel Peress, and Lu Zheng. “Does your fund manager trade on the news? media coverage, mutual fund trading and performance.” Media Coverage, Mutual Fund Trading and Performance (March 18, 2009)</p>
<p>[10]Drake, Michael S., et al. “Is there information content in information acquisition?.” <em>The Accounting Review</em> 95.2 (2020): 113-139.</p>
<p>[11]Chen, Honghui, et al. “The Geography of Information Acquisition.” <em>Available at SSRN 3371978</em> (2019).</p>
<p>[12]Drachter, Kerstin, Alexander Kempf, and Michael Wagner. “Decision processes in German mutual fund companies: evidence from a telephone survey.” <em>International Journal of Managerial Finance</em> (2007).</p>
<p>[13]Rebello, Michael, and Kelsey Wei. “A glimpse behind a closed door: The investment value of buy-side research and its effect on fund trades and performance.” (2011).</p>
<p>[14] Farago, Adam, et al. <em>Cognitive skills and economic preferences in the fund industry</em>. No. 2019-16. Working Papers in Economics and Statistics, 2019.</p>
<p>[15] Wiltbank, Robert. “Investment practices and outcomes of informal venture investors.” <em>Venture Capital</em> 7.4 (2005): 343-357.</p>The HypothesisMammalian Aggression2021-01-17T00:00:00+00:002021-01-17T00:00:00+00:00https://srconstantin.github.io/2021/01/17/Mammalian-Aggression<p><strong>Introduction</strong></p>
<p>In trying to understand how aggression works, as well as aggressive emotions like anger, I decided to go to the animal literature. Human psychology research is all too prone to being determined by researchers’ preconceptions, and we all have a lot of firsthand experience and personal agendas when it comes to theorizing about human behavior. It’s easier to get some distance when thinking about animals; we have less stake in any particular theory of how animal emotions work. It’s also easier to set up experimental conditions with animals that would be hard to do ethically with humans, like keeping them in confinement and exposing them to stressors.</p>
<p>What the mammal literature says about aggression is that it splits neatly into discrete types. Researchers disagree on exactly how many clusters there are, since there are inevitable judgment calls in defining taxonomies. And the pattern is somewhat different depending on species. But one very consistent finding is that there <em>are</em> qualitatively different types of aggression. They are governed by different hormones, activated in different situations, and seem to involve different subjective experiences.</p>
<table>
<tr>
<td>
</td>
<td><strong>Defensive</strong>
</td>
<td><strong>Social</strong>
</td>
<td><strong>Maternal</strong>
</td>
<td><strong>Predatory</strong>
</td>
</tr>
<tr>
<td><strong>Target</strong>
</td>
<td>Conspecifics, other species, inanimate objects
</td>
<td>Conspecifics only
</td>
<td>Conspecifics and other species
</td>
<td>Other species only
</td>
</tr>
<tr>
<td><strong>Situation</strong>
</td>
<td>Acute pain, imminent danger without possibility of escape
</td>
<td>Competition (over e.g. food, territory, mates)
</td>
<td>Threats to nursing young
</td>
<td>Hunting edible prey
</td>
</tr>
<tr>
<td><strong>Attack lethality</strong>
</td>
<td>Low
</td>
<td>Varies
</td>
<td>High
</td>
<td>High
</td>
</tr>
<tr>
<td><strong>Arousal</strong>
</td>
<td>High
</td>
<td>High
</td>
<td>Low
</td>
<td>Low
</td>
</tr>
<tr>
<td><strong>Affect</strong>
</td>
<td>Distressed, angry, fearful
</td>
<td>alert
</td>
<td>fearless
</td>
<td>Calm, alert, happy, curious, fearless
</td>
</tr>
<tr>
<td><strong>Piloerection</strong>
</td>
<td>Depends on species
</td>
<td>Yes
</td>
<td>Yes
</td>
<td>No
</td>
</tr>
<tr>
<td><strong>Vocalizing and threats</strong>
</td>
<td>Yes
</td>
<td>Yes
</td>
<td>No
</td>
<td>No
</td>
</tr>
<tr>
<td><strong>Association with sex hormones</strong>
</td>
<td>?
</td>
<td>Yes (increased by testosterone; blocked by ovarian hormones)
</td>
<td>Yes (increased by progesterone, testosterone)
</td>
<td>Depends on species
</td>
</tr>
<tr>
<td><strong>Cortisol levels during attack</strong>
</td>
<td>High
</td>
<td>High
</td>
<td>Low
</td>
<td>Low
</td>
</tr>
<tr>
<td><strong>Other positively associated hormones</strong>
</td>
<td>cholecystokinin, dopamine, histamine, substance P
</td>
<td>ACTH, CRH, histamine, norepinephrine, substance P, vasopressin
</td>
<td>NO, vasopressin, oxytocin
</td>
<td>acetylcholine
</td>
</tr>
<tr>
<td><strong>Other negatively associated hormones</strong>
</td>
<td>norepinephrine
</td>
<td>serotonin
</td>
<td>CRH, neuropeptide Y, neurotensin
</td>
<td>serotonin
</td>
</tr>
<tr>
<td><strong>Brain region promoting the behavior </strong>
</td>
<td>amygdala, hippocampus, PAG
</td>
<td>Amygdala, lateral hypothalamus, lateral septum, olfactory bulb
</td>
<td>dorsal raphe, lateral septum
</td>
<td>amygdala, lateral hypothalamus, olfactory bulb
</td>
</tr>
<tr>
<td><strong>Brain region inhibiting the behavior</strong>
</td>
<td>lateral septum, medial hypothalamus
</td>
<td>?
</td>
<td>PAG
</td>
<td>PAG
</td>
</tr>
<tr>
<td><strong>Drugs that increase the behavior</strong>
</td>
<td>amitriptyline, delta-9-THC, desmethylimipramine, ethanol, imipramine, iproniazid, naloxone, nialamide, pargyline
</td>
<td>amphetamine, anabolic steroids, chlordiazepoxide, cyproheptadine, ethanol, fenfluramine, PCPA
</td>
<td>alprazolam, chlordiazepoxide, diazepam, fluoxetine, oxazepam
</td>
<td>arecoline
</td>
</tr>
<tr>
<td><strong>Drugs that decrease the behavior</strong>
</td>
<td>lithium, opioids, PCP
</td>
<td>5-HT, cannabis, citalopram, fluoxetine, fluprazine, naloxone, quipazine, tryptophan
</td>
<td>5-HT, amitriptyline, amfonelic acid, desipramine, fluprazine, GnRH antagonists, imipramine, morphine, NOS inhibitors, PCPA
</td>
<td>5-HT, amphetamine, atropine, delta-9-cannabidiol, ethanol, scopolamine
</td>
</tr>
<tr>
<td><strong>Effect of domestication</strong>
</td>
<td>reduces
</td>
<td>no change
</td>
<td>no change
</td>
<td>no change
</td>
</tr>
</table>
<p><strong>“Defensive Aggression”/”Defensive Rage” – Cortisol, Substance P</strong></p>
<p>A certain cluster of behaviors in mammals can be called “defensive aggression”, “affective defense,” or “defensive rage”. These behaviors are reactions to pain or immediate threat, whether that threat comes from a member of the same species, a member of a different species, or an inanimate object.</p>
<p>Defensive aggression is associated with negative emotions like fear and anger. It is aversive; a rat will learn not to push a lever that stimulates its brain in the same region that stimulates defensive aggression. It is also associated with cortisol (the “stress hormone”), substance P (involved in pain perception), cholecystokinin (associated with panic), all suggesting that it is a reaction to frightening and painful situations.</p>
<p>Defensive aggression in some species seems to involve qualitatively different and “milder” types of attack (less likely to cause injury) than other types of aggression. It is also prompted by the same types of situations and same regions of brain stimulation associated with fleeing, hiding, and submission signals (like baring the belly to get an opponent to stop attacking.) And animals engage in defensive aggression reflexively when hurt even when there is no visible attacker; they’ll “attack” inanimate objects or the air, as though “letting off steam”. Speculatively, these details suggest that defensive aggression is something of a reflexive “lashing out” when an animal is hurt or scared, not very well optimized to injure or intimidate an opponent, and have more in common with other self-preservation behaviors (like fleeing, hiding, or submitting) than with other types of aggression.</p>
<p><em>“Affective Defense”/“Defensive Rage” in Cats</em></p>
<p>“Affective defense” in mammals typically involves flattening of the ears, lowering of the body, drawing in the head, pupillary dilation, piloerection, hissing, and stiffening of the tail. It is triggered by either a conspecific or a member of another species who is perceived to be a threat.[18]</p>
<p>In cats, “defensive rage” behavior includes ear retraction, piloerection, back arching, pupillary dilatation, vocalization, unsheathing of the claws, and paw strike. It occurs when a cat is threatened by either a member of the same or different species. Stimulating the midbrain periaqueductal gray (PAG), which is generally a pain center, elicits defensive rage behaviors in cats.[21]</p>
<p>Various compounds associated with pain and stress, as well as acute ethanol intoxication, can affect the “defensive rage” response.</p>
<p>Blocking substance P, a substance involved in pain response, in cats reduces the defensive rage response to stimulation in the medial amygdala and medial hypothalamus.[22]</p>
<p>Ethanol enhances defensive rage responses in cats, while it reduces predatory attacks.[23]</p>
<p>Cholecystokinin, a neuropeptide and digestive hormone which causes nausea and induces panic when administered to humans, potentiates the defensive rage response in cats.[24]</p>
<p>Naloxone reduces the threshold for inducing defensive rage in the cat by brain stimulation; opioid receptor agonists block defensive rage.[57]</p>
<p>Defensive rage in cats appears to be inhibited by the medial hypothalamus. Medial hypothalamus lesions make cats extremely defensive – they spit and claw in the presence of humans, they’ll run from a dog and fight if attacked.[48] However, olfactory bulbectomy doesn’t affect defensive aggression in cats.[48]</p>
<p><em>Defensive Aggression in Dogs</em></p>
<p>The septal region in the brain is involved in inhibiting defensive aggression in dogs. Septal lesions make dogs more “overexcitable, baring their teeth, and attempting to bite when handled.”[48]</p>
<p><em>Cortisol-Related Aggression in Hamsters</em></p>
<p>Syrian and Siberian hamsters are more aggressive in the winter (short-day condition) than the summer, despite their testes being smaller in the winter. The increased aggression appears to be mediated by elevated cortisol, downstream of melatonin signaling. In primates as well, seasonal rises in testosterone don’t always correlate to increased aggression, and exogenous T doesn’t always increase aggression. Just as in male humans, there is no correlation between testosterone levels and aggressive behavior.[33]</p>
<p>However, amygdala lesions suppress shock-induced fighting in hamsters.[48]</p>
<p><em>Defensive Aggression in Marmosets</em></p>
<p>As with cats and opossums, stimulating the marmoset ventromedial hypothalamus elicits aggressive responses, chiefly short attacks and vocal threats, as well as flight responses.[27]</p>
<p>Female marmosets attack intruders; the magnitude of the aggressive response correlates positively with testosterone level immediately after the attack.[92]</p>
<p><em>Defensive Aggression in Mice</em></p>
<p>Defensive aggression in mice seems to be inhibited by the septal region of the brain and enhanced by the olfactory bulb, unlike hamsters and gerbils who do not have an olfactory bulb-dependent aggression response.[48]</p>
<p>Mice who have had their olfactory bulb removed do not fight back when attacked or exhibit fighting behavior after electric shocks. Peripheral anosmia does not cause this response, indicating that its effect on aggression is not due exclusively to the fact that it is necessary for smell.[48]</p>
<p>Septal lesions in mice enhance defensiveness; struggling, biting, and escaping.[48]</p>
<p><em>Defensive Aggression in Rabbits</em></p>
<p>Septal lesions increase defensive responses (like foot thumping) to human experimenters in rabbits.[48]</p>
<p><em>Defensive Aggression in Rats</em></p>
<p>Defensive biting in rats is different from attack biting; it is usually targeted at the snout, while attacking rats bite their opponent’s back; and defensive biting is seen <em>more</em> often against human hands or tools than against rats. Defensive biting only occurs during or immediately after the defending animal has been hurt, and only when escape is impossible. Defensive biting also does not involve piloerection, while offensive biting always does.[4]</p>
<p>Defensive aggression is specifically selected against when rats are domesticated.</p>
<p>233 wild-caught rats were selected for “tameness”, that is, lower rates of aggressive behaviors towards human handlers, or “aggression”, that is, higher rates of aggressive behaviors towards human handlers, over 8-10 generations. [1]</p>
<p>There was no difference in testosterone levels between tame and wild rats of both sexes; however, aggressive rats had significantly higher serum cortisone levels than wild rats, in both sexes. Aggressive rats had significantly larger startle responses to stimuli than tame rats, in both sexes.[1]</p>
<p>Tame rats show fewer displays of defensive aggression towards other rats than aggressive rats, but no fewer displays of offensive aggression.[1]</p>
<p>As with other animals, the septal and medial hypothalamus regions of the brain appear to inhibit defensive aggression in rats, while the amygdala and hippocampus stimulate it.</p>
<p>Septal lesions in rats enhance defensiveness – heightened fighting in response to foot shock and handling. Medial hypothalamus lesions also dramatically increase defensiveness. Amygdala and hippocampus lesions, by contrast, decrease defensiveness.[48][79]</p>
<p>Certain drugs affect defensive aggression in rats.</p>
<p>“Irritable aggression” in both male and female rats – an increased tendency to fight each other when deprived of food or sleep or administered electric shocks – is increased by administering cannabis or delta-9-THC.[78]</p>
<p>Lithium reduces aggression in rats in response to pain from hot plates or electric shocks.[80]</p>
<p>The tricyclic antidepressant drugs imipramine, amitryptiline, and desmethylimipramine, and the MAOIs nialamide, iproniazid, and pargyline, all increased shock-induced aggression in rats.[81]</p>
<p>Acute administration of dopamine intravenously increases shock-induced aggression in rats, while acute intravenous norepinephrine reduces it.[82]</p>
<p>Phencyclidine (PCP) dose-dependently reduces defensive aggression in rats both against other rats after foot shock, and against an inanimate target after immobilization and tail shock.[83]</p>
<p>Histamine increases rat aggression in response to foot shocks; this effect is further potentiated by an H1-receptor-blocking antihistamine and suppressed by an H2-receptor-blocking antihistamine, suggesting that H2 histamine receptors are involved in defensive aggression.[84]</p>
<p>Cholecystokinin type 2 receptors in the PAG are necessary for two defensive behaviors in rats, freezing and escape.[116]</p>
<p><em>Pain-Induced Aggression in Spider Monkeys</em></p>
<p>Spider monkeys will bite other monkeys, rats, mice, dolls, and balls immediately after being administered painful electric shocks. If two monkeys are both shocked, initially both will attack; after repeated shocks, a pattern emerges where one always attacks and one always flees.[29]</p>
<p><em>Aggressive Vocalization and Pain-Induced Aggression in Squirrel Monkeys</em></p>
<p>The “kecker” call, associated with aggression, can be stimulated in squirrel monkeys by electrodes in the amygdala, hypothalamus, and periventricular gray.[36]</p>
<p>Phencyclidine at high doses blocks pain-induced aggression in squirrel monkeys.[94]</p>
<p><strong>Social Aggression (“Offensive Aggression”, “Intermale Aggression”) – Testosterone, Vasopressin, Low Serotonin</strong></p>
<p>Social aggression, unlike defensive aggression, is directed only at members of one’s own species. It is sometimes called “intermale aggression” or “hormone-dependent aggression” even though it is not exclusive to males, because it is generally more common in males and correlates well to testosterone levels. It also inversely correlates to serotonin levels.</p>
<p>Social aggression revolves around competition for scarce resources – mates, territory, or in some species food and water. It generally involves threat displays intended to make an opponent back down without a fight.</p>
<p>Social aggression is the least well-categorized of the types of aggression I describe here; in some species (such as marmosets) there doesn’t seem to be a clear distinction between social and defensive aggression. In rats, social aggression is always accompanied by piloerection (hair standing on end) while defensive aggression never is. But not all species seem to have this sharp distinction.</p>
<p>There are major differences between the ways “social aggression” is studied in rodents vs. primates which make the situation more confusing.</p>
<p>In rodents, “offensive aggression” is defined as the propensity for an individual to attack an unknown intruder into his space. Since the “resident” invariably defeats the “intruder”, dominance and “offensive aggression” are identical. Dominant rodents are higher in testosterone than average and have more access to mates. In rodents, the relationship between social aggression and the hormones serotonin and testosterone is straightforward: testosterone raises social aggression and serotonin lowers it. Stress and anxiety anticorrelate with offensive aggression.</p>
<p>In primates and social carnivores such as wolves and mongooses, however, studies are typically done within a group of individuals who live together (in the wild or the lab). Conflicts are primarily with community members, and only occasionally with strangers. And intragroup conflicts often resolve with little or no physical violence, just threat behaviors and mild scuffling. So “dominance” is a more complex phenomenon; a dominant individual in a group is the one who wins most conflicts and receives the most submission behavior, and has the most access to resources (like mates, food, and water), but the dominant individual is <em>not</em> necessarily the most aggressive individual.</p>
<p>The relationship between dominance, aggression, and the hormones testosterone, serotonin, and cortisol, is likewise complicated in primates and in social carnivores. Dominance rank does not necessarily correlate positively with aggression. Completely nonviolent individuals are, by definition, at the bottom of the dominance hierarchy (they lose all fights they’re in), but otherwise, in primates and carnivores, “fighting more” is not necessarily “winning more.” The most dominant individuals in a stable hierarchy are rarely threatened, and can easily cause others to back down with a harmless threat display.</p>
<p>Aggression does not always correlate with cortisol in primates and social carnivores. Dominance usually correlates positively with baseline cortisol levels. On the other hand, losing fights causes an <em>acute</em> spike in cortisol in the loser. Because of the negative feedback in cortisol levels, these two observations are consistent; frequent experiences of losing fights can be expected to <em>depress</em> long-term baseline cortisol levels, even as each losing battle causes a spike in cortisol in the short term.</p>
<p>Serotonin in primates correlates <em>positively</em> with dominance rank and with <em>non-severe</em> aggression (initiating threat displays or harmless physical scuffles) but <em>negatively</em> with severe aggression (wounding another primate). As in rodents, low serotonin correlates with serious violence in primates, but primates also have a more complex repertoire of dominant/threatening social behavior which are associated with <em>high</em> serotonin.</p>
<p>Testosterone, though, in primates and carnivores just as in rodents, has a straightforward positive correlation with both dominance and aggression.</p>
<p><em>Social Aggression in Baboons</em></p>
<p>Among female baboons, testosterone correlates with dominance rank and within-individual aggression but not across-individual aggression – i.e. higher-T baboons are not more aggressive overall, but particular baboons are more aggressive at times when their T is higher.[90]</p>
<p>Dominant baboons have more copulatory success, are more likely to dominate in conflicts (receive submissive gestures or avoidance from other baboons), and are more likely to win conflicts over food. But they do not engage in more aggressive encounters. High dominance rank among baboons is associated with low baseline cortisol and high cortisol response to stress.[98]</p>
<p><em>Social Aggression in Chimpanzees</em></p>
<p>Behavioral style in chimpanzees was broken down into 6 principal components:</p>
<ul>
<li>“Smart” (uses coalitions when initiating aggression; is usually the groom-ee in grooming interactions; has most play offers accepted)</li>
<li>“Affiliative” (participates in a lot of grooming; frequent hugging and touching)</li>
<li>“Playful” (plays often and with many other chimps)</li>
<li>“Aggressive” (most social interactions are aggressive; has many coalition partners in aggression)</li>
<li>“Friendly” (has many friends; spreads affiliative behavior around many individuals)</li>
<li>“Mellow” (frequently does not react to aggression or social approach)</li>
</ul>
<p>“Friendly” and “Affiliative” personality was not associated with dominance rank.</p>
<p>“Playful” and “Smart” personalities were more likely to be subordinate.</p>
<p>“Aggressive” and “Mellow” personalities were more likely to be dominant.</p>
<p>Cortisol did not correlate with rank, aggression given, or aggression received. There was a nonsignificant positive association between cortisol and the “Smart” and “Aggressive” styles.[61]</p>
<p>In adolescent male chimpanzees, testosterone (after correcting for age) was positively associated with dominance and aggression given, negatively associated with aggression received, and positively associated with the “mellow” behavioral style. Testosterone was not associated with the “Aggressiveness” behavioral style. Note that “Aggressiveness” indicates that a high percent of one’s total social interactions are aggressive, so an individual who is both aggressive and friendly might have a <em>low</em> “Aggressiveness” score.[100]</p>
<p>Dominance rank, aggression, and testosterone are correlated in adult male chimpanzees.[98]</p>
<p>Citalopram, an SSRI, reduced aggressive behavior in a zoo chimpanzee.[102]</p>
<p><em>Aggression and Social Dominance in Cynomolgus Monkeys</em></p>
<p>Dominant cynomolgus monkeys (those who win most conflicts) tend to also engage in more aggression overall. Serotonin tends to inhibit aggression.</p>
<p>Other hormones have relationships with aggression and dominance as well: testosterone is positively correlated with dominance rank; cortisol is positively correlated with rank in males but not females; and ovariectomy increases both aggression and submission in females, suggesting that some ovarian hormone is responsible for blocking aggression and submission.</p>
<p>In female cynomolgus monkeys, the lower the social rank of a monkey, the more aggression she received and the more submissive behaviors she practiced. But aggressive behaviors follow an inverted U-shaped relationship with rank; the most dominant individuals actually engage in less aggression than the middle ranks, though the most subordinate individuals do the least aggression of all. If monkeys are split into two groups, “dominant” and “subordinate”, the difference in aggression is not significant, but it’s clear how with this pattern, different choices of split point would result in different conclusions.[107]</p>
<p>Dominant monkeys were larger and had higher levels of LH, cortisol response, oxytocin, and dopamine metabolites than subordinates.[107]</p>
<p>There was no association between cortisol levels and social rank in female cynomolgus monkeys. Higher-ranked monkeys engaged in more aggression while lower-ranked monkeys engaged in more submission.[59]</p>
<p>When given sertraline, an SSRI, adult female cynomolgus monkeys showed changes in social behavior. Before treatment, dominant monkeys were more aggressive than subordinates; with sertraline, dominant monkeys engaged in less aggression until they matched the low subordinate level. Before treatment, subordinate monkeys engaged in more submission than dominants; with sertraline, the subordinates’ submissive behavior dropped to match the low dominant level.[103]</p>
<p>Homovanillic acid levels (a metabolite of dopamine) were higher in both male and female dominant cynomolgus monkeys than in subordinates. No association with norepinephrine metabolites. In males but not females, lower HIAA (a metabolite of serotonin) was associated with dominance.[105]</p>
<p>Dominant male monkeys have higher basal cortisol and testosterone levels; subordinate monkeys have stronger cortisol response to ACTH challenge.[58]</p>
<p>Ovariectomy causes a 2-3x increase in aggression and submission in female cynomolgus monkeys.[106]</p>
<p>As with other animals, ethanol can stimulate aggression in cynomolgus monkeys.</p>
<p>Acute and chronic alcohol drinking both increase rates of contact aggression in cynomolgus monkeys.[104]</p>
<p><em>Social Aggression in Dogs</em></p>
<p>Domestic dogs who engaged in “leash aggression” (attempting to attack other dogs while on leash) were matched to a dog of the same age, sex, and breed who did not engage in “leash aggression.” Aggressive dogs were more likely to bark, lunge, and growl at model dogs than non-aggressive dogs. Aggressive dogs had higher levels of free vasopressin than nonaggressive dogs, but no difference in oxytocin.[89]</p>
<p>Among assistance dogs bred for affectionate dispositions and low aggressiveness, oxytocin was higher than in pet dogs.[89]</p>
<p><em>Social Aggression in Gerbils</em></p>
<p>Like mice and rats, male gerbils who cohabit with a female will attack unfamiliar intruders in their home territory.[109] Castration abolishes territorial aggression; castration + supplemental testosterone restores it.[110]</p>
<p>Olfactory bulbectomy reduces social aggression in gerbils; high dose testosterone propionate reverses this effect. [48]</p>
<p>Gerbils will typically attack unfamiliar gerbils and also rats and mice that venture into their territory. Gerbils dosed with delta-9-THC will still sniff, approach, and chase a mouse, but will not bite it.[111]</p>
<p><em>Social Aggression in Hamsters</em></p>
<p>As with other animals, testosterone and other androgens increase aggression in hamsters; so do the hormones vasopressin and corticotropin releasing hormone (CRH), a stimulator of the HPA-axis.</p>
<p>In hamsters, vasopressin administration increases rates of flank marking (a dominance behavior), and vasopressin antagonists reduce flank marking by dominant hamsters, which in turn increases flank marking by submissive hamsters.[33]</p>
<p>Blocking vasopressin dose-dependently reduces male hamsters’ rate of attacking intruders.[91]</p>
<p>A CRF1 antagonist blocks attacks against intruding male hamsters – higher latency to bite, lower chase duration, lower attack frequency.[63]</p>
<p>Anabolic steroids (testosterone cypionate, nandrolone deconate, and boldenone undecylinate) increase offensive aggression in male hamsters.[74]</p>
<p><em>Social Aggression in Marmosets</em></p>
<p>Common marmosets exhibit “vocal threats” along with limited piloerection in the tail and relatively harmless “short attacks”, when competing over food. Short attacks are generally made against lower-ranking or younger monkeys, are terminated by flight or submissive squeals, and are never followed by chasing.</p>
<p>Genital display and flicking of the ear-tufts are behaviors that alpha marmosets usually make towards subordinate marmosets, or any marmosets towards strange marmosets and humans. If the strangers counter-threaten, serious biting attacks ensue. Violent attacks and fighting are accompanied by substantial piloerection.[26]</p>
<p>In the common marmoset and black tufted-ear marmoset, as well as in lemurs and tamarins, dominant individuals have higher cortisol than subordinates.[88]</p>
<p><em>Social Aggression in Mice</em></p>
<p>Olfactory bulbectomy reduces social aggression in mice; peripherally induced anosmia does not.[48]</p>
<p>Naloxone suppresses intermale aggression in isolated mice.[75]</p>
<p>Cannabis reduces the tendency of mice to fight an intruder, even at doses too low to suppress locomotor activity.[78]</p>
<p>In a subpopulation of rats and mice, roughly a quarter of subjects, ethanol administration increases aggression against intruders. In particular, ethanol lengthens the duration of bursts of aggressive activity, but does not affect the latency to attack.[96]</p>
<p>Mice lacking the HNMT gene have higher levels of brain histamine, and are more aggressive against intruders. They also have an altered sleep/wake cycle (they are more active during the light period when mice usually sleep, and less active during the dark period when mice are usually awake.)[117]</p>
<p>Mice lacking substance P receptors are far less likely to attack an intruder.[118]</p>
<p><em>Social Aggression in Rabbits</em></p>
<p>The male rabbit who is most likely to follow, attack, and chase is considered the dominant rabbit in a group; he has higher peripheral testosterone levels than the others.[93]</p>
<p><em>“Offensive” or “Hormone-dependent” Aggression in Rats</em></p>
<p>Offensive aggression in rats is clearly delineated from defensive aggression.</p>
<p>In a colony of rats, if an intruder enters, one male rat will typically attack the intruder; this male is also the dominant rat in “agonistic encounters” within the colony. These attacks are preceded by approach, sniffing, and (if the rat is not a colony member) piloerection, followed by biting, boxing, and climbing on top of the other rat. The intruder rat rarely bites back after being attacked.[4]</p>
<p>Only hormone-dependent aggression in rats is accompanied by piloerection; defensive and predatory aggression are not. Hormone-dependent aggression is not territorial – a male rat will attack an unfamiliar male rat even if he is in an unfamiliar area.[6]</p>
<p>When a cat smell is added to a rat cage, offensive attacks disappear; defensive biting is unchanged or increased, however.[3]</p>
<p>Offensive aggression in rats is associated with testosterone, copulation, and winning fights; it is reduced when a rat experiences “disappointment”, failing to get an expected reward.</p>
<p>Castration reduces social aggression in male rats, and testosterone supplementation increases it. The amount of aggression in intact male rats correlates with the baseline level of serum testosterone. Rat testosterone spikes after exposure to a receptive female and after successful aggression.[6]</p>
<p>Male rats will exhibit much more social aggression if they cohabit with females. Both male and female rats will exhibit more hormone-dependent aggression if they are competing for scarce food.[6]</p>
<p>Offensive aggression in male rats increases after copulation with females.[7]</p>
<p>Male intruder rats display offensive aggression against female residents, but never males. Female intruder rats rarely are attacked, and when they are it is usually only after they rebuff multiple attempts to mate.[8]</p>
<p>When access to food or water is restricted, the “alpha” male or female rats in a colony (those who attack intruders the most) are <em>not</em> the same rats who get the most access to the food or water. But alpha male rats <em>are</em> the ones who have the most access to copulating with females.[8]</p>
<p>Rats surprised by a lack of reward in a situation that normally provides rewards show a reduction in social aggression and a greater propensity to be attacked.[9]</p>
<p>Social aggression in rats also anti-correlates with serotonin and is increased by serotonin-depleting drugs and decreased by serotonergic drugs.</p>
<p>Male Wistar rats treated with PCPA, a drug which depletes cerebral serotonin, or a saline control, before being placed in another weight-matched rat’s cage. The PCPA-treated intruder rats frequently attacked the residents; the control rats never did. PCPA-treated rats were also more likely to socially approach the resident rats. Defensive and submissive behaviors were unchanged.[2]</p>
<p>When it was the resident rats who were treated with PCPA or control, treated rats attacked more; there was no change in defensive or submissive behaviors.[2]</p>
<p>Hypothalamic stimulation prompts rats to attack other rats (male and female), anaesthetized or dead rats, and mice, but not toy rats. Castration increases latency of hypothalamic aggression; testosterone reverses the effect. Serotonin-receptor-binding drugs such as fluprazine, quipazine, and TFMPP, increase the threshold for hypothalamic aggression.[5]</p>
<p>Perhaps surprisingly, though, social aggression in rats anticorrelates with anxiety. Rats bred for low rates of anxious behavior were more aggressive than rats bred for high rates of anxious behavior or rats without selective breeding.[76]</p>
<p><em>Social Aggression in Mongooses</em></p>
<p>In the dwarf mongoose, dominant females have higher cortisol levels than subordinate females.[88]</p>
<p>Unusually among social mammals, mongooses don’t show elevated testosterone in situations of conflict. Testosterone levels in male mongooses don’t correlate with rates of aggression, dominance rank, or mating rates. [112]</p>
<p>Mongooses are unusual in that they are cooperative breeders; only a few individuals in a group reproduce, and the rest are “helpers” who look after the children. However the “helper” males have just as much testosterone as the dominant males. Mongooses also continue to play even as adults, which many species don’t.[112]</p>
<p><em>Social Aggression in Oryx</em></p>
<p>Oryx engage in postural threats (erect posture, threatening with horns) and head-butting conflicts with the horns of other males. They submit by bowing their heads or leaving after challenged. Melengestrol acetate, a progestin, reduces aggression when given in the feed of a herd of male oryx. Melengestrol reduces testosterone levels, as well as levels of posturing, contact, chasing, and submission.[108]</p>
<p><em>Social Aggression in Rhesus Monkeys</em></p>
<p>In rhesus monkeys, serotonin is negatively associated with intra-species aggression in rhesus monkeys, but positively associated with dominance. When aggression is split into the two categories of competitive aggression (threatening, chasing, and displacing, without causing serious injury) vs. severe aggression (causing wounds), we find that serotonin, and dominance rank, are <em>positively</em> associated with competitive aggression and <em>negatively</em> associated with severe aggression.</p>
<p>Testosterone is positively associated with aggression. Cortisol is negatively associated with threat displays.</p>
<p>In free-living young male rhesus monkeys, ACTH and norepinephrine levels were positively associated with aggressiveness ratings, while 5-HIAA (a serotonin metabolite) levels were negatively associated.[27]</p>
<p>28 young male monkeys taken from 3500 free-living macaques on an island in South Carolina were rated for “aggressiveness” by researchers based on direct observation, examination of scars and wounds, and photographs. ACTH was significantly positively associated with aggressiveness, as was norepinephrine; serotonin was negatively associated.[37]</p>
<p>Dominance among females in a free-living macaque colony is associated with the frequency of threatening, displacing, and chasing behavior, but not with severe aggression or spontaneous wounding. High dominance rank correlated positively with 5-HIAA (a serotonin metabolite.) Severe aggression or wounding correlated negatively with 5-HIAA.[41]</p>
<p>The C77G polymorphism in the mu-opioid receptor gene in macaques is associated with an abnormally low cortisol response to stress and pain. Threat displays, such as teeth-baring, staring, and ear-flapping, correlated <em>negatively</em> with cortisol levels. The mutant macaques had significantly higher rates of threat display, but not more cage-shaking or attacks on self or inanimate objects.[35]</p>
<p>Testosterone in male rhesus monkeys correlates positively with rates of aggression, dominance rank, rate of receiving submission, and “tension” (yawning, teeth grinding, and banging objects; also symptomatic of inhibited aggressive behavior due to the presence of dominant animals.) High testosterone correlates negatively with submissive behaviors. On the other hand, the reverse correlation does not apply; the monkeys most likely to submit do not have the lowest testosterone.[40]</p>
<p>Dominance in rhesus monkeys seems to involve activity in the amygdala and lateral hypothalamus.</p>
<p>If you remove the amygdala from a dominant rhesus monkey, he becomes submissive, never aggresses or retaliates, and moves to the bottom of the dominance hierarchy. He also becomes more aggressive/fearless in individual-cage settings.[41]</p>
<p>Stimulation of male rhesus monkeys in the lateral hypothalamus prompts them to aggressively attack the dominant monkey. The stimulated monkeys did not attack females or inanimate objects. The stimulated subordinate monkey usually lost fights with the dominant; the dominant monkey mounted the female more and actively threatened the stimulated subordinate male. Eventually the formerly subordinate monkeys became dominant; their hair stood on end, they strutted, they <em>looked</em> dominant, while the formerly dominant monkeys crouched and had matted hair.[39]</p>
<p>When amphetamine is administered to stumptail macacques, affiliative behavior decreases and aggressive behavior increases.[97]</p>
<p><em>Social Aggression in Squirrel Monkeys</em></p>
<p>Squirrel monkeys make threat displays and aggressive vocalizations when faced with a strange intruder; the rate of these aggressive responses increases when they are given ethanol or the benzodiazepine chlordiazepoxide.[95]</p>
<p><em>Dominance in Vervet Monkeys</em></p>
<p>Dominance is measured by how often a male monkey succeeds in agonistic encounters (i.e. the other monkey submits or avoids). 36 adult male vervet monkeys were separated into 12 groups of 4. In each, a dominant male (winning over 85% of encounters) emerged. Tryptophan and fluoxetine (both serotonergic) significantly increased the frequency of approaching, proximity, and grooming but decreased the rate of aggressive behaviors. By contrast, fenfluramine and cyproheptadine (which deplete serotonin), decreased approaching, proximity, and grooming and increased aggression.[38]</p>
<p>The animals treated with serotonergic drugs became dominant and remained so; the animals treated with anti-serotonin drugs became subordinate and remained so. This suggests that low serotonin may be a signal of <em>low</em> or <em>threatened</em> dominance, which prompts aggression.[38]</p>
<p>Cortisol levels do not correlate with social dominance in stable groups of vervet monkeys. Cortisol levels rise during competition for dominance among familiar males, particularly among the winners of such competitions.[60]</p>
<p><em>Social Aggression in Wolves</em></p>
<p>Cortisol is higher in dominant wolves than subordinate wolves, consistent across 3 packs and 2 years. There is no overall correlation between cortisol and levels of agonistic and aggressive behavior. However, cortisol is higher during the mating period, and so is aggressive behavior. Dominant wolves do not fight more than subordinate wolves; they just win a higher percentage of their fights.[85]</p>
<p>Male wolves are more likely than female wolves to fight against other packs; male wolves also have higher cortisol than female wolves.[86]</p>
<p>Dominant male wolves have higher testosterone and cortisol than subordinate wolves.[87]</p>
<p><strong>Maternal Aggression: Oxytocin, Vasopressin</strong></p>
<p>Maternal aggression is the propensity of mammalian mothers to become more aggressive in defense of their offspring during pregnancy and while nursing.</p>
<p><em>Maternal Aggression in Mice</em></p>
<p>Mouse maternal aggression is promoted by nursing and caring for infant offspring, not necessarily pregnancy or even female sex. The male sex hormone testosterone, in addition to pregnancy-related female hormones, increases maternal aggression.</p>
<p>In a species of mice where fathers as well as mothers have significant parental investment into raising children, there is a “paternal aggression” phenomenon in which male parents are more aggressive towards intruders than male virgins are.[66]</p>
<p>Prenatal testosterone exposure increases maternal aggression in mice.[67]</p>
<p>Mouse maternal aggression is blocked by stress, as well as stress and anxiety-related hormones, such as CRH, neuropeptide Y, and neurotensin.</p>
<p>Corticotropin-releasing hormone, as well as the presence of stressors, inhibits maternal aggression in mice. Nursing mice also show reduced fear and anxiety.[50]</p>
<p>Mice selected for high maternal aggression have reduced neuropeptide Y expression, which also correlates with decreased fear and anxiety. They also have increased CRF binding protein expression (which reduces the effect of CRF), and increased NO synthase. [51]</p>
<p>Neurotensin injected into a lactating mouse’s brain significantly and dose-dependently reduces maternal aggression. Neurotensin antagonists significantly increase maternal aggression. Neurotensin has many functions, including stimulating ACTH production.[53]</p>
<p>Serotonin-related drugs also affect maternal aggression in mice, though the pattern of effect is not obvious.</p>
<p>PCPA, a serotonin depletion agent, as well as 5-HTP, a serotonin precursor, inhibit maternal aggression in postpartum mice. Antagonists of serotonin receptors such as mianserin, methiothepin, and methysergide, also reduce maternal aggression.[70] 5-HTP and PCPA have opposite effects on serotonin but they both increase dopamine levels, and also increase levels of 5HIAA, the metabolite of serotonin.[70]</p>
<p>Imipramine, a tricyclic antidepressant with strong effects on many neurotransmitter receptors, reduces maternal aggression in mice.[69]</p>
<p>Morphine reduces maternal care for pups and maternal aggression in mice.[68]</p>
<p><em>Maternal Aggression in Rats</em></p>
<p>Maternal aggression in rodents, like predatory aggression and unlike social aggression, is <em>not</em> accompanied by a cortisol response, elevated arousal, or social signaling (threats). Maternal aggression tends to attack more vulnerable body parts (the belly) as opposed to social aggression (which attacks the back) or defensive aggression (which attacks the face).[33]</p>
<p>Female rats become more aggressive against unfamiliar rats during pregnancy, after birth, and during lactation. To a lesser extent, cohabiting with even a sterile male induces increased aggression in female rats.[6]</p>
<p>Female social aggression in rats is confined to the living area, unlike social aggression in male rats; a female rat outside her home will not attack a stranger.[6]</p>
<p>Female rats need to be stimulated by suckling pups in order to have maternal aggression. Removing nipples doesn’t remove the aggression, but anaesthesia to the ventral skin does, suggesting that the trigger is sensory rather than lactation-related.[10]</p>
<p>Lactating female rats, but not alpha male rats, will bury an intruder after attacking it. Like social aggression and unlike defensive aggression, piloerection is present in both maternal and alpha male attacks on intruders.[55]</p>
<p>Maternal aggression in rats is enhanced by oxytocin and vasopressin, as well as GnRH (which increases the release of sex hormones).</p>
<p>Blocking oxytocin chemically reduces maternal aggression in high-aggression lactating rats, and adding IV oxytocin increases maternal aggression in low-aggression lactating rats. Likewise, blocking vasopressin in high-aggression lactating rats reduces maternal aggression, while IV vasopressin in low-aggression lactating rats increases maternal aggression.[11]</p>
<p>GnRH antagonists reduce maternal aggression in rats, but not maternal care.[71]</p>
<p>Serotonin has a complicated relationship with maternal aggression in rats.</p>
<p>Lesions to the serotonin-producing cells in the dorsal raphe reduce both maternal aggression and maternal care in rats, indicating that serotonin is necessary for maternal aggression.[54]</p>
<p>Also, fluoxetine (an SSRI) increases maternal aggression in rats relative to controls.[64]</p>
<p>On the other hand, serotonergic drugs often decrease maternal aggression, such as fluprazine [64], amitriptyline[73], and desipramine.[73]</p>
<p>In keeping with the finding that stress anticorrelates with maternal aggression, all benzodiazepines (which have anxiolytic effects) increase maternal aggression in rats.[67]</p>
<p>The lateral septum is necessary for maternal aggression in rats, and the periaqueductal gray (PAG) inhibits it, as one would expect for a behavior that is negatively associated with anxiety.</p>
<p>Lesions to the lateral septum in rats abolish maternal aggression, as well as maternal behavior such as retrieving, licking, and nursing pups.[52]</p>
<p>Rats lesioned in the periaqueductal gray (PAG) attack intruders 2x as often as controls.[56]</p>
<p>Domestication does not inhibit maternal aggression; wild and domesticated Norway rat strains show no difference in maternal aggression.[77]</p>
<p><em>Maternal Aggression in Voles</em></p>
<p>A nitric oxide synthesis inhibitor reduces maternal aggression in prairie voles.[72]</p>
<p>Prairie voles are monogamous, and after pair-bonding, <em>male</em> prairie voles become much more aggressive against intruders. Vasopressin receptor antagonists prevent this increase in aggression, while supplemental vasopressin increases it.[113]</p>
<p>It’s possible that male aggression in voles actually is a closer hormonal match to maternal aggression given the pair-bonding aspect. Consistent with this hypothesis, supplemental testosterone does not increase aggression in male voles[114] and castration does not inhibit aggression.[115]</p>
<p><strong>Predatory Aggression</strong></p>
<p>Predatory aggression is violence against edible prey. It is almost always directed against members of a different species, though some mutations make animals attack conspecifics in ways that resemble predatory aggression.</p>
<p>Predation is distinct from social and defensive aggression in that it is <em>stealthy</em> (there is no vocalization or threat display, to avoid scaring off the prey) and it is <em>pleasurable rather than stressful</em> to the predator. Predatory behavior is not associated with cortisol response, and it is stimulated by the centers of the brain associated with reward and alertness, rather than the ones associated with fear and pain.</p>
<p><em>Predatory Aggression in Baboons</em></p>
<p>Olive baboons hunt occasionally, mostly hares, gazelles, birds, and other ungulates. Male olive baboons do most of the killing and eating of prey.[101]</p>
<p><em>Predatory Aggression in Cats</em></p>
<p>Cats can attack other animals in two obviously distinct ways; “affective attack”, which involves hissing, growling, back arching, and piloerection; and “predatory attack”, in which the cat quietly stalks its prey and does not make aggressive noises or arch its back, and its hair does not stand on end.[12]</p>
<p>Cats who are quicker to attack rats are also quicker to approach novel stimuli and slower to avoid threatening stimuli; the reverse is true of cats who are slow to attack rats. Predatory behavior in cats seems to be related to curiosity and fearlessness.[21]</p>
<p>Predatory aggression in cats is stimulated by activity in the lateral hypothalamus and amygdala and inhibited by activity in the periaqueductal gray.</p>
<p>Electrical stimulation of the lateral hypothalamus in the cat (the same area that promotes feeding and wakefulness behavior) elicits predatory aggression.[21]</p>
<p>Cats lesioned in the amygdala stop killing mice.[48]</p>
<p>Lesions in the periaqueductal gray (PAG) lowered the threshold to cats attacking rats when stimulated in the hypothalamus.[43]</p>
<p>Gonadectomy in female cats makes them quicker to attack a rat; gonadectomy in male cats makes them slower to attack a rat. This suggests a positive association between testosterone and predation in cats.[25]</p>
<p>The muscarinic agonist arecoline can induce biting attack in the cat; muscarinic antagonists such as scopolamine and atropine block this effect.[62] Arecoline is the psychoactive ingredient in betel nuts, and in humans causes an effect similar to nicotine – alertness, energy, euphoria, and relaxation.</p>
<p><em>Predatory Aggression in Chimpanzees</em></p>
<p>There is significant overlap between intraspecific aggression and predation in chimpanzees. They sometimes stalk each other before attacking, and they have been known to eat infant chimpanzees after a fight.[49]</p>
<p><em>Predatory Aggression in Foxes</em></p>
<p>Administration of 5-HT (serotonin) significantly reduced a fox’s likelihood of attacking a rat placed in its cage.[42]</p>
<p><em>Predatory Aggression in Mice</em></p>
<p>Mice kill and eat crickets. A strain of mice bred for large amounts of voluntary wheel-running had no significant difference from controls in their rates of intermale aggression or maternal aggression, but the wheel-running mice were quicker to attack crickets. Since wheel-running is a pleasurable activity that mice seek out, this suggests that propensity to kill crickets is associated with reward from active behaviors. The wheel-running mice were smaller and had more pups than the control mice; serum testosterone levels were the same.[17]</p>
<p>The reproductive and hormone status of female mice does not correlate with their propensity to attack crickets, suggesting that predatory and maternal aggression have different physiological bases. Ovariectomy reduces maternal aggression in mice but does not reduce cricket-killing.</p>
<p>A mouse’s sense of smell seems related to its ability to distinguish its own species from others. Abolishing it doesn’t reduce predation, but does cause cannibalism (a mouse “preying” on its own kind.)</p>
<p>Experimentally induced anosmia reduces both maternal aggression and intermale aggression, but not cricket-killing.[19]</p>
<p>Olfactory bulbectomy in mice causes cannibalism – one adult mouse will kill and eat the other, and mothers will eat their young.[48]</p>
<p>Similarly, the hormone vasopressin in mice seems to be essential for aggression against other mice, but not for predation against other species.</p>
<p>Mice with a disrupted vasopressin receptor, Avpr1b-/-, have lower intermale aggression, maternal aggression, and defensive biting responses, but the same number of “defensive avoidance” behaviors (fleeing, boxing). Predatory aggression against crickets is intact in Avpr1b-/- mice. This gene seems to be required for all types of attack responses towards conspecifics, but not to other species.[20]</p>
<p>Some neuroactive drugs block mouse predation, including drugs that increase serotonin.</p>
<p>Amphetamine, imipramine, and tripelennamine (an antihistamine) block mice from killing frogs.[14] Serotonergic drugs (imipramine, fluoxetine, 5-HT) inhibit locust-killing in CBA mice[42].</p>
<p><em>Predatory Aggression in Minks</em></p>
<p>If you put a rat in a mink’s cage, it will attack 100% of the time. When given 5-HT (serotonin), only half the minks attacked the rat.[42]</p>
<p><em>Predatory Aggression in Primates</em></p>
<p>Many species of primates engage in some predation, against frogs, lizards, snakes, birds, or monkeys. Almost all use the craniocervical bite, a killing bite to the head or neck of the prey. The exception is the baboon, which often starts to eat before its prey is dead, perhaps because the baboon’s size and strength allow it to immobilize prey even without immediately killing it.[30]</p>
<p><em>Predatory Aggression in Rats</em></p>
<p>Rats often kill and eat frogs and turtles. Attacks on these animals are probably a better measure of rat predatory aggression than mouse-killing, even though rats do often eat mice as well; mouse-killing seems stimulated by some of the same mechanisms as social aggression and is a less “pure” instance of the class.</p>
<p>Testosterone doesn’t affect predatory aggression in rats.</p>
<p>When male Wistar rats were tested for whether they would kill a frog (<em>Rana pipens</em>) placed in their cage, those who didn’t kill the frog immediately never attacked a frog on subsequent trials. Testosterone injection didn’t induce frog killing. The rats who did kill frogs learned to kill them faster upon repeated trials, but again testosterone injection had no effect on latency.[13]</p>
<p>Testosterone supplementation doesn’t increase frog-killing in female rats either.[15]</p>
<p>Some drugs also reduce predatory aggression in rats.</p>
<p>Amphetamine blocks rats from killing mice, and not just because it reduces appetite; at low doses, rats are still willing to kill mice even though they don’t want to eat them. The same is true for frog-killing.[16]</p>
<p>Delta-9-cannabinol (the main psychoactive ingredient in cannabis) reduces rats’ frequency of attacking turtles.[45]</p>
<p>Some rats attack other rats in ways more akin to predation than social aggression.</p>
<p>In strains of rats with abnormally low glucocorticoid function, the lateral hypothalamus is activated during conflicts with other rats. These low-cortisol rats attack other rats on the head, throat, and belly, without any of the usual preliminaries of signaling aggression. In other words, their aggression against conspecifics looks more like predation. Humans diagnosed with antisocial personality disorder also have lower cortisol levels than average.[33]</p>
<p>Rats subjected to post-weaning social isolation also are abnormally aggressive and prone to attack vulnerable regions without intention signaling, again more like predatory or maternal aggression than typical social aggression.[47]</p>
<p>As with social aggression and maternal aggression, domestication of rats does not reduce predatory aggression. Norway rats bred for low aggression towards humans did not show any decline in predatory behavior.[42]</p>
<p><em>Predatory Aggression in Voles</em></p>
<p>After 13 generations of selecting bank voles for higher rates of predatory behavior, raising the rate of predatory behavior 5x relative to controls, the two highest SNPs found in the predatory lines were in the gene PDE4D, found expressed in the brain. PDE4D is responsible for degrading cAMP. PDE4D inhibitors have antidepressant effects.[46]</p>
<p><strong>Mobbing</strong></p>
<p>Mobbing refers to behaviors by groups of prey animals to approach, intently observe, harass, and attack a predator or other large member of another species. Mobbing is common in primates, particularly New World monkeys.</p>
<p>Baboons, geladas, and chimpanzees launch aggressive counterattacks that can seriously wound predators; e.g. baboons often kill leopards. Arboreal New World monkeys like tamarins and capuchins, by contrast, tend to lunge, jump, and make stereotyped threat behaviors when a predator (such as a snake) has captured one of them. Where mobbing does not pose a lethal threat to the predator, it may be an attempt to get the predator to move on, as well as monitoring the threat. But capuchins also mob non-threatening, non-prey animals, and the reason why is unknown.[31]</p>
<p><strong>Parallels to Human Aggression</strong></p>
<p>The criminology literature tends to make a single distinction in types of aggression – “reactive” aggression, a spontaneous, “hair-trigger” loss of self-control in response to frustration or provocation, or “predatory” aggression, a deliberate behavior engaged in to achieve a desired goal. Acts of “reactive” aggression are done under stress; acts of “predatory” aggression are done calmly and strategically, and may even be enjoyable. The analogy between “predatory” aggression in humans and literal predation in animals is loose, and based primarily on the fact that both involve low cortisol and are not associated with strong negative emotions.</p>
<p>“Reactive” aggression in this criminology paradigm would seem to correspond either with “defensive” or “social” aggression – they’re not clearly delineated.</p>
<p>Children with a history of aggressive behavior have been observed to cluster into two types. One type of child engages only in “impulsive” or “reactive” aggression. A second type of child engages both in this “impulsive” aggression and in “premeditated”/ “pro-active” aggression.</p>
<p>Children in the “impulsive” group were more likely to have low IQs and schizophrenia diagnoses; children in the “mixed” group were more likely to have a history of drug abuse. [12]</p>
<p>In studies of juvenile offenders, “premeditated”/”instrumental” aggression was reported to be a better predictor of future criminality than “reactive” aggression.[12]</p>
<p>In studies of men who battered their wives, some men’s heart rate rises during marital conflict, and some men’s heart rate lowers. The low-heart-rate group was more likely to have a history of violence outside the marriage, more likely to have a drug dependence, and more likely to have antisocial and aggressive-sadistic characteristics.[12]</p>
<p>Human hunter-gatherers rarely engage in spontaneous “reactive” aggression, while chimpanzees and bonobos engage in conflict three orders of magnitude more often. An unusually high-violence group of Australian aborigines, plagued by poverty and alcoholism, was observed by ethnographers to engage in violence 0.005 times per 100 hours per individual, compared to 1-3 times per 100 hours per individual for chimpanzees and bonobos. In other words, human hunter-gatherers spend at least 1000x less time than apes in violent squabbles with members of their community.[32]</p>
<p>On the other hand, human hunter-gatherers engage in hostile raids and ambushes that are deadlier than anything other primates do. Compared to our nearest primate neighbors, we have extremely low rates of reactive aggression and extremely high rates of proactive (premeditated) aggression.[32]</p>
<p>When animals such as dogs are bred for tameness, it is chiefly defensive aggression that is selected against (since we are selecting primarily for lack of violence against humans, who are neither prey nor conspecifics). Hominid facial morphology has changed in the same way as dog facial morphology, and we have developed a longer developmental period, prolonged play, and cooperative communication, similar to the “domestication syndrome” in other animals.</p>
<p>Some hypothesize that have “bred ourselves” for tameness starting about 200,000 years ago, perhaps through capital punishment of reactively-aggressive, antisocial individuals. Capital punishment appears to be a human universal, and in hunter-gatherer societies it is typically antisocial males with a history of selfish violence who are executed. Capital punishment itself, of course, is an example of <em>proactive</em> aggression – carefully planned and calmly premeditated.[32]</p>
<p>Chimpanzees have a lower death rate from intergroup aggression than human subsistence farmers, but comparable to human subsistence hunter-gatherers, based on 33 human groups from around the world.[99]</p>
<p><strong>Generalizations & Speculations</strong></p>
<p>Defensive aggression is pretty clearly a response to fear and pain, which belongs in the same category with other behaviors like fleeing, hiding, freezing, cowering (protecting vulnerable body parts), and fawning (submission signals.) It is an <em>agitated, reactive, and non-strategic</em> form of aggression, as you can see from the fact that it is relatively ineffective at harming the opponent, and that often an animal in pain will “take its frustration out on” any nearby animals or inanimate objects, regardless of whether they caused the pain. Human experiences like frustration, irritability, or “defensiveness” are probably manifestations of defensive aggression.</p>
<p>Translating social aggression into the human realm is more complicated. It seems clearly related to testosterone, competition, and status conflict, as well as protecting valuable resources (like territory, food, or mates), all of which of course humans do. But it’s unclear to me what the <em>subjective feeling</em> is that corresponds with social aggression. Even valence is unclear – is engaging in social aggression pleasant or unpleasant for animals?</p>
<p>The lateral hypothalamus is generally considered a pleasure center (or at least a “reward-seeking” center), and stimulating it makes rhesus monkeys much more socially aggressive, suggesting that they are in a “seeking”, eager mood when they start fights; the amygdala is associated with fear, and amygdalectomized monkeys are passive and placid and never fight back. So, at least, social aggression is associated with energetic, urgent feelings, but it seems to be a mix or an ambiguous relationship between fear and pleasure-seeking.</p>
<p>Maternal aggression is very clearly associated with <em>fearlessness</em> and the <em>absence of stress</em>. It is a calm, non-agitated, deadly type of aggression. It’s not otherwise clear to me what it “feels like from the inside”, though, or what situations (if any) apart from defending young children it would arise in.</p>
<p>Predatory aggression has a very consistent psychological profile – it’s alert, calm, focused, and eager. It is a strategic and goal-directed kind of aggression, very effective at killing. In humans, it probably shows up during literal hunting (we are a predatory species after all), as well as in strategic types of conflict such as warfare. It seems to have a lot in common with the “flow state” of enjoyable, focused, trance-like absorption in a stimulating activity, which humans also engage in through nonviolent activities such as games and skilled work.</p>
<p>Animal domestication selectively breeds animals for reduced defensive aggression, while preserving other types of aggression (social, maternal, and predatory.) Tame animals are less fearful and skittish around new objects and surprising encounters, less likely to either flee or fight out of fear or irritation.</p>
<p>Human evolution, our own “domestication”, probably did the same thing; we have drastically fewer impulsive, irritable violent reactions to our neighbors than other primates, but probably equal motivation for defending our children and competing for social status, and <em>greater</em> skill than any of our primate relatives in forms of organized violence such as hunting and warfare.</p>
<p>Among contemporary humans, showing frustration is viewed as a sign of weakness, but being calmly dangerous can earn respect. We admire predatory (and social) aggression, but disdain defensive aggression.</p>
<p>As far as hormones go, serotonin seems to clearly correlate with what might be termed “contentment” or “satiety.” It reduces motivation to hunt and to engage in social aggression, reliably across animals. High serotonin levels correlate with and even cause dominant social rank; the very most dominant individuals in a hierarchy are typically <em>less</em> violent, or less severely violent, than the mid-rank individuals, presumably because they’re so high status they don’t have to fight much.</p>
<p>Testosterone seems to increase motivation to engage in <em>both</em> social aggression and social submission, while progesterone inhibits both aggression and submission. This is contrary to the stereotype of submission as “unmanly”.</p>
<p>Perhaps testosterone increases motivation to engage in <em>all</em> social-status-related activities, both fighting and submission, while serotonin has a somewhat independent effect, such that low serotonin increases aggression but not submission.</p>
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<p>[111]Ginsburg, Harvey J., Steve A. Norris, and Gail Hudson. “Delta-9-tetrahydrocannabinol affects consummatory but not appetitive sequence of interspecific aggression in the Mongolian gerbil (Meriones unguiculatus).” <em>Bulletin of the Psychonomic Society</em> 10.5 (1977): 361-363.</p>
<p>[112]Creel, Scott, David E. Wildt, and Steven L. Monfort. “Aggression, reproduction, and androgens in wild dwarf mongooses: a test of the challenge hypothesis.” <em>The American Naturalist</em> 141.5 (1993): 816-825.</p>
<p>[113]Winslow, James T., et al. “A role for central vasopressin in pair bonding in monogamous prairie voles.” <em>Nature</em> 365.6446 (1993): 545-548.</p>
<p>[114]Winslow, James T., et al. “A role for central vasopressin in pair bonding in monogamous prairie voles.” <em>Nature</em> 365.6446 (1993): 545-548.</p>
<p>[115]Demas, Gregory E., et al. “Castration does not inhibit aggressive behavior in adult male prairie voles (Microtus ochrogaster).” <em>Physiology & Behavior</em> 66.1 (1999): 59-62.</p>
<p>[116]Bertoglio, Leandro José, Valquiria Camin de Bortoli, and Hélio Zangrossi Jr. “Cholecystokinin-2 receptors modulate freezing and escape behaviors evoked by the electrical stimulation of the rat dorsolateral periaqueductal gray.” <em>Brain research</em> 1156 (2007): 133-138.</p>
<p>[117]Naganuma, Fumito, et al. “Histamine N-methyltransferase regulates aggression and the sleep-wake cycle.” <em>Scientific reports</em> 7.1 (2017): 1-9.</p>
<p>[118]De Felipe, Carmen, et al. “Altered nociception, analgesia and aggression in mice lacking the receptor for substance P.” <em>Nature</em> 392.6674 (1998): 394-397.</p>IntroductionChronic Mania and Persistent Euphoric States2020-07-29T00:00:00+00:002020-07-29T00:00:00+00:00https://srconstantin.github.io/2020/07/29/chronic-mania<p>Can a human be happy all the time?</p>
<p>Let me clarify; I don’t mean “happiness” in any kind of complex sense. I don’t mean wellbeing or eudaimonia or life satisfaction or anything like that. I mean <em>being in a good mood</em> – better than good, “high”, bubbly, enthusiastic.</p>
<p>In the psychiatry literature they call this state “euphoria” or “elation.” It can be produced by recreational drugs, or by placing electrodes in some locations in the brain, or by some brain injuries, or by neurological or psychiatric disorders. It is common in manic and hypomanic episodes. And, of course, it is a normal mood that healthy sober people can enter as well.</p>
<p>But most euphoric states are transient, and most ways to deliberately induce euphoria don’t work. Morphine, for instance, can produce euphoria, but not continuously for months at a time; you develop tolerance for the drug until the euphoria-producing dose and the fatal dose intersect. And people who have a stroke of good fortune like <a href="https://en.wikipedia.org/wiki/Hedonic_treadmill#Happiness_set_point">winning the lottery</a> don’t stay euphoric forever – they initially feel great but then <em>adapt</em> to their changed circumstances.</p>
<p>So, you might ask, is there some kind of negative feedback loop in the brain such that euphoria is <em>always</em> temporary? Is it literally impossible to feel awesome all the time, for months or years at a stretch?</p>
<p>Turns out the answer is no.</p>
<p>There is something called chronic mania, which is just what it sounds like: a manic state, including euphoria/elation, which lasts for over 6 months, sometimes forever.</p>
<p>The nineteenth-century psychiatrist Emil Kraepelin was the first to give a clinical description of chronic mania, though some modern neurologists think that today those patients would be diagnosed with frontotemporal dementia[1], and in his day, chronic mania was the second most common reason for a patient to be committed to a mental hospital.[2]</p>
<p>Apart from the length of their episodes, chronic mania patients differ from bipolar patients in a few systematic ways. Chronic mania generally doesn’t alternate with depression, and is more likely than bipolar mania to come with an “elated mood.” Chronic mania, compared to bipolar mania, is more likely to come with delusions, especially delusions of grandeur, while bipolar mania is more likely to come with symptoms of psychomotor agitation like tension, pressured speech, loss of sleep, and elevated sex drive.[2] Chronic mania is more likely to begin after age 40.[3]</p>
<p>The typical pattern, from case studies, seems to be of a person who may have had transient manic episodes in the past, “settling into” a chronic manic state where they are generally euphoric but out of touch with reality, engaging in reckless, inappropriate, or obnoxious behavior, until they come to the attention of psychiatrists when neighbors or relatives bring them to the hospital.</p>
<p><strong>Case Studies</strong></p>
<p>Kraepelin commented on the behavioral disinhibition and poor impulse control of chronic mania patients:</p>
<p>“Only the coarser enjoyments, eating, drinking, smoking, snuffing, still arouse in them vivid feelings, further the satisfaction of their personal wishes and wants…[they] talk more than their share, swagger, try to gain for themselves all possible little advantage.”[1]</p>
<p>He also notes that they engage in hoarding behavior:</p>
<p>“They collect all possible rubbish in their pockets, make a mess with it all round about, rub and wipe things, adorn themselves with rags and scraps of ribbon.”[1]</p>
<p>Frederic Wertham, a psychiatrist writing in 1929, described cases of chronic mania that fit the overall pattern.[4] In all seven cases, the chronic mania began after age 30 (later than the typical onset of bipolar disorder), and in all cases it lasted several years. In several cases, the patients had previously had briefer manic episodes.</p>
<p>Wertham describes traits such as “pressure of activity, great sociability, lack of fatigue, good humor”, “noisiness and talkativeness”, “buoyant” and “elated” moods, “wild schemes” and delusions (of unrealistic business deals, religious revelations, million-dollar inheritances), “joviality and playfulness with jokes and laughing”, “vulgar and profane” language and sexual advances towards nurses.</p>
<p>Like Kraepelin’s patients, one of Wertham’s patients collects useless items and decorates herself – she “wore flowers in her hair and bits of colored wool tied to her buttons…continued decorating herself with little objects.”</p>
<p>Wertham notes some patterns: chronic mania patients tend to be middle-aged at onset, tend to have highly sociable and active personalities even before their illness, have no sign of cognitive decline (as you’d expect in dementia), and tend to be heavyset.</p>
<p>Similar features show up in more recent case studies of chronic mania: older age, hoarding, delusions, disinhibited behavior.</p>
<p>One 68-year-old woman[5] had been in an “elevated mood” state for 30 years, during which she increasingly hoarded objects and lived in increasing squalor, refusing all help. She had no sign of dementia or memory loss when tested, and no history of drug abuse. Prior to her illness she had had one depressive episode after the death of her husband, and before that she had been a “rather jovial schoolmistress” – like Wertham’s patients, her baseline personality was cheerful. She recovered after treatment with lithium.</p>
<p>A 65-year-old Indian man had been manic for 48 years,[6] with the onset beginning after a fever at age 12. He was “cheerful, optimistic, talkative, outgoing, and overly confident,” and became involved in politics with some success. But he also engaged in reckless behavior, traveling by train across India without paying his fare, stealing objects and giving them away to the poor. He “would often describe himself as a messenger of God with special powers, stating God had created him for the welfare of poor people”. He couldn’t hold down a job and he was divorced twice, but his mood was “persistently cheerful or irritable.” He was eventually hospitalized due to complaints by neighbors and relatives, and recovered after a temporary course of treatment with antipsychotics.</p>
<p>A 33-year-old woman who had been manic for 17 years[7] “expressed grandiose beliefs and evidenced a euphoric mood”, and had been unable to keep a job due to her “over-familiar” behavior. She had never abused drugs. “Her parents described her premorbid personality as generally affable, co-operative and creative but occasionally forceful and stubborn.”</p>
<p><strong>Chronic Mania and Brain Damage</strong></p>
<p>A variety of case studies of chronic mania identified a neurological cause.</p>
<p>One young woman who had mania-like symptoms since childhood (behavior problems, restlessness, talkativeness, labile and disinhibited mood, sexually provocative behavior starting at adolescence) was found upon radiological examination to have severe degeneration of the cerebellum.[8]</p>
<p>Another patient, a young man who had been electrocuted by getting entangled with a wire two years previously, developed manic symptoms of grandiose and persecutory delusions, hallucinations, poor judgment, and increased appetite.[9]</p>
<p>A 55-year-old man who had become irritable, extremely sociable, and extravagant with money was found to have an oligodendroglioma, a large brain tumor in the left temporoparietal lobe, and his symptoms improved after surgery.[10]</p>
<p>An eight-year-old child who had been ill with polioencephalomyelitis had a marked personality change – “he started talking excessively, singing songs and dancing. The symptoms became worse once he came home. He started talking with relatives, neighbours and strangers, content of talk was how he would act in a movie, how he would build a big house, that he would marry a beautiful lady, etc. He was singing film songs, was going out of the house and it used to be very difficult to locate and bring him back. His appetite was increased, sleep was disturbed. Majority of the time, he was very happy and cheerful.”[11]</p>
<p>A patient with a stroke damaging the periventricular zone of the hypothalamus was reported to have developed “persistent euphoria”, while in another case of brain surgery on the hypothalamus, “every time the surgeon gently wiped coagulated blood from the ventricle floor the patient burst out laughing, whistled, made jokes, and uttered obscene remarks.”[12]</p>
<p>An 81-year-old woman with a stroke in the right thalamus “became increasingly euphoric and talkative, and had grandiose delusions…believed that her health was better than ever and joked inappropriately. She also reported a decreased need for sleep.” After treatment with a temporary course of antipsychotics, she recovered but was still “mildly euthymic.”[13]</p>
<p>Out of 66 consecutive patients treated for head trauma, 6 (9%) developed mania[14]. The only lesion location significantly associated with mania was the temporal pole (p = 0.0005), which is also one of the first areas damaged in frontotemporal dementia and Alzheimer’s disease.</p>
<p>Compared to patients who developed bipolar disorder after brain injury, patients who developed only mania after brain injury were significantly more likely to have cortical lesions (esp. the orbitofrontal cortex and the right basotemporal cortex.)[15]</p>
<p>Another study found that mania after brain injury was “was associated primarily with orbitofrontal, thatamic, caudate, and basotemporal lesions in the right hemisphere.”[16]</p>
<p>The most common locations of lesions for patients with post-stroke mania (out of 74 cases) are the right frontal lobe and basal ganglia. Out of 16 patients who developed mania after a brain tumor, the tumor was in the frontal lobe, temporal lobe, or subcortical limbic structure in 13 patients, and two patients (12.5%) had chronic mania. [17]</p>
<p>One of the symptoms of multiple sclerosis is reported to be euphoria, or “euphoria sclerotica”, an unusual cheerfulness, optimism, and lack of awareness of their physical disability.</p>
<p>In a study of 44 MS patients and 22 healthy controls, 13% of MS patients had euphoria and 13% had disinhibition while no control subjects had either. There was a significant (p < 0.01) correlation between the degree of euphoria in the MS patients and the severity of frontotemporal degeneration observable on an MRI. [18]</p>
<p>Charcot’s original definition of multiple sclerosis in 1873 described “foolish laughter without cause” as one of the symptoms; Brown and Davis, in their survey of 100 cases in 1926, reported 63% of patients were euphoric. In an 1986 study of 76 MS patients, 48% were found to be euphoric, and the euphoric patients were more likely than the non-euphoric ones to have a progressive course of disease, to have brain involvement, and to have more severe physical & functional disability.[19]</p>
<p>Brain damage can cause mania, including chronic mania, in patients with no psychiatric history, particularly damage to the frontal and temporal lobes. Damage to other locations such as the cerebellum, thalamus, and hypothalamus can also cause mania. There also seems to be a tendency for mania to be more common as a result of damage to the right brain hemisphere.</p>
<p>The frontal and temporal lobes are involved in self-restraint and appropriate behavior, so it’s not surprising that damage to them should cause some of the disinhibitory and compulsive aspects of mania. Apparently, brain damage can also cause persistently euphoric states.</p>
<p><strong>Conclusions</strong></p>
<p>I think we can safely say that it <em>is</em> possible for humans to remain in a euphoric state, continuously for months or years on end. (Often in these case studies the euphoria is punctuated by irritability, but <em>not</em> sadness or depressed mood.)</p>
<p>Now, most of the examples we know of these prolonged euphoric states are undesirable. They often come with reckless or harmful behavior, delusions, and cognitive impairment.</p>
<p>They’re also unpredictable – some but not all people who get strokes, tumors, or injuries to these brain areas will become manic or otherwise euphoric.</p>
<p>But the existence of persistent euphoric states suggests that it could be in principle possible to deliberately induce a long-lasting elevated mood without some of the problematic side effects.</p>
<p>It’s a common finding that deep brain stimulation of the nucleus accumbens or subthalamic nucleus can cause transient feelings of euphoria, and sometimes outright manic episodes.[21][22][23][24][25][26][27][28] However, there is a tolerance effect here – with continuous stimulation for a year, the same stimulus that initially caused euphoria produced no perceivable effect at 12 months.[29] It’s not impossible that some variant on this type of electrical stimulation could produce long-term euphoria, though, at a deliberately tuned dose (since higher voltages cause stronger mood effects). So I’m intrigued by the prospects of developing a form of “<a href="https://qualiacomputing.com/2016/08/20/wireheading_done_right/">wireheading done right</a>.”</p>
<p><strong>References</strong></p>
<p>[1]Gambogi, Leandro Boson, et al. “Kraepelin’s description of chronic mania: a clinical picture that meets the behavioral variant frontotemporal dementia phenotype.” <em>Arquivos de neuro-psiquiatria</em> 74.9 (2016): 775-777.</p>
<p>[2]Perugi, Giulio, et al. “Chronic mania.” <em>The British journal of psychiatry</em> 173.6 (1998): 514-518.</p>
<p>[3]Cameron, Kenneth. “Chronic mania.” <em>Journal of Mental Science</em> 82.340 (1936): 592-594.</p>
<p>[4]Wertham, F. I. “A group of benign chronic psychoses: prolonged manic excitements: with a statistical study of age, duration and frequency in 2000 manic attacks.” <em>American Journal of Psychiatry</em> 86.1 (1929): 17-78.</p>
<p>[5]Fond, G., F. Jollant, and M. Abbar. “The need to consider mood disorders, and especially chronic mania, in cases of Diogenes syndrome (squalor syndrome).” <em>International psychogeriatrics</em> 23.3 (2011): 505.</p>
<p>[6]Mendhekar, D. N., et al. “Chronic but not resistant mania: a case report.” <em>Acta Psychiatrica Scandinavica</em> 109.2 (2004): 147-149.</p>
<p>[7]Malhi, G. S., P. B. Mitchell, and G. B. Parker. “Rediscovering chronic mania.” <em>Acta Psychiatrica Scandinavica</em> 104.2 (2001): 153-156.</p>
<p>[8]Cutting, J. C. “Chronic mania in childhood: case report of a possible association with a radiological picture of cerebellar disease.” <em>Psychological medicine</em> 6.4 (1977): 635-642.</p>
<p>[9]Ameen, Shahul, Siddhartha Dutta, and Vinod Kumar Sinha. “Electroencephalogram changes and its improvement with sodium valproate in a patient with electrocution-induced chronic mania.” <em>Bipolar disorders</em> 5.3 (2003): 228-229.</p>
<p>[10]Rahul, S. A. H. A., and Kiran Jakhar. “Oligodendroglioma presenting as chronic mania.” <em>Shanghai archives of psychiatry</em> 27.3 (2015): 183.</p>
<p>[11]Subrahmanya, B., and Shivaprakash HS Narayana. “CHRONIC MANIA FOLLOWING POLIOENCEPHALOMYELITIS—A CASE REPORT.” <em>Indian journal of psychiatry</em> 23.3 (1981): 266.</p>
<p>[12]Barbosa, Daniel AN, et al. “The hypothalamus at the crossroads of psychopathology and neurosurgery.” <em>Neurosurgical focus</em> 43.3 (2017): E15.</p>
<p>[13]Kulisevsky, Jaime, Marcelo L. Berthier, and Jesús Pujol. “Hemiballismus and secondary mania following a right thalamic infarction.” <em>Neurology</em> 43.7 (1993): 1422-1422.</p>
<p>[14]Jorge, Ricardo E., et al. “Secondary mania following traumatic brain injury.” <em>American Journal of Psychiatry</em> 150 (1993): 916-916.</p>
<p>[15]Starkstein, Sergio E., et al. “Manic-depressive and pure manic states after brain lesions.” <em>Biological Psychiatry</em> 29.2 (1991): 149-158.</p>
<p>[16]Robinson, Robert G., et al. “Comparison of mania and depression after brain injury: causal factors.” <em>Am J Psychiatry</em> 145.2 (1988): 172-178.</p>
<p>[17]Satzer, David, and David J. Bond. “Mania secondary to focal brain lesions: implications for understanding the functional neuroanatomy of bipolar disorder.” <em>Bipolar Disorders</em> 18.3 (2016): 205-220.</p>
<p>[18]Diaz-Olavarrieta, Claudia, et al. “Neuropsychiatric manifestations of multiple sclerosis.” <em>The Journal of neuropsychiatry and clinical neurosciences</em> 11.1 (1999): 51-57.</p>
<p>[19]Rabins, PETER V. “Euphoria in multiple sclerosis.” <em>Neurobehavioral aspects of multiple sclerosis</em> (1990): 180-185.</p>
<p>[20]Mosley, Philip E., et al. “Persistence of mania after cessation of stimulation following subthalamic deep brain stimulation.” <em>The Journal of neuropsychiatry and clinical neurosciences</em> 30.3 (2018): 246-249.</p>
<p>[21]Synofzik, Matthis, Thomas E. Schlaepfer, and Joseph J. Fins. “How happy is too happy? Euphoria, neuroethics, and deep brain stimulation of the nucleus accumbens.” <em>AJOB Neuroscience</em> 3.1 (2012): 30-36</p>
<p>[22]Haq, Ihtsham U., et al. “Smile and laughter induction and intraoperative predictors of response to deep brain stimulation for obsessive-compulsive disorder.” <em>Neuroimage</em> 54 (2011): S247-S255.</p>
<p>[23]Anderson, Karen E., and Jake Mullins. “Behavioral changes associated with deep brain stimulation surgery for Parkinson’s disease.” <em>Current neurology and neuroscience reports</em> 3.4 (2003): 306-313.</p>
<p>[24]Greenberg, Benjamin D., et al. “Three-year outcomes in deep brain stimulation for highly resistant obsessive–compulsive disorder.” <em>Neuropsychopharmacology</em> 31.11 (2006): 2384-239</p>
<p>[25]Kuhn, Jens, et al. “Transient Manic‐like Episode Following Bilateral Deep Brain Stimulation of the Nucleus Accumbens and the Internal Capsule in a Patient With Tourette Syndrome.” <em>Neuromodulation: Technology at the Neural Interface</em> 11.2 (2008): 128-131.</p>
<p>[26]Mosley, Philip E., et al. “Persistence of mania after cessation of stimulation following subthalamic deep brain stimulation.” _The Journal of neuropsychiatry and clinical neurosciences _30.3</p>
<p>[27]Chopra, Amit, et al. “Voltage-dependent mania after subthalamic nucleus deep brain stimulation in Parkinson’s disease: a case report.” <em>Biological psychiatry</em> 70.2 (2011): e5-e7.</p>
<p>[28]Tsai, Hsin-Chi, et al. “Hypomania following bilateral ventral capsule stimulation in a patient with refractory obsessive-compulsive disorder.” <em>Biological psychiatry</em> 68.2 (2010): e7-e8.</p>
<p>[29]Springer, Utaka S., et al. “Long-term habituation of the smile response with deep brain stimulation.” <em>Neurocase</em> 12.3 (2006): 191-196.</p>Can a human be happy all the time?COVID-19 Vaccine Update2020-07-24T00:00:00+00:002020-07-24T00:00:00+00:00https://srconstantin.github.io/2020/07/24/COVID-19-vaccine-update<p>So far I’ve found 6 vaccine candidates that are reporting positive results from clinical trials.</p>
<p>Moderna [1] has been testing an mRNA vaccine called mRNA-1273, consisting of the RNA encoding a portion of the COVID-19 virus’s spike protein, wrapped in a lipid nanoparticle. Their Phase 1 study on 45 healthy adults aged 18-55 found that there was a dose-dependent antibody response (relative to baseline) lasting until the end of the 60-day study, and that all participants’ antibodies were able to neutralize at least 80% of the COVID-19 virus in vitro. The antibodies were as effective at neutralizing virus as those in convalescent plasma from patients who had recovered.</p>
<p>AstraZeneca [2] in collaboration with researchers from Oxford University, has been testing a vaccine called ChAdOx1, and has released interim results from a Phase 1 / 2 study on 1077 healthy adults aged 18-55. This vaccine is an adenovirus vector expressing the spike protein of the COVID-19 virus. The trial found that the antibody levels were higher in vaccinated subjects than controls, with a comparable magnitude of antibody response to convalescent plasma, and with the elevated response lasting throughout the 60-day trial. Of the 35 vaccinated patients tested for a neutralizing response, all were able to neutralized COVID-19, while none of the control patients were.</p>
<p>A Chinese group [3] also tested a vaccine consisting of an adenovirus vector expressing a part of the COVID-19 virus’ spike protein, on 508 adults aged 18-60. The vaccinated subjects had significantly more antibody response and neutralizing ability than the placebo group. 96-97% of vaccinated subjects had antibodies against spike protein; 59% had neutralizing antibodies. The vaccine also produced significantly more T-cell response than placebo.</p>
<p>A German company, BioNTek, produced another vaccine candidate based on mRNA of a portion of the spike protein, this one attached to a “foldon” peptide to improve immunogenicity. In an un-peer-reviewed preprint [4] they report an uncontrolled trial on 60 healthy adults age 18-55. Their average antibody response to the virus was significantly higher and more effective at neutralizing COVID-19 than the antibodies in convalescent plasma.</p>
<p>Two other biotech companies, Sinovac [5] and Inovio [6], have announced in press releases that their initial human vaccine trials had positive results; Sinovac claims 90% of its vaccinated subjects had neutralizing antibodies and Inovio claims 94% of its vaccinated subjects had an antibody response to the vaccine. Neither company has released a paper or additional data.</p>
<p>Ok, so what does this mean?</p>
<p>Looking for antibody response is a pretty standard way to test vaccines. The purpose of a vaccine is to stimulate the immune system to produce antibodies (and potentially other responses) to the virus, so that when you get the actual virus you’ll be able to produce the right antibodies faster, in greater quantities, and for a greater length of time. So, given that experimental ethics rules make it hard to actually <em>infect</em> people with the virus and seeing if the vaccine protects them, researchers usually use antibody response as a proxy.</p>
<p>Do the vaccinated subjects <em>produce</em> antibodies that actually bind to the viral antigen? How much do they produce? And do those antibodies <em>neutralize</em> the virus, i.e. prevent it from spreading in a petri dish full of cells?</p>
<p>Like all proxy metrics, antibody response is not a perfect substitute for finding out what happens in a real world scenario – in this case, how well the vaccine will protect against infection. But I think it’s a reasonable proxy to use.</p>
<p>The base rates of vaccines that enter clinical trials ultimately getting approved by the FDA are actually not bad – quite a bit higher than the clinical success rates of other drugs.</p>
<p>Based on a dataset of clinical trials between 2000 and 2015, [7] it turns out that vaccines for infectious diseases have an overall success rate of 33.7% from Phase I trials to approval; that is, once a vaccine _enters _ clinical trials, it has about a ⅓ chance of being found safe and effective enough to satisfy the FDA. For all drugs and vaccines taken as a whole, that number is more like 1/20.</p>
<p>Another study on a clinical trial database ranging from 1995 to 2017 [8] reached a similar conclusion: a vaccine for infectious disease that enters clinical trials has a 31% chance of ultimately reaching approval.</p>
<p>The riskiest stage in this process is going from phase 2 to phase 3, which is a 61% probability; Moderna has already passed that test, having begun its phase 3 trial, and now, on priors alone, it has an 80% chance of approval.</p>
<p>There’s a more pessimistic number floating around, that says vaccine candidates have only a 6% chance of success, but I don’t think it’s applicable to the current COVID-19 situation. The number comes from a study [9] that looks at the probability that a _preclinical _vaccine candidate will ultimately be approved – that means, candidates that have only been tested on animals so far, which are obviously riskier than candidates that showed positive enough results to start testing in humans. Moreover, that study included vaccines for _noninfectious _diseases in that group, including cancer vaccines, which have a dismal track record.</p>
<p>If we’re thinking about how hopeful to be about COVID-19 vaccine candidates, we shouldn’t be lumping them in with chronic disease “vaccines”, which don’t work the same way and aren’t nearly as effective.</p>
<p>With as many vaccine candidates as are currently in the pipeline, I think chances are quite good that we’re going to see an approval somewhere.</p>
<p>The other big question, though, which _isn’t _going to show up in the clinical success rates, is how well this vaccine is going to work on the elderly.</p>
<p>COVID-19 is deadlier the older you get. Also, because immune system function declines with age, vaccines are less effective the older you get. Flu vaccines are basically ineffective on the old. And you don’t need to prove that a vaccine is effective on the elderly to get it approved.</p>
<p>Both the Moderna and Oxford vaccine teams are enrolling older adults in trials, so we’ll actually find out how well they work soon enough.</p>
<p><strong>References</strong></p>
<p>[1] Jackson, Lisa A., et al. “An mRNA Vaccine against SARS-CoV-2—Preliminary Report.” <em>New England Journal of Medicine</em> (202)</p>
<p>[2]Folegatti, Pedro M. et al. “Safety and immunogenicity of the ChAdOx1 nCoV-19 vaccine against SARS-CoV-2: a preliminary report of a phase 1/2, single-blind, randomised controlled trial” <em>The Lancet</em> (2020)</p>
<p>[3] Zhu, Feng-Cai, et al. “Safety, tolerability, and immunogenicity of a recombinant adenovirus type-5 vectored COVID-19 vaccine: a dose-escalation, open-label, non-randomised, first-in-human trial.” <em>The Lancet</em> (2020).</p>
<p>[4]Sahin, Ugur, et al. “Concurrent human antibody and TH1 type T-cell responses elicited by a COVID-19 RNA vaccine.” <em>medRxiv,</em> 2020</p>
<p>[5] <a href="https://www.clinicaltrialsarena.com/news/sinovac-coronavac-data/">https://www.clinicaltrialsarena.com/news/sinovac-coronavac-data/</a></p>
<p>[6] <a href="https://www.statnews.com/2020/06/30/inovio-claims-positive-results-on-covid-19-vaccine-but-critical-data-are-missing/">https://www.statnews.com/2020/06/30/inovio-claims-positive-results-on-covid-19-vaccine-but-critical-data-are-missing/</a></p>
<p>[7]Wong, Chi Heem, Kien Wei Siah, and Andrew W. Lo. “Estimation of clinical trial success rates and related parameters.” <em>Biostatistics</em> 20.2 (2019): 273-286.</p>
<p>[8]DiMasi, Joseph A., et al. “Development times and approval success rates for drugs to treat infectious diseases.” <em>Clinical Pharmacology & Therapeutics</em> 107.2 (2020): 324-332</p>
<p>[9]Pronker, Esther S., et al. “Risk in vaccine research and development quantified.” <em>PloS one</em> 8.3 (2013): e57755.</p>So far I’ve found 6 vaccine candidates that are reporting positive results from clinical trials.Moving to New York2020-07-20T00:00:00+00:002020-07-20T00:00:00+00:00https://srconstantin.github.io/2020/07/20/moving-to-new-york<p>Well, it’s official – I’m going to start a new position at the R&D department of <a href="https://nanotronics.co/">Nanotronics</a>, a company that does automation and AI for manufacturing process control.</p>
<p>I’m going to be researching new applications for their core technology, a system that uses machine learning to tune parameters along a manufacturing pipeline – or to guide a human worker – to optimize output and quality. I’m really excited about the possibilities here. I’ve known some of the Nanotronics people for a long time, and feel lucky to be working with such brilliant and high-integrity folks.</p>
<p>The new job is in Brooklyn, so that’s where my family & I are going, at the end of the month. I’d love to catch up with New York friends (and make new ones) – outside, of course!</p>
<p>Does this mean Daphnia Labs is dead?</p>
<p>Unfortunately, yes.</p>
<p>To recap, I started a company about a year ago with the goal of building an automated platform for drug screening in invertebrates, with the goal of discovering new life-extending drugs.</p>
<p>I still think that research thesis should be done, but we weren’t able to make it work as a business. We may have been too early; a new model organism <em>and</em> a new technology platform <em>and</em> being in the relatively new and controversial field of longevity means we had some skepticism to overcome. Not to mention we were hit with a global pandemic before we could really get sales off the ground.</p>
<p>I’m disappointed that I couldn’t figure out a way to make Daphnia Labs work, but I’m moving on and excited for what lies ahead.</p>Well, it’s official – I’m going to start a new position at the R&D department of Nanotronics, a company that does automation and AI for manufacturing process control.Dose-Response Effects of Viral Exposure in COVID-192020-06-02T00:00:00+00:002020-06-02T00:00:00+00:00https://srconstantin.github.io/2020/06/02/Dose-Response<p><img src="/images/virus-infection.jpg" alt="virus" /></p>
<p>Does being exposed to a small quantity of SARS-CoV-2 virus result in less severe disease than being exposed to a large quantity?</p>
<p>The answer is relevant to how we should respond to COVID-19.</p>
<p>If high dose exposures are worse than low-dose exposures, then:</p>
<ul>
<li>We should consider people who spend a lot of time with infected people, like healthcare workers and family members of COVID-19 patients, to be more at risk than people who get briefly exposed to the virus
<ul>
<li>Reopening lower-risk public spaces (like outdoor cafes or parks) may be low-risk compared to reopening spaces that involve a lot of close contact (like gyms and nightclubs)</li>
<li>We should prioritize PPE even <em>more</em> for people who regularly interact with COVID-19 patients</li>
</ul>
</li>
<li>Low dose exposure to SARS-CoV-2 may produce immunity without producing serious illness.
<ul>
<li>If low dose exposure is safe and produces immunity, it may be good for people and available faster than a vaccine can be manufactured and approved.</li>
</ul>
</li>
</ul>
<p><strong>Bottom Lines</strong></p>
<p>People who have higher respiratory <em>viral loads</em> are significantly more likely to have severe COVID-19; the same pattern held in both the SARS and MERS coronavirus epidemics. More virus in the body does tend to correspond to more severe disease.</p>
<p>There’s far less data about how different forms of <em>exposure</em> correlate to disease severity, but there are a few studies pointing towards a greater chance of severe COVID-19 from household contacts than from travel, and one study indicates that mask usage increases the probability that a SARS case will be asymptomatic. These constitute weak evidence that larger doses of exposure to human coronaviruses cause more severe disease.</p>
<p>When human volunteers are experimentally exposed to viruses, some viruses cause more severe symptoms at higher doses, while some viruses don’t. None of the relevant studies were on coronaviruses, however.</p>
<p>In <em>animal</em> experimental exposures to virus, higher doses consistently cause more severe symptoms, including in experiments on the coronaviruses SARS, MERS, and PEDV.</p>
<p>The available evidence is highly incomplete, but tends towards the conclusion that lower dose exposure to COVID-19 should result in less severe disease.</p>
<p><strong>Viral Load in COVID-19</strong></p>
<p>Here’s a table of studies that compared viral load in mild and severe COVID-19 patients.</p>
<table>
<tr>
<td><strong>N</strong>
</td>
<td><strong>Mean Viral Load, Mild</strong>
</td>
<td><strong>Mean Viral Load, Severe</strong>
</td>
<td><strong>Significance</strong>
</td>
<td><strong>Location of Sample</strong>
</td>
<td><strong>Context</strong>
</td>
</tr>
<tr>
<td>15
</td>
<td>Ct = 25 (n = 6, range 17-32)
</td>
<td>Ct = 27 (n = 9, range 19-33)
</td>
<td>n.s.
</td>
<td>Nasopharyngeal swab
</td>
<td>Private hospital, Mumbai, India[1]
</td>
</tr>
<tr>
<td>92
</td>
<td>Ct = 28 (n = 62, sigma = 0.5)
</td>
<td>Ct = 25 (n = 30, sigma = 0.5)
</td>
<td>p = 0.017
</td>
<td>Sputum
</td>
<td>Zhejiang, China; severe patients older & with more comorbidities but not different exposure histories. [2]
</td>
</tr>
<tr>
<td>96
</td>
<td>4.1 log copies/mL (n = 22, sigma = 1.4 )
</td>
<td>5.1 log copies/mL (n = 74, sigma = 1.4)
</td>
<td>p = 0.03
</td>
<td>Sputum (no difference between mild & severe pts in serum or stool)
</td>
<td>Zhejiang, China; severe patients more likely to be from Wuhan[3]
</td>
</tr>
<tr>
<td>76
</td>
<td>delta-CT = -1.25 (n = 30, sigma = 5.2)
</td>
<td>delta-CT = 4.48(n = 46, sigma = 3.0)
</td>
<td>p < 0.001
</td>
<td>nasopharyngeal
</td>
<td>Nanchang, China; median time from disease onset = 4 days[4]
</td>
</tr>
<tr>
<td>23
</td>
<td>5 log copies/mL (n = 10, sigma = 2.2)
</td>
<td>6 log copies/mL (n = 13, sigma = 3.0)
</td>
<td>n.s.
</td>
<td>oropharyngeal
</td>
<td>Hong Kong[5]; mild & severe patients had similar duration of illness at admission, age, sex, & comorbidities
</td>
</tr>
<tr>
<td>12
</td>
<td>Ct = 35.2 (n = 10, sigma = 5)
</td>
<td>Ct = 26 (n = 3, sigma = 5.1)
</td>
<td>p = 0.0177
</td>
<td>nasal
</td>
<td>Guangdong, China [6]
</td>
</tr>
<tr>
<td>18
</td>
<td>Ct = 30.9(n = 12, sigma = 5.6)
</td>
<td>Ct = 30.3 (n = 6, sigma = 5.3)
</td>
<td>n.s.
</td>
<td>nasopharyngeal
</td>
<td>Singapore[7]
</td>
</tr>
<tr>
<td>6
</td>
<td>Ct = 39 (n = 2, sigma = 1.2)
</td>
<td>Ct = 39 (n = 4, sigma = 1.1)
</td>
<td>n.s.
</td>
<td>nasopharyngeal
</td>
<td>Chongqing, China; all patients had previously recovered from COVID-19 and had reoccurence of disease.[8]
</td>
</tr>
<tr>
<td>94
</td>
<td>Ct=30 (n = 76, sigma = 5)
</td>
<td>Ct = 30 (n = 18, sigma = 4)
</td>
<td>n.s
</td>
<td>Throat swabs
</td>
<td>Guangzhou, China [9]
</td>
</tr>
<tr>
<td>11
</td>
<td>6.39 log copies/mL (n = 5, sigma = 0.9)
</td>
<td>6.15 log copies/mL (n = 6, sigma = 1.6)
</td>
<td>n.s.
</td>
<td>nasopharyngeal
</td>
<td>Hong Kong [10]; first 11 patients diagnosed with COVID-19
</td>
</tr>
<tr>
<td>5
</td>
<td>6.3 log copies/ 1000 cells (n = 2, sigma = 1.25)
</td>
<td>5.3 log copies/1000 cells (n = 3, sigma = 2.4)
</td>
<td>n.s.
</td>
<td>nasopharyngeal
</td>
<td>France [11]; patients traveling from Wuhan
</td>
</tr>
</table>
<p>Do severe COVID-19 patients have higher viral loads than mild patients?</p>
<p>This is a flawed proxy for the question of initial exposure, since patients are usually not tested for COVID-19 until at least several days after infection. Higher viral load could indicate that the virus replicated faster inside the body, or simply that the patients were later in their course of disease, rather than that the initial exposure was lower.</p>
<p>Still, the correlation between viral load and disease severity is suggestive as to whether there’s a dose-response effect in COVID-19.</p>
<p>Viral load can be measured with Ct, the number of PCR amplification cycles necessary before viral RNA is detectable. Lower Ct numbers mean exponentially more virus. It can also be measured by delta-Ct, the difference between the number of cycles to detection in a control sample (without virus) and the test sample. Finally, it can be measured by the absolute concentration of viral particles per mL. These numbers cannot be directly compared because the sensitivity of RT-PCR equipment varies and isn’t always given in the papers.</p>
<p>For all studies measured in Ct value, mean Ct score is 29.6 for mild cases and 26.1 for severe cases; this is a significant effect, p = 0.0004.</p>
<p>For the 4 studies measured in absolute concentration, mean concentration was 4.7 log copies/mL for mild cases and 5.3 log copies/mL for severe cases, which was not statistically significant, possibly because the sample size was too small.</p>
<p>Also note that the two studies which looked at sputum samples both found significant effects, and sputum samples reliably contain more virus RNA than nasopharyngeal samples. This suggests that viral load in the lungs is more predictive of the amount of lung damage & thus the severity of respiratory illness than viral load in the upper respiratory tract.</p>
<p><em>Severe COVID-19 patients have significantly higher initial viral loads than mild COVID-19 patients.</em></p>
<p><strong>Exposure Effects in COVID-19</strong></p>
<p>Another question we might ask is whether people with extensive exposure to the virus had more severe illness than people with transient or low-dose exposure.</p>
<p>In a study of 36 children with COVID-19, there was no significant difference in disease severity between those who had close contact with a family member with COVID-19 and those who had traveled to an area affected by COVID-19.[12]</p>
<p>In 1663 patients with COVID-19 in Wuhan, China, there was no significant difference in severity between those who did and did not have a family member with the disease or exposure to the Wuhan seafood market, but were significantly (p<0.0001) less likely to have severe disease if they were healthcare workers compared to the general population. On the other hand this may be because healthcare workers are younger (most of the patients were retirees.)[13]</p>
<p>In 568 COVID-19 patients in Wuhan, China, there was a nonsignificant trend (p = 0.06) for severe cases to be more likely to have had household exposure to the virus, while non-severe cases were more likely to have had hospital exposure to the virus.[14]</p>
<p>In another study of 487 patients with COVID-19 in Zhejiang Province, China, patients with severe disease were significantly less likely to have traveled to an affected area (49.0% vs. 65.1%, p = 0.027) but significantly more likely to be part of a family cluster of three or more patients (10.2% vs. 2.5%).[15]</p>
<p>Overall it doesn’t seem that the relationship between disease severity and magnitude of exposure to infected people has been much studied in COVID-19.</p>
<p>However we do have two Chinese studies indicating that severe cases of COVID-19 are more common in those who had frequent long-term exposure to other patients (i.e. sharing a household with many other patients) and less likely in those who have had transient contact with patients (as in travel to an epidemic-affected province.)</p>
<p><strong>Viral Load in Other Human Coronaviruses</strong></p>
<p><em>SARS</em></p>
<p>In 75 SARS patients, there was no difference in the rate of positive viral RNA samples at diagnosis between patients who later developed ARDS and those who did not.[16]</p>
<p>In 133 SARS patients, initial viral load was significantly (p = 0.025) associated with developing ARDS, and with shorter survival time (p = 0.006).[17]</p>
<p>In 12 SARS patients, viral RNA levels were 30x higher in patients who required ICU admission than in those who didn’t (p < 0.005).[18]</p>
<p>In 154 SARS patients, viral load in nasopharyngeal aspirated was associated (p < 0.01) with diarrhea, oxygen desaturation, mechanical ventilation, and death. Death was 54x as likely in patients positive for viral RNA than negative. [19]</p>
<p><em>MERS</em></p>
<p>In 17 MERS patients, viral load was nonsignificantly (p = 0.06) higher in severe than mild cases.[20]</p>
<p>In 21 MERS patients, blood positivity for MERS RNA was associated with much lower survival (p = 0.017) and higher rates of needing mechanical ventilation (p = 0.003). Higher respiratory viral load was not associated with survival.[21]</p>
<p>In 14 MERS patients, viral load was not significantly associated with mortality but plasma and respiratory viral loads were significantly higher in severe than mild cases.[22]</p>
<p>In 102 MERS patients, respiratory viral titers were significantly (p = 0.0087) higher in patients who died than patients who survived.[23]</p>
<p>The evidence seems very consistent that_ higher viral load correlates with more severe and deadly disease_ in both SARS and MERS.</p>
<p><strong>Exposure Effects in Other Human Coronaviruses</strong></p>
<p>Among 80 health care workers in Singapore exposed to SARS, 45 were serologically positive for the virus. Of those 45, healthcare workers were significantly more likely to be asymptomatic (p = 0.025) if they used masks.[24]</p>
<p>During the SARS epidemic in Hong Kong, there was no significant association between the risk of death and any disease source (household, hospital, community-acquired, airplane, or none of the above.)[25]</p>
<p>In 1649 SARS patients in Beijing, contact with a SARS patient prior to illness was not a significant predictor of mortality.[26]</p>
<p>Healthcare workers with confirmed MERS infection were younger, more likely to be female, and less likely to have comorbidities disease than other cases of MERS. They also had significantly (p < 0.001) lower risk of death and higher chance of being asymptomatic.[27]</p>
<p>MERS patients have a higher risk of mortality (HR = 2.9, p= 0.001) from hospital-acquired infections as opposed to other routes of infection such as household contacts or camels; even after adjusting for age and comorbidities.[28]</p>
<p>Healthcare workers may be exposed to larger doses of SARS or MERS, but it doesn’t show up in increased risk of death or severe disease for healthcare workers, possibly because healthcare workers tend to be younger than other patients.</p>
<p>Hospital-acquired MERS infections are more deadly than other sources of infection, but this may be confounded by the fact that patients who are already in hospitals for other reasons tend to be sicker.</p>
<p>The one piece of evidence from SARS and MERS that points to low-dose exposure being safer is that wearing masks is more likely to result in asymptomatic SARS infection than not wearing masks.</p>
<p><strong>Dose-Response Effects in Other Viruses: Human Studies</strong></p>
<p>Humans have been experimentally exposed to viruses (usually with milder effects than SARS or MERS) in a few challenge trials; this can help us ascertain whether there’s a dose-response effect to the quantity of initial viral exposure on the severity of the disease symptoms.</p>
<p><em>Adenovirus Type 4</em></p>
<p>In 16 military recruits, the probability of infection varied with the dose of adenovirus they were exposed to, but the probability of illness did not.[29]</p>
<p><em>Echovirus</em></p>
<p>In 127 adult volunteers inoculated with various doses of ECHO-11 virus, there was a dose-response relationship with infectivity, but dose had no effect on the severity of upper respiratory symptoms in the infected group. On the other hand, high-dose cases were significantly more likely than low-dose cases to have lower respiratory symptoms (cough, sore throat, laryngitis). Prior challenge reduced symptoms upon rechallenge, and more for the high-dose-prior-exposed than the low-dose-prior-exposed group.[30]</p>
<p><em>Influenza</em></p>
<p>Across 36 studies with different doses and strains, there was no association of higher doses of influenza with higher chance of the subjects becoming ill.[31]</p>
<p><em>Norovirus</em></p>
<p>In a study of 57 adults infected with different doses of Norwalk virus, higher doses were associated with significantly (p =0.001) faster time before symptom onset and longer (p = 0.04) duration of illness, as well as a dose-response relationship in probability of infection.[32]</p>
<p><em>Respiratory Synctial Virus</em></p>
<p>In 35 adult volunteers, there was no association between the dose of RSV administered and the viral load or the probability of infection. Symptom severity, however, as well as cytokine levels, correlated closely with viral load, both across patients and within patients over time.[33]</p>
<p>Volunteers infected with low-dose RSV did not develop illness (0/16), while volunteers infected with high-dose RSV did develop colds (6/17). Illness was independent of the amount of viral shedding.[34]</p>
<p>In 36 volunteers infected with high or low dose RSV, higher doses were associated with higher risk of infection but not higher risk of symptomatic illness.[35]</p>
<p><em>Rhinovirus</em></p>
<p>In 155 young adult volunteers infected with different doses of rhinovirus, daily symptom scores were consistently higher in those exposed to higher doses. Higher antibody titers and higher doses of virus were associated with higher rates of infection.[36]</p>
<p><em>Rotavirus</em></p>
<p>In a study of 62 adult volunteers experimentally infected with different doses of rotavirus, there was a dose-response relationship between the concentration of virus and the probability of infection, but there was no relationship between the virus dose and the probability of experiencing symptoms.[37]</p>
<p>Whether higher initial doses of virus correlate with more severe symptoms or higher probability of having symptoms at all, seems to depend on the virus. There is no relationship between dose and symptom severity in human volunteers exposed to adenovirus, influenza, and rotavirus, but there is a relationship in echovirus, rhinovirus, and norovirus, and the results are ambiguous in respiratory synctial virus.</p>
<p>It remains unclear how well any of these observations translate to COVID-19. Unfortunately there were no studies comparing the effect of dose on the symptoms of any of the mild human coronaviruses.</p>
<p><strong>Dose-Response Effects in Other Viruses: Animal Studies</strong></p>
<p><em>Ebola</em></p>
<p>Exposure to 100 plaque-forming units of Ebola virus in the nose was lethal to macaques; but exposure to 10 plaque-forming units caused no clinical symptoms or detectable antibodies or viral RNA.[38]</p>
<p><em>EEV</em></p>
<p>Eastern Equine Encephalitis Virus is lethal in high doses in macaques (6/6 animals died) but less severe in low-dose exposure (2/6 animals died and clinical scores were lower). [39]</p>
<p><em>Herpes</em></p>
<p>Serial dilutions of the baboon herpesvirus HPV2 inoculated into mice showed a dose-response curve with higher doses resulting in higher rates of infection, CNS symptoms, and death.[40]</p>
<p><em>Influenza</em></p>
<p>There was a dose-response relationship between initial inoculation dose, probability of infection, and probability of death, in H5N1 and H7N1 influenza in turkeys, chickens, and ducks.[41]</p>
<p>Probability of infection, probability of clinical signs, and survival time all varied dose-dependently by the inoculation dose of H5N1 in pigeons.[42]</p>
<p>A H0N1 strain of influenza in mice had a dose-response relationship for both infectiousness and mortality; it was more deadly when introduced to the respiratory tract than intranasally.[43]</p>
<p>A PR8 strain of influenza has a dose-response relationship with serum viral load, weight loss, clinical score, and mortality. The low dose and high dose groups had similar antibody and leukocyte recruitment levels as the high dose, but no mortality. [44]</p>
<p><em>MERS</em></p>
<p>In transgenic mice, there was a dose-response effect in lethality for exposure to MERS virus: it killed 50% of the mice at a dose of 10 TCID50, compared to 25% at 1.25 TCID50 and 100% at 100 TCID50.[45]</p>
<p><em>PEDV</em></p>
<p>PEDV is a coronavirus that causes diarrhea in pigs. It has a dose-response relationship to symptoms: 0.056 TCID50 caused diarrhea in 25% of piglets while 0.56 TCID50 and higher caused diarrhea in 100% of piglets.[46]</p>
<p><em>SARS</em></p>
<p>Both mice and guinea pigs exposed to SARS virus had a higher probability of increased rectal temperature at higher doses of virus exposure. For guinea pigs, ID50 = 5.47 log CPE50, or 50% of guinea pigs were infected at 5.47 * log (the dose at which 50% of cells died).[47]</p>
<p><em>SIV</em></p>
<p>Simian immunodeficiency virus, closely related to HIV, had a dose-response relationship with the probability of infection in macaque monkeys, but steady-state (2-week) viral load among those infected did not correlate with initial dose. There was no correlation between survival time and dose.[48]</p>
<p>Low-dose challenge with SIV successfully produced “silent infection” (no symptoms or viral RNA but virus-specific T cell proliferation.) However, when these monkeys were exposed to a high dose of SIV, they were not immune but became infected and developed AIDS-like disease at the same rate as naive monkeys.[49]</p>
<p>Dose-response relationships between virus inoculum and infection rate or death seem to be common in animal studies, and consistently, including in coronaviruses, higher doses cause more severe symptoms.</p>
<p>However, in at least one case (SIV) a dose of virus that was low enough to produce asymptomatic infection did <em>not</em> produce immunity to future exposures, so we can’t assume that low-dose exposure always brings immunity.</p>
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