Why is the prompt “let’s think step by step” so effective? Andrej Karpathy suggests “models need tokens to think”: since each token requires a similar amount of compute, harder problems require longer reasoning traces. More generally, prompts can (hackishly) approximate a kind of System 2 reflection. An interesting framework for interpreting recent innovations like tree of thoughts.
Certain academics (e.g., Yann LeCun) like to focus on architecture design. But the scaling hypothesis predicts AGI will come simply with more data and compute. “OpenAI, lacking anything like DeepMind’s resources, is making a startup-like bet that they know an important truth which is a secret: the scaling hypothesis is true!” That’s why they got there first: the courage of their convictions.
We have no moat: an interesting (albeit controversial) discussion of open-source vs closed-source AI development.
Emergence. A tabulation of 137 emergent abilities in LLMs. An explainer, “Somewhat mysteriously, all of these abilities emerge at a similar scale despite being relatively unrelated.” But see the misaligned evaluation metrics section for an important criticism.
Thomas Schelling described a kidnapper who suddenly gets cold feet. He wants to set his victim free, but is afraid he will go to the police. In return for his freedom, the victim gladly promises not to do so. The problem, however, is that both realize it will no longer be in the victim’s interest to keep this promise once he is free. And so the kidnapper reluctantly concludes that he must kill him.
Schelling suggests the following way out of the dilemma: “If the victim has committed an act whose disclosure could lead to blackmail, he may confess it; if not, he might commit one in the presence of his captor, to create a bond that will ensure his silence.” (Perhaps the victim could allow the kidnapper to photograph him in the process of some unspeakably degrading act.) The blackmailable act serves here as a commitment device, something that provides the victim with an incentive to keep his promise. Keeping it will still be unpleasant for him once he is freed; but clearly less so than not being able to make a credible promise in the first place.
In everyday economic and social interaction, we repeatedly encounter commitment problems like the one confronting Schelling’s kidnapper and victim. Being known to experience certain emotions enables us to make commitments that would otherwise not be credible. The clear irony here is that this ability, which springs from a failure to pursue self-interest, confers genuine advantages.
Granted, following through on these commitments will always involve avoidable losses not cheating when there is a chance to, retaliating at great cost even after the damage is done, and so on. The problem, however, is that being unable to make credible commitments will often be even more costly. Confronted with the commitment problem, an opportunistic person fares poorly.
Deterrence. Jones has a $200 leather briefcase that Smith cabinets. If Smith steals it, Jones must decide whether to press charges. If he does, he will have to go to court. He will get his briefcase back and Smith will spend 60 days in jail, But the day in court will cost Jones $300 in lost earnings. Since this is more than the briefcase is worth, it is clearly not in his material interest to press charges. (To eliminate an obvious complication, suppose Jones is about to move to a distant city, so deterrence is not a relevant consideration). Thus, if Smith knows that Jones is a rational, self interested person, he is free to steal the briefcase with impunity. Jones may threaten to press charges, but his threat will be empty.
Now suppose that Jones is not a pure rationalist; that if Smith steals the briefcase, Jones will become enraged, and think nothing of a day’s lost earnings, or even a week, in order to see justice done. If Smith knows that Jones will be driven by emotion, not reason, he will let the briefcase be. People expect us to behave rationally in response to theft of property, we will sell them need to behave irrationally in practice, because it is not in their interest to steal it. And predisposed to respond irrationally serves much better here than being guided only by material self interest.
Cheating. Two persons, Smith and Jones, can engage in a potentially profitable venture, say, a restaurant. Their potential for gain arises from the natural advantages inherent in the division and specialization of labor. Smith is a talented cook, but is shy and an incompetent manager. Jones, by contrast, cannot boil an egg, but is charming and has shrewd business judgment. Together, they have the necessary skills to launch a successful venture. Working alone, however, their potential is much more limited. Their problem is this: Each will have opportunities to cheat without possibility of detection. Jones can skim from the cash drawer without Smith’s knowledge. Smith, for his part, can take kickbacks from food suppliers. If only one of them cheats, he does very well. The non-cheater does poorly, but isn’t sure why. His low return is not à reliable sign of having been cheated, since there are many benign explanations why a business might do poorly. If the victim also cheats, he, too, can escape detection, and will do better than by not cheating; but still not nearly so well as if both had been honest. Once the venture is under way, self-interest unambiguously dictates cheating. Yet if both could make a binding commitment not to cheat, they would profit by doing so.
Bargaining. In this example, Smith and Jones again face the opportunity of a profitable joint venture. There is some task that they alone can do, which will net them $1000 total. Jones has no pressing need for extra money, but Smith has important bills to pay. It is a fundamental principle of bargaining theory that the party who needs the transaction least is in the strongest position. The difference in their circumstances thus gives Jones the advantage. Needing the gain less, he can threaten, credibly, to walk away from the transaction unless he gets the lion’s share of the take, say $800. Rather than see the transaction fall through, it will then be in Smith’s interest to capitulate. Smith could have protected his position, however, had he been able to make a binding commitment not to accept less than, say, half of the earnings. One possible way of accomplishing this would be to sign a contract that requires him to contribute $500 to the Republican party in the event he accepts less than $500 from his joint venture with Jones. (Smith is a lifelong Democrat and finds the prospect of such a gift distasteful.) With this contract in place, it would no longer be in his interest to give in to Jones’s threat. (If Smith accepted $200, for example, he would have to make the $500 contribution, which would leave him $300 worse off than if he hadn’t done the job with Jones at all.) Jones’s threat is suddenly stripped of all its power.
Marriage. As a final example of the commitment problem, consider the difficulty confronting a couple who want to marry and raise a family. Each considers the other a suitable mate. But marriage requires substantial investment, which each person fears could be undercut if the other were to leave for an even more attractive opportunity in the future. Without reasonable assurance that this will not happen, neither is willing to make the investments required to make the most of their marriage. They could solve their problem if they could write a detailed marriage contract that would levy substantial penalties on whichever of them attempted to leave. They are, after all, willing to forego potentially attractive opportunities in the future in order to make it in their interests to invest in the present effort of raising a family. It would serve their purposes to take steps now that would alter the incentives they face in the future.
Life, it seems, is rife with commitment problems.
Emotions as Commitment Devices
My claim is that specific emotions act as commitment devices that help resolve these dilemmas.
Retaliation and Deterrence. Consider a person who threatens to retaliate against anyone who harms him. For his threat to deter, others must believe he will carry it out. But if others know that the costs of retaliation are prohibitive, they will realize the threat is empty. Unless, of course, they believe they are dealing with someone who simply likes to retaliate. Such a person may strike back even when it is not in his material interests to do so. But if he is known in advance to have that preference, he is not likely to be tested by aggression in the first place.
Proportionality vs Bargaining. Similarly, a person who is known to “dislike” an unfair bargain can credibly threaten to walk away from one, even when it is in her narrow interest to accept it. By virtue of being known to have this preference she becomes a more effective negotiator.
Guilt vs Cheating. Consider, too, the person who “feels bad” when he cheats. These feelings can accomplish for him what a rational assessment of self-interest cannot–namely, they can cause him to behave honestly even when he knows he could get away with cheating. And if others realize he feels this way, they will seek him as a partner in ventures that require trust.
Love and Marriage. It is no surprise that the marriage problem is better solved by moral sentiments than by awkward formal contracts. The best insurance against a change in future material incentives is a strong bond of love. If ten years from now one partner falls victim to a lasting illness, the other’s material incentives will be to find a new partner. But a deep attachment will render this change in incentives irrelevant. (Indeed, research has shown the “active ingredient” of romantic and non-romantic attachment is derogation of alternatives).
Signaling Your Commitment
Emotions qua commitment devices would not have evolved unless a person can reliably signal possessing them. Consider:
One fall day, almost twenty years ago, black activist Ron Dellums was speaking at a large rally. But at least one young man was not moved by Dellums’s speech. He sat still as a stone on the steps of Sproul Plaza, lost to some drug, his face and eyes empty of expression. Presently a large Irish setter appeared, sniffing his way through the crowd. He moved directly to the young man sitting on the steps and circled him once. He paused, lifted his leg, and, with no apparent malice, soaked the young man’s back. He then set off again into the crowd. The boy barely stirred.
Now, the Irish setter is not a particularly intelligent breed. Yet this one had no difficulty locating the one person in that crowd who would not retaliate for being sprayed. Facial expressions and other aspects of demeanor apparently provide clues to behavior that even dogs can interpret. And although none of us had ever witnessed such a scene before, no one was really surprised when the boy did nothing. Before anything even happened, it was somehow obvious that he was just going to go right on sitting there.
Without doubt, however, the boy’s behavior was unusual. Most of us would have responded angrily, some even violently. Yet we already know that no real advantage inherent in this “normal” response. After all, once the boy’s shirt was soaked, it was already too late to undo the damage. And since he was unlikely ever to encounter that particular dog again, there was little point in trying to teach the dog a lesson. On the contrary, any attempt to do so would have courted the risk of being bitten.
Our young man’s problem was not that he failed to respond angrily, but that he failed to communicate to the dog that he was so predisposed. The vacant expression on his face was somehow all the dog needed to know he was a safe target. Merely by wearing “normal” expressions, the rest of us were spared.
There are numerous behavioral clues to people’s feelings. Posture, the rate of respiration, the pitch and timbre of the voice, perspiration, facial muscle tone and expression, and movement of the eyes, are among the signals we can read. We quickly surmise, for example, that someone with clenched jaws and a purple face is enraged, even when we do not know what, exactly, may have triggered his anger. And we apparently know, even if we cannot articulate, how a forced smile differs from one that is heartfelt. At least partly on the basis of such clues, we form judgments about the emotional makeup of the people with whom we deal. Some people we sense we can trust, but of others we remain forever wary.
A commitment problem is one where maximizing immediate material welfare is maladaptive in the long run.
A commitment device hijacks one’s own reward mechanism towards irrational behavior (insensitive to one’s material welfare).
Many emotions (including guilt, rage, love) and intuitions (including fairness) may be best seen as commitment devices.
A commitment device must be advertised to work effectively: the organism must emit (hard to fake!) signals of their presence.
Across the life course, an organism must choose between somatic investment (growth, learning, maintenance) vs reproductive effort (parenting, alloparenting, mating). But there are also trade-offs within each of these investment categories. For example, within reproductive effort, should I emphasize mating or parenting?
We can reformulate these tradeoffs as current vs future reproduction, and offspring quantity vs quality. Due to sexual selection asymmetries, first trade-off tends to be more salient to females, and the second is more salient to males.
The effect of these tradeoffs can be detected in various life history (LH) traits:
The disposable soma theory posits a causal chain: higher environmental mortality → prioritized reproductive effort → increased senescence. But faster aging also correlates with early puberty (Belsky & Shalev 2016). Perhaps both LH traits respond to the same life-history tradeoff?
If you compare all five life history traits from species-typical traits across all species, they all run together (Jeschke et al 2008).
Fast species show early reproductive maturity and short lives. Semelparous species like salmon undergo “programmed death” immediately after reproduction.
Slow species live longer, and take more time to reach reproductive maturity. For example, iteroparous species like blue whales have extremely slow lifespans.
This is the fast-slow continuum. This is supported by comparative analyses in mammals (Bielby et al. 2007), birds (Saether 1988), reptiles (Bauwens & Diaz-Uriarte 1997), fish (Winemiller & Rose 1992), insects (Johansson 2000) and plants (Salguero-Gómez et al. 2016).
In fact, two components stand out in dimensionality reduction analyses. A fast-slow axis that accounts for 70-80% of the variance in the traits, and a precocial-altricial axis that explains 10-15% of the variance. While smaller species tend to be fast and vice versa, controlling for body size does not make the continuum disappear; rather, the respective variances change to 30-50% and 20-30% (Del Guidice 2020).
As an aside, our species presents a kind of exception to the fast-slow continuum! Human longevity is more “slow” than chimpanzees. But we also have a shorter interbirth interval, a “fast” characteristic. This energetic paradox is explained by a lifting of energetic constraints (somatic vs reproductive effort – why not both?). It was funded by an increase in human basal metabolic rate (Pontzer et al 2016); this expanded energy budget funded both increased reproductive output (some ~100 kcal per day) and somatic costs (larger brains, longer lifespans, etc).
Explaining The Continuum
The fast-slow continuum is a reliable empirical pattern. Why does it exist? What causes these interspecies differences in the pace of life (POL)?
In the 1970s, three US ecologists proposed the r/K theory of life history, which strove to explain it by appealing to population density and carrying capacity of the environment. But by the 1980s it was clear that carrying capacity could not explain the continuum.
Three theoretical approaches stand out:
Modern density dependent models (e.g., Engen & Sæther 2016) do away with carrying capacity, but extend classical r/K density concepts.
Allometric models (e.g., the metabolic theory of ecology in Brown et al 2004) can explain body size covarying with life history; but struggle to predict the continuum’s persistence after body size is partialed out.
Other models invoke extrinsic mortality (risk beyond an individual’s control). Extrinsic mortality affects LH traits only through modifying the intensity of competition: higher extrinsic mortality reduces the intensity of competition and vice versa (Andre & Rousset 2020).
But I haven’t yet encountered a “theory of everything” that integrates across these perspectives. Data in quantitative ecology tends to be rather sparse, making generalizations difficult.
Personality & Plasticity
Let’s talk about animal personality. Numerous studies have found that some individuals are consistently bolder (Wilson et al 1994) or more aggressive (Johnson & Sih 2007) than others across multiple situations, and indeed that boldness and aggressiveness are often positively correlated (Bell & Sih 2007). Such behavioral syndromes have been seen in a wide range of taxa (Gosling 2001).
Why should animals have a personality as opposed to being completely flexible? Why are human personalities so pervasive that when someone is a behavioral chameleon, we often view them as psychopathic?
Behavior could be, in principle, completely flexible (i.e, an animal could be highly aggressive one moment, and then cautious shortly thereafter). But if optimal behavior is connected to a slow-changing state variable, then adaptive behavior should also be consistent over long periods. A few examples from Sih (2011):
Personality is thought to emerge from feedback loops between state and behavior (Sih et al 2015). Negative feedback tends to remove individual differences; positive feedback tends to accentuate them. A few more examples:
Individual differences are often grounded in genetics. For example, twin studies models suggest that 50-80% of the variance from pubertal onset is genetic (Rowe 2002). But the above data suggests a role for environmental influence. We must therefore model organism plasticity, or conditional adaptations in response to environmental conditions.
The Pace of Life Syndrome
Behavioral syndromes within species bear a striking resemblance to interspecific fast-slow differences. Links have been found:
… between aggressive, risky behaviors and high reproductive success but also to lower survival (Smith & Blumstein 2008). Found in bighorn sheep (Reale et al 2009) and red squirrels (Boon et al 2008).
… between aggressive individuals and dispersal (Dingemanse et al. 2003).
… between aggressive males and less parental care (Duckworth & Badyaev 2007).
… between sociability and reduced propensity to disperse (Cote et al 2010).
Perhaps the conditions that generate interspecific POLS also generate interindividual POLS. This working assumption is known as the ecological gambit. The gambit becomes riskier if causal factors are known to operate at one level of analysis, but not another (Pollet et al., 2014). But the assumption is not without support. Some density dependent models that explain species POLS concurrently explain individual differences (Wright et al 2019). Finally, the Andre & Rousset (2020) model shows that extrinsic mortality influences individual, not just species, differences in life histories.
We can visualize the relationship between species and individual-level pace of life with the following cartoon. The biggest dark-blue oval represents the entire fast-slow continuum, the smaller blue ovals each represent a species, and the yellow ovals represent communities or individuals within a given species.
Behavior co-evolves with anatomy. If an individual’s body decays more quickly (preferentially investing resources into growth and reproductive effort), we should expect that individual to adopt different behaviors. Fast bodies should exhibit behaviors such as aggressiveness (especially in the context of intrasexual contest competition), and risk seeking. In fact, many behavioral metrics arguably conform to the fast-slow continuum.
Most sections in this article are fairly uncontroversial. However, the topics of this section are more contentious. Not everyone agrees that POLS can be applied to individuals and behaviors; some prefer to keep the analysis to average traits across species.
Evaluating the Syndrome
Life history theory (LHT) can be usefully understood as two sub-disciplines, whose literatures operate largely independently of one another (Nettle and Frankenhuis 2019)
LHT-E, or life history theory as practiced in ecology and evolutionary biology.
LHT-P, or life history theory as practiced in evolutionary psychology.
LHT-E tends to focus on the POLS traits across species. Within LHT-P, there are four separate movements, with decreasing levels of contact with evolutionary biology: pace of life syndrome research, evolutionary anthropology, evolutionary developmental psychology, and evolutionary personality psychology.
One of the strongest criticisms of LHT-P is its reliance on verbal models in lieu of formal models. As argued by Stearns & Rodrigues (2020), our capacity to develop complex verbal arguments is limited (the chamber of consciousness is small!). Our intuition often misleads, and the sensitivity of predictions to their underlying assumptions is not easy to see within informal arguments.
For example, Darwin’s several attempts to explain verbally the evolution of 50:50 sex ratios were unsuccessful: “I now see that the whole problem is so intricate that it is safer to leave its solution for the future” (Darwin 1874, pp. 259, 260). This problem was later solved in a few lines of algebra (Edwards 1998, 2000).
Another important criticism is a reliance on questionable assumptions of “extrinsic mortality”, which too often conflates random vs condition-dependent forms of environmental mortality.
The fast-slow continuum seems to be settled science. But animal personality research in general, and POLS in particular, is on empirically shaky ground (Mathot and Frankenhuis 2018). Yet I suspect more conservative examples of LHT-P are worth attending to.
But the construct seems to explain a great deal of physiology. Chronic stress may not be a disease; it may canalize the fast phenotype.
Chronic Stress vs. Pubertal Onset
The development of individual organisms is subject to ecological factors that drive interspecific differences. Human females, for example, can experience rapid (k1) or slow (k4) somatic growth. Each growth curve corresponds to a different optimal age of reproductive maturity; the solid line denotes this reaction norm.
Compared to the 19th century, women have become younger and taller at age of maturity (Worthman 1999). This secular trend has been most intense within groups of low socioeconomic status (SES) (e.g., Abioye-Kuteyi et al 1997). This class effect only pertains to countries where low SES groups do not suffer from systematic malnutrition and disease (it is absent in e.g., Denmark Helm & Lidegaard 1989). Interestingly, the link between nutrition and earlier puberty may be partially mediated by fiber content in the diet (Koo et al 2002). Other physical stressors can delay female puberty. While some exercise promotes androgens (Elias 1981), professional athletes often experience delayed puberty (e.g., Bale et al 1996).
Taken together, the shift up the reaction norm occurred with the Industrial Revolution and its concomitant energy surplus. Higher activity in the HPG axis is associated with earlier puberty; which may explain why levels of testosterone are also higher in developed countries (Henrich 2020 pp 551).
But some stressors can have the opposite effects. Survivors of the Great Sichuan earthquake were twice as likely to experience early puberty than controls (Lian et al 2018; see also Pesonen et al 2008). And more generally, a substantial literature indicates that early exposures to childhood adversities (e.g., socioeconomic adversity, childhood attachment, heightened parent–child conflict, father absence) tend to predict earlier pubertal development in females (Ellis 2004).
How to reconcile these findings? It seems like pubertal timing is contingent firstly on health and nutrition (see especially Kyweluk et al. 2018) and secondly, when these are adequate, on socioemotional conditions (Coall & Chisholm 2003).
Recall the big life history tradeoffs faced by organisms:
Three endocrine systems are involved in these dimensions:
I’ve previously noted how insulin-like growth-factor 1 (IGF-1) seems involved in the tradeoff between somatic and reproductive effort. It is especially responsive to nutritional status.
I have elsewhere noted how glucocorticoids (GC), and the stress response system (SRS) more generally, seem to mediate fast and slow phenotypes. The SRS is especially responsive to unpredictability and lack of control.
Finally, testosterone (T) plays a role in mating vs parenting decisions, at least in males. Testosterone drops substantially after marriage, and again on the birth of a child. It also appears to promote intragroup competition, consistent with sexual selection theory:
It may be worth exploring interactions between these different endocrine systems as they unfold across development.
Until next time.
Abioye-Kuteyi et al (1997). The influence of socioeconomic and nutritional status on menarche in Nigerian school girls
Andre & Rousset (2020). Does extrinsic mortality accelerate the pace of life? A barebones approach
Baams et al (2015). Transitions in body and behavior: a meta-analytic study on the relationship between pubertal development and adolescent sexual behavior
Bale et al (1996). Gymnasts, distance runners, anorexics body composition and menstrual status.
Belsky et al (2010). Infant attachment security and the timing of puberty: testing an evolutionary hypothesis
Belsky & Shalev (2016). Contextual adversity, telomere erosion, pubertal development, and health: two models of accelerated aging, or one?
Bergmuller et al (2010). Animal personality due to social niche specialization
Boon et al (2008). Personality, habitat use, and their consequences for survival in North American red squirrels (Tamiasciurus hudsonicus).
Brown et al (2004). Toward a metabolic theory of ecology
Clark (1994). Antipredator behavior and the asset protection principle.
Cote et al (2010). Social personalities influence natal dispersal in a lizard.
Dall et al (2012). An evolutionary ecology of individual differences.
Dammhahn et al (2018)
Del Guidice (2020). Rethinking the Fast-Slow Continuum of Individual Differences
Dingemanse et al (2003) Natal dispersal and personalities in great tits (Parus major).
Duckworth & Badyaev (2007). Coupling of dispersal and aggression facilitates the rapid range expansion of a passerine bird.
Elias (1981). Serum cortisol, testosterone, and testosterone-binding globulin responses to competitive fighting in human males
Ellis (2004). Timing of pubertal maturation in girls: an integrated life history approach
Engen & Sæther (2016). Optimal age of maturity in fluctuating environments under r- and K-selection
Gettler et al (2011). Cortisol and Testosterone in Filipino Young Adult Men: Evidence for Co-regulation of Both Hormones by Fatherhood and Relationship Status
Helm & Lidegaard (1989). The relationship between menarche and sexual, contraceptive, and reproductive life events
Henrich (2020). The WEIRDest people in the world: how the West became psychologically peculiar and particularly prosperous
Jeschke et al (2008) r-Strategist/K-strategists.
Koo et al (2007). A cohort study of dietary fibre intake and menarche
Kyweluk et al (2018). Menarcheal timing is accelerated by favorable nutrition but unrelated to developmental cues of mortality or familial instability in Cebu, Philippines.
Lian et al (2020). The impact of the Wenchuan earthquake on early puberty: a natural experiment
Mathot and Frankenhuis (2018). Models of pace-of-life syndromes (POLS): a systematic review
Mehta et al (2009). When are low testosterone levels advantageous? The moderating role of individual versus intergroup competition
Nettle & Frankenhuis (2020). Life-history theory in psychology and evolutionary biology: one research programme or two?
Pollet et al (2014). What can cross-cultural correlations teach us about human nature?
Pontzer et al (2016). Metabolic acceleration and the evolution of human brain size and life history
Pesonen et al (2008). Reproductive traits following a parent-child separation trauma during childhood: a natural experiment during World War II.
Reale et al (2009). Male personality, life-history strategies and reproductive success in a promiscuous mammal
Reale et al (2010). Personality and the emergence of the pace-of-life syndrome concept at the population level
Sear (2020). Do human ‘life history strategies’ exist?
Stearns & Rodrigues (2020).
Shultz (1969). The life of primates
Smith & Blumstein (2008). Fitness consequences of personality: a metanalysis.
Stearns (1983). The influence of size and phylogeny on patterns of covariation among life-history traits in the mammals.
Worthman (1999). Evolutionary perspectives on the onset of puberty.
Wright et al (2019). Life-history evolution under fluctuating density-dependent selection and the adaptive alignment of pace-of-life syndromes
Two research traditions provide very different accounts of hippocampal function:
Cognitive Account: The hippocampus has been linked to spatial navigation (reviewed here) and declarative memory.
Emotional Account: The hippocampus has been linked to the behavioral inhibition system, and its correlate – anxiety.
This situation is exacerbated by the radical simplicity of hippocampal circuitry. Buzsaki & Tingley (2018) attempt to unify the cognitive account, by exploring equivalencies between memory and navigation (both rely on sequential representations, with memory as “internal navigation at an attention-derived velocity”). But the cognitive and emotional strands are more difficult to reconcile. Strange et al (2014) attributes cognitive function to dorsal, and emotional function to ventral hippocampus. And there is strong lesion evidence in rats (Bannerman et al 2004) and neuroimaging studies in humans to support this view. It has a grain of truth.
But theta oscillations are found throughout the dorso-ventral axis. Yet these accounts attribute both emotional and cognitive properties to theta. This is puzzling. Is it reasonable to expect anxiety to lessen if running speed is reduced?
Varieties of Theta
Korotkova et al (2017) adduce evidence that cognitive and emotional elements contribute to the slope and y-intercept of theta, respectively. This dissociation was predicted by the Burgess (2008) model, which received empirical support in Wells et al (2013). These separate contributions to theta also cohere with developmental measures: large changes in intercept occurring between day 18 and 24 of the rat, despite much slower, gradual changes in slope (Wills et al., 2010).
But theta is not unitary. More precisely, the theta frequency band contains more than one oscillator. In rats, rabbit, and guinea pigs, two types of theta have been identified (Sainsbury & Montoya 1983). We recently found both oscillators in human neurosurgery patients (Goyal et al 2020), with very similar functional properties.
Type 1 Theta (~9 Hz in rats, ~8 Hz in humans). Correlates with movement speed, and dependent on entorhinal cortex
Type 2 Theta (~6 Hz in rats, ~3 Hz in humans). Does not correlate with movement speed.
The Respiration Oscillator
Theta is not the only biomarker relevant to behavioral inhibition. The hippocampus is also home to another rhythm entrained to breathing (Tort et al 2018). This respiration oscillator has been found in rat hippocampus (Lockmann et al 2016), and respiration-locked activity has been found in human cortex (Perl et al 2019). Beta oscillators peak at inspiration onset (Kluger & Gross 2021), which may explain why most voluntary behaviors are also initiated during this phase (Park et al 2020). Importantly, slow breathing promotes parasympathetic activity, mitigating the sympathetic arousal associated with BIS anxiety. This may mediate the health benefits provided by breath-centric meditation.
The nucleus incertus is one of four nuclei known to modulate theta rhythms, and it preferentially projects to the ventral hippocampus (Ma & Gundlach 2015). Within this nucleus, relaxin-3-positive neurons can be excited by the stress hormone corticotropin releasing factor (CRF) (Ma et al 2013). This constitutes a direct link between the stress response and hippocampal theta. This neuronal population also participates in respiratory activity (Furuya et al 2020), which strikes me as suggestive.
Bannerman et al (2004). Regional dissociations within the hippocampus–memory and anxiety
Burgess (2008). Grid cells and theta as oscillatory interference: theory and predictions
Buzsaki & Tingley (2018). Space and time: the hippocampus as a sequence generator
Furuya et al (2020). Relaxin-3 receptor (RXFP3) mediated modulation of central respiratory activity
Goyal et al (2020). Functionally distinct high and low theta oscillations in the human hippocampus
Eating mammal meat (aka red meat) promote chronic disease in humans, but not other animals. Why? Malaria uses the biochemical used to digest red meat – sialic acid – as a vehicle to enter primates. Some 4mya, a mutation altered Australopith sialic acid. The mutation helped our ancestors evade malaria!
Ultimately, of course, malaria caught up & regained the ability to infect us. Why has the sialic acid degradation been maintained since then? Domesticated mammals are a big source of disease. The longer they have been with us, the more “C19-like” zoonotic events have occurred. Living with domesticates has its benefits, but also increases risk of disease. Perhaps the inflammation produced by eating red meat provides some additional protection from mammal-born diseases. Such adaptive tuning of the immune system may increase inflammatory protection – only where it’s most needed.
In general, when getting vaccinated or boosted, you may consider a morning appointment. Immune response is literally twice as strong in the morning for most people. Like everything else in the body, the immune system fluctuates at a circadian rhythm.
Human RCT supports the “gravitostat” theory of fat mass regulation. Wearing a weighted vest 8h/d for 3 weeks caused fat loss. Possibly a parallel regulatory pathway to the one involving leptin.
More evidence for the role of persistent organic pollutants (POPs) in the sperm crisis.
Poverty damages mental & physical health via chronic stress. But chronic stress isn’t exactly a disease. It can mold the child to make the best of a bad situation. Chronic stress damages working memory capacity (aka fluid intelligence). But poverty also IMPROVES flexibility & updating! In unpredictable environments with rapidly changing statistics, it should be advantageous to rapidly update information about the immediate environment. But retrieval and capacity are more beneficial in predictable environments, where past experiences will likely apply to the future. Study, replication.
Some people (the Specialists) have strong, fixed personalities. Others (the Generalists) have weaker personalities, and adapt more to early life experience. Childcare quality doesn’t affect everybody. Specialist kids aren’t affected much by your parenting. Their genetic program is locked in. “Resilience” comes at a cost. But the Generalist kids! These are the ones at an advantage if are born in a happy home, and profoundly disadvantaged otherwise.This is the differential susceptibility model, aka “biological sensitivity to context”.
Did the sclera (whites of the eyes) evolve as a cooperative device, to share attentional information? The argument against.
UV vision in birds. Recall the evolution of color vision in primates: where duplication of long-range conopsin extended the dichromat ancestral pattern. Birds historically perceive a wider frequency range. A good example of umwelt.
Most integrals are intractable (life is hard), so we must often integrate numerically. Sadly, numerical integrators are unreliable & computationally expensive. Why not use ML as a numerical method? Introducing Probabilistic Numerics.
GitHub CoPilot has been released, an ML tool that will help you write code for $10/month.
One might venture that approach and avoidance are produced by a unitary system. But early behaviorist experiments showed that the strength of avoidance decreased at a greater rate than that of approach (Miller 1944). If you present food and shock together in an alley at the appropriate volumes, the approach system will dominate… until the rat gets close enough for its avoidance system to counterbalance. The result: fidgeting. Drugs like sodium amylobarbitone can modify the location of the conflict point. These data suggest, distinct systems control approach and avoidance behaviors.
The stress response system (SRS) is not synonymous with “fight or flight”. As we noted previously, the SRS engages behavioral effectors to address challenges to homeostasis. Behavioral effectors include avoidance – but they also include approach (e.g., foraging). Let us call the distinction between approach vs avoidance the bivalent motivation theory.
What about anxiety? Several theorists have sought to locate anxiety within the avoidance system. But anxiety dissociates from fear. Panicolytic drugs, which mimic amygdala lesions, mitigate fear but not anxiety. Anxiolytic drugs, which mimic hippocampal lesions, mitigate anxiety but not fear (Blanchard et al. 1997).
Gray & McNaughton (2004) argue that in some cases (novel objects, ambiguous social contexts) can concurrently activate the approach and avoidance systems. Rather than risking a disorganized response, this conflict resolution system is activated, and performs two functions:
To suppress prepotent behavior candidates generated by the approach and avoidance systems.
To elicit risk assessment behaviors to disambiguate the situation. And indeed, anxiolytic drugs suppress risk assessment behaviors (Blanchard et al 2011).
We will be referring to these three systems often.
The avoidance system is also called the fight, flight, or freeze system (FFFS).
The approach system is also called the behavioral activation system (BAS).
The conflict resolution system is also called the behavioral inhibition system (BIS).
While much exploration occurs in a context of safety, BIS-mediated explorations are conducted in situations of high risk. Thus, the BIS promotes physiological arousal and the stress response, to prepare the body for a potential emergency. Finally, the BIS increases negative bias by sensitizing the FFFS avoidance system, which may reduce the risk of further wasteful approach-avoidance conflict.
Reactivity vs Coping Style
Koolhaas et al (2010) describe two coping styles: proactive coping (boldness) and reactive coping (shyness). These traits are consistently expressed in the same individual at different times and in different situations. For example, proactive individuals who response aggressively to resident intruders are more likely to produce defensive behavior in a burying test two weeks later.
Reactive coping is also associated with individual differences in behavioral flexibility and impulse control! To me, this suggests reactive coping is analogous to an overactive BIS (although de Boer et al 2017 deny reactive coping relates to anxiety, nor the primary role of hippocampus).
Most well-known personality tests have poor statistical reliability… except one. The Big 5 (OCEAN) theory of personality explains large amounts of behavioral variation. Factor analyses reveal a hierarchy (DeYoung et al 2007):
Neuroticism is associated with reactivity of the HPA axis. It has two major subfactors:
Withdrawal reflects risk of anxiety and depression;
Volatility a disposition towards irritability, anger, and emotional lability.
Koolhaas et al (2010) present a 2D model, with the HPA axis playing a role in reactivity, and serotonin playing a role in coping style. This nicely dovetails the personality constructs above.
Withdrawal (reactive coping) has been attributed to an overactive BIS system. In developmental psychology, this has been studied in children with behavioral inhibition (BI; see Kagan et al 1984), analogous to adult shyness (Barker et al 2018).
High BI children produce a larger startle (Barker et al 2014), and enhanced amygdala activity (Cremers et al 2010): sensitized avoidance.
High BI adults exhibit faster responses to both reward and punishment (Hardin et al 2006): sensitized approach (Helfinstein et al 2012).
Why does shyness occur? BIS only activates when the BAS and FFAS conflict. If both mechanisms expand, conflict occurs more frequently.
Evolution of Bivalence
These systems are extraordinarily ancient and conserved across phyla (Elliot & Covington 2001). In unicellular organisms, movement is dictated by gradients, such as foraging initiated by immediate chemical gradients in the immediate surroundings. While the representation capacities of these systems have clearly increased, the basic dichotomy persists.
Cisek (2021) proposes that bivalent motivation was a central organizing principle of neural evolution.
He also argues that
Contralateral innervation evolved to support the avoidance system: if a predator is sensed by the left hemisphere, the animal needs to move to the right and vice versa.
The approach system implemented winner-take-all decision-making, whereas the avoidance system is implements averaging. If you spot two predators, your escape vector should integrate both of them. But if you find two foraging patches, it is optimal to only approach one.
For the BAS approach system, tonic dopamine in the basal ganglia plays a central role in motivating approach. This is clearly seen in neurological conditions (Krack et al 2010):
The FFAS avoidance system is grounded in the central amygdala and the bed nucleus of the stria terminalis (BNST). Just as the approach system calculates reward, the lateral habenula calculates antireward. This extended amygdala loop interoperates with the three “classical” basal ganglia loops above:
The BIS conflict detection system is closely associated with the septo-hippocampal system (Gray & McNaughton 1980). Anxiolytic drugs bear a strong resemblance to hippocampal lesions.
Of course, the cortex also plays an important role. Consider the pregenual cingulate (a.k.a. BA 25, or prelimbic cortex). This region has been implicated in depression (Pizzagalli 2011), addiction (Goldstein et al 2009), OCD (Fitzgerald et al 2005), and PTSD (Kasai et al 2008). While most of this surface had equal numbers of approach- and avoidance- representing neurons, one particular subregion (ventral pregenual anterior cingulate cortex, vPgACC) was predominated by avoidance processes.
Stimulation of vPgACC altered the decision boundary for approach-avoidance tasks, where the rat had to choose whether to experience food and an aversive airpuff, but not approach-approach tasks where the rat had to choose between two different kinds of food. These effects were cumulative: avoidance became increasingly pronounced as the number of stimulation trials increased. Finally, the effect of this region evaporated on administration of antianxiety drugs (Amemori & Graybiel 2012).
The striatum contains patches of cells (striosomes) in an otherwise homogenous population (matrix). The matrix appears to be only responsive to benefits; whereas the striosomes evaluates costs and benefits when both values are high. Striosomes in the dorsomedial associative striatum receive input preferentially from vPgACC, and their activity also changes the decision boundary by increasing loss aversion (Friedman et al 2015). Striosomes project gorgeous bouquets (Crittenden et al 2015) into the dopaminergic substantia nigra pars compacta (SNpc), which mediates their impact on decision making.
Lateralization in Frontal Cortex
In the cortex, some of the underlying mechanisms appear to be lateralized.
One tradition argues that the left frontal cortex participates in approach; the right in avoidance (Fetterman et al 2013; Carver & Harmon-Jones 2009).
Chemical suppression (via amytal injection) to the left hemisphere produced depression; right injections produce mania. (Terzian 1964).
Lesions to the left hemisphere produce depression, lesions to the right hemisphere produce mania (Robinson & Price 1982).
Experiments which elicit reward processes create left-asymmetric activity; punishment created right-biased activity (Coan & Allen 2004)
Personality differences in approach and avoidance are predicted by resting EEG asymmetries (Davidson 1999)
Another tradition argues that left vs right reflects behavioral continuation vs override (Wacker et al 2008), or task setting vs monitoring (Stuss & Alexander 2007). Both traditions seem close to convergence on the left hemisphere. I wonder if there might exist some middle ground, where the right hemisphere participates in the other avoidance system (BIS).
Right frontal theta is uniquely sensitive to approach-avoidance conflict, and is more pronounced in people suffering anxiety disorder (Shadli et al 2021). Such goal conflict-specific rhythmicity (GCSR) is now being used as a biomarker for anxiety disorder.
Consider posing asymmetries. The left side of the face is more active during emotional expression (Borod et al 1997). This explains why people prefer to show (and view) the left side of the face, and why people instructed to hide their emotions preferentially display the right.
The right hemisphere theory attributes perception & performance of all emotions to the right hemisphere. But there appears to be a second lateralization effect compatible with bivalent motivation (Demaree et al 2005). While on average the left hemiface is more expressive for all emotions, the left-bias was stronger for negative emotions, and weaker for positive emotions (Borod et al 1997).
Humans preferentially turn rightward in the (approach) act of kissing (Gunturkun 2003).
In general, left-hemisphere dominance for handedness and language might be compatible with a general specialization for routine action control (MacNeilage 1998), and can be reconciled with the postural origins theory of handedness (MacNeilage 2007).
The study of lateralization suffers several limitations:
The shadow of mythology looms large (McManus 2018), exemplified in popular brainedness theories (e.g. Jaynes 1976, McGilchrist 2009).
The comparative biology data of handedness is equivocal.
The difference scores method in comparing hemispheric activity is contentious.
These data often only permit macro-scale descriptions (“frontal cortex”), which inevitably conflate meso- and micro-scale structural circuits.
I have not found a unifying theory to explain the relationship of lateralization effects across domains.
Yet these low-resolution data still suggest to me a left-bias for approach, and a right-bias for avoidance.
Stimulating avoidant nuclei in the hypothalamus produces fight, flight, or freezing. These behaviors depend not on the location of the probe, but on the context of the animal’s environment. Blanchard & Blanchard (1990) showed that considerable behavioral variation can be explained by defensive distance:
Defensive distance is more nuanced than physical distance. In a more dangerous situation, a greater real distance will be required to achieve the same defensive distance. Likewise, with a braver individual, a smaller real distance will be required to achieve the same defensive distance.
The behavioral hierarchy is driven by defensive distance. More distant threats produce slower, sophisticated defenses; more proximal threats produce faster, cruder defense mechanisms (Blanchard & Blanchard 1990). These are:
Undirected escape (emotional correlate: dread)
Directed escape (emotional correlate: panic)
Active avoidance (emotional correlate: fear and phobias)
Discriminated avoidance (which might include complex emotions such as guilt)
Recall the neural hierarchy: the further from the brainstem, the more conceptual the representations. Graeffe (1994) argues the behavioral hierarchy is isomorphic to a neural hierarchy, with phylogenetically newer structures layered on top of older systems. This is the hierarchical defense system.
The central amygdala supports fear conditioning (Le Doux 1994). Defense systems lower in the hierarchy do not support such learning, but directly respond to dangerous stimuli.
Just as BAS and FFFS are organized hierarchically, McNaughton & Corr (2004) argue the same for BIS:
Economics and Emotion
It is important to distinguish between valuation and motivation. Specific visceral states dynamically alter individual valuations (this is alliesthesia). But even holding visceral deprivation constant, there are individual differences in valuation sensitivity. In behavioral economics, the ratio of positive to negative sensitivity is known as loss aversion.
Loss aversion is not the same as repulsion sensitivity. Individual differences in valuation and motivation vary independently.
Modular theories of emotion (e.g Panksepp 1998) envision distinct neural circuitry for each basic emotion. In contrast, constructivist theories explore emotional states as emergent properties from a few core dimensions. The latter have been heavily influenced by Russel (1980) circumplex model, which organizes emotional experience into two dimensional space.
Approach/avoidance theorists are more aligned with dimensional models. But rather than interpreting valence as one-dimensional (bipolar), they claim each object is simultaneously attributed a positive and a negative valence score (bivalenced). Ambivalence is universal. Psychological evidence (van Harreveld et al 2004) and neural evidence (Man et al 2017) suggests brains retain multiple representations of valence. For example, the basolateral nucleus of the amygdala (BLA) contains three subpopulations of neurons: positive valence, negative valence, and arousal (Shabel & Janak 2009).
We have previously learned how the brain engages in biological defense of physiological balance points conducive to life. For example, temperature is regulated by deploying both internal effectors (e.g., shivering, goose flesh, vasoconstriction) and external effectors (i.e., seeking warmth in the environment).
On this view, a stressor is anything in the outside world that knocks you out of homeostatic balance, and the stress-response is what your body does to reestablish homeostasis.
What happens when the organism is severely stressed? Hunting your prey, being hunted, fighting for females, freezing to death, and having sex each levy unique behavioral demands. But they also require many things in common:
Sharpened attention & faster reflexes
High heart rate & blood pressure to enhance blood supply to the organs.
More energy (more glucose in the bloodstream, intracellular anabolism) to subsidize rapid movement.
Pausing long-term projects (e.g., digestion consumes 10-20% of the mammalian energy budget)
What happens when an organism is comfortable? We might predict these effectors to be offline, and bodily resources to be engaged in projects with long-term benefits: sleep, digestion, cell repair, reproductive activity, protein construction (catabolism) etc.
The stress response is not identical to physiological actions required to sustain life. But it is the embodiment of overlapping needs within the effector ecosystem. Call this the effector overlap theory of stress. The generality of the stress response explains why its discoverer Selye dubbed it the General Adaptation Syndrome.
The above account distinguishes between short-term emergencies versus long-term projects. On the life history theory of stress, stress involves postponing long-term projects. We can see this in semelparous species like salmon or which evolved to die immediately after reproduction. These salmon die from a prolonged stress response. Remove their overactive adrenal gland, and they are suddenly able to live for another year.
We previously distinguished between reactive vs predictive homeostasis. On the overlap theory, it should not be surprising that the stress response also exhibits a predictive, circadian component.
The Anatomy of Stress
This basic dichotomy manifests in the parasympathetic (PNS) “rest and digest” and sympathetic (SNS) “fight or flight” systems. Nearly every organ is dually innervated by both systems, with the vagus nerve carrying most parasympathetic signals, and the sympathetic trunk mediating sympathetic signals. Moreover, these two subsystems often constitute opponent processes; that is, they exhibit functional antagonism.
But the stress response involves more than just the SNS. We have previously introduced circumventricular organs (CVOs), which puncture the blood-brain barrier in a controlled way. These organs provide neuroendocrine integration. There are many neuroendocrine axes, including HPG (reproduction), HPT (metabolism) and HPS (growth). The hypothalamus-pituitary-adrenal (HPA) axis also regulates levels of glucocorticoids (cortisol in humans). Stressors also evoke other hormonal responses, including
glucagon (energy mobilization),
prolactin (suppressing reproduction),
endorphins (blunting pain perception), and
vasopressin (mediating the cardiovascular stress response)
osteocalcin (inhibits the parasympathetic branch) Berger et al (2019).
Another branch coordinates activity between SNS and HPA: the sympathomedullary (SAM) pathway.
The affective dimension of arousal involves increased alertness to sensory stimuli, increased motor activity and increased emotional reactivity (Pfaff, 2006). Levels of arousal typically vary in a circadian fashion, but various events, including exposure to a stressor, can rapidly increase arousal levels. The orexin system appears to mediate the relationship between stress and arousal in the brain (Berridge et al 2010).
In periphery, norepinephrine (NE) and acetylcholine (ACh) mediate the SNS and PNS, respectively. In the brain, loosely speaking, these same neuromodulators are associated with arousal and learning. A good example of core-periphery functional consilience.
Taken together, these systems (SNS, HPA axis, SAM, etc) are known as the stress response system (SRS).
There are two kinds of stress response
Interoceptive (systemic) stress, where the body detects homeostatic imbalance. Related to reactive homeostasis.
Exteroceptive (psychogenic) stress, or predicted future dysregulation. Related to predictive homeostasis.
These forms of stress are handled differently by the brain,
There are two kinds of stress responses:
Bodily stress response (e.g., physical exercise). Mediated primarily by noradrenaline via the SNS system.
Mental stress response (e.g., working memory tasks). Mediated primarily by adrenaline via the SAM system.
Many interoceptive stressors require bodily responses, whereas some exteroceptive stressors only require mental responses.
The Experience of Stress
Our experience frequently toggles between these two systems. As Sapolsky (2004) writes:
If you are a growing kid and you have gone to sleep, your parasympathetic system is activated. It promotes growth, energy storage, and other optimistic processes. Have a huge meal, sit there bloated and happily drowsy, and the parasympathetic is going like gangbusters. Sprint for your life across the savanna, gasping and trying to control the panic, and you’ve turned the parasympathetic component down.
The interplay between the autonomic nervous system is visible in respiration. The PNS is dominant during exhalation, and stress response is more active during inhalation. This may explain why exhalation-focused breathing (with low inhalation/exhalation ratio) can promote calmness.
The interface between SNS and PNS is also well described during sexual intercourse:
To get an erection, a guy has to be calm, vegetative, and relaxed. What happens next, if you are male? You are having a terrific time with someone. Maybe you are breathing faster, your heart rate has increased. Gradually, parts of your body are taking on a sympathetic tone. After a while, most of your body is screaming sympathetic while, heroically, you are trying to hold on to the parasympathetic tone in that one lone outpost as long as possible. Finally, when you can’t take it anymore, the parasympathetic shuts off at the penis, the sympathetic comes roaring on, and you ejaculate.
The pain system is a competition between fast pain and slow pain (Hopkin 1997). Only the former promotes the stress response – they motivate you to quickly move away from the source of the piercing pain. What the slow fibers are about is getting you to hunker down so you can heal.
Stress can also cause analgesia (pain desensitization, e.g., a runner’s high), because your body secrets beta endorphins which mitigate objective pain perception in the spinal cord (Guillemin et al 1977). But when the stress response tilts towards anxiety, stress-induced hyperalgesia can occur via promoting subjective pain perception (Price 2000).
Heart attacks are much more likely to occur when the SRS is activated. So are flare-ups from autoimmune diseases like multiple sclerosis. Withdrawal and excessive drug use can be blocked by CRF antagonists, which speak to the intimate relationship between addiction and stress.
Three Phases of the Stress Response
These systems work at different timescales. SNS responds to stressors immediately, but cortisol changes occur within a few minutes. One can usefully model three phases of the stress response: stress initiation (high CRH, low cortisol), stress maintenance (high CRH and cortisol), and stress recovery (low CRH, high cortisol).
CRH inhibits eating (hypophagia), but cortisol promotes it (hyperphagia). The phase model of stress helps us make sense of this seemingly inefficient tension: eating is inhibited during the first two phases (high CRH), but promoted during stress recovery (low CRH). This explains why people exposed to long, continuous stressors (inhabiting the middle phase) tend to lose weight; whereas people with frequent, intermittent stressors (spending more time in recovery phase) tend to gain weight.
For those reactive to stress, stress eating can cause problems. Cortisol hypersecretors are most likely to be hyperphagic after stress (Epel et al 2001), and they disproportionately favor comfort foods (Dallman et al 2003). These people are more likely to have visceral fat (Epel et al 2000), which is much more harmful than subcutaneous fat (Welin et al 1987). This is because glucocorticoids are disproportionately expressed in the abdomen (Rebuffe-Scrive et al 1990), and are activated during stress recovery.
A similar trade off occurs in the immune system. The beginnings of stress response (first 30min) promotes immune function, but after a while (past 1h mark) stress has an immunosuppressant effect. This explains why long, continuous stressors suppress the immune system; whereas frequent, intermittent stressors stimulate the immune system and over time increases the risk of autoimmune disorders (e.g., asthma or multiple sclerosis). This explains why putting people “on steroids” (giving them massive amounts of cortisol) can protect against autoimmune disorders, and yet flare-ups of autoimmune symptoms are also yoked to stress.
Herpesviruses establish latency, which means they hide inside cells and only replicate when they are at an advantage. Their DNA contains a glucocorticoid sensor – when the virus detects elevated GCs, it knows the immune system is temporarily suppressed & it comes out of latency. The virus can even artificially induce an SRS response via your hypothalamus.
Chronic Stress and Senescence
While today’s discussion is at the systems level, the SRS also interacts with intracellular mechanisms. As we will explore next time, individual differences in chronic stress may involve differential rates of senescence. For example, individuals exposed to chronic stress show signs of accelerated biological aging, such as telomere erosion (Humphreys et al 2012).
Many mechanistic theories of senescence appeal to metabolic functions of the mitochondria. And chronic stress has been shown to reduce mitochondrial energy production capacity (Picard & McEwen 2018).
The reactive oxidative species (ROS) theory of senescence appeals to intracellular oxidative stress, not to be confused with systemic psychological stress. But chronic psychological stress does seem to promote oxidative stress (Aschbacher et al 2013), which may explain its role in accelerated aging.
Stress reactivity (larger, slower-fading GC response to stressors) is caused by chronic stress. The Big-5 personality trait of Neuroticism is a crucial moderator of reactivity (Zobel et al 2004)
The Volatility facet of Neuroticism, analogous to Hostile Type A personalities, produces an increased risk of cardiovascular disease (CVD) (Williams & Litman 1996). The link seems causal (Friedman et al 1996). Amusingly, the link between Type A and CVD seems to have been first discovered by an upholsterer in a cardiologist’s office: “…what on earth is wrong with your patients?”:
Stress is involved in age-related diseases like general inflammation, and CVD. However, GC seems to not play a causal role in another age-related disease: cancer. Another endocrine system implicated in senescence, insulin-like growth factor-1 (IGF-1), is more involved in cancer risk.
Stressor Determinants: Predictability and Control
Gradual-onset ulcers are caused by an acid-resistant bacteria known as helicobacter pylori (Dooley & Cohen 1988). Yet, while nearly all of us have the disease, only 10% of us develop ulcers. Stress is one of the lifestyle factors which inhibits repair of the stomach lining, and hence increases risk of ulceration (Levenstein 1998). Ulceration is thus a useful operationalization of stress, and you can explore intricacies of the SRS by measuring gastric lesions.
Weiss (1972) hooked mice to receive tail shock every minute in a continuous 21-hour session. His work sheds light on psychological mechanisms of coping.
Predictability: if you give a warning tone before the shock, rats experience less stress (left vs right column)
Control: give a lever to stop its shock and a “yoked” neighbor, the rat will experience less stress (gray vs black bar).
Foreknowledge: early foreknowledge of shock worsens stress only in rats with no control (left vs middle column).
Predictability can drive SRS magnitude, independent of the physiological implications:
Random interval feeding is associated with stronger SRS response than fixed intervals in rats.
Stressor habituation reduces the response to predictable stressors. Parachute jumpers eventually experience no stress as they move through their training (Ursin et al 1978).
In WW2, nightly air raids in cities produced fewer ulcers than infrequent & unpredictable suburban bombings (Stewart & Winser 1942).
Uncontrollability can shut down the SRS. Overmeier & Leaf (1965) discovered that dogs exposed to uncontrollable stressors were later unable to learn a shock-avoidance task, one that controls were easily able to master. Such learned helplessness has tight links to major depression (Seligman 1975). Polyvagal theory interprets this as Jacksonian dissolution: if the SRS fails, the nervous system will fall back to the dorsal vagus.
White (1959) described the desire for control as a motivational drive for competence. As behaviorism was supplanted during the Cognitive Revolution, Rotter (1966) reformulated the theory as locus of control: attitudes of self-control are associated with positive outcomes in myriad facets of daily life (Lefcourt 1992). People’s ratings of self-efficacy are better predictors of future behavior than their past behaviors (Bandura 1977). Self-efficacy also controls effort. When faced with difficulties, people who doubt their abilities quickly give up; people who don’t ratchet up their effort (Bandura & Cervone 1983)
These led to the attributional reformulation of learned helplessness; with its three parameters of explanatory style:
Locus: is the cause internal to the self, or external?
Consistency: are the causes stable over time, or not?
Scope: are the causes global, or specific?
A person with a depressive style (habitually invoking internal, stable, and global factors to explain failures) is most at risk of becoming depressed in the face of uncontrollable circumstances.
Outlets for Frustration
We have previously discussed displacement behaviors: for example, if a starving rat is given some food, but not enough to mitigate the drive, it will engage in ritualistic behaviors, such as pacing, gnawing wood, or self-directed behaviors. These behaviors reduce the stress response, but only for men with low neuroticism (Mohiyeddini et al 2015). Displacement behaviors don’t seem to help women in the same way (Mohiyeddini et al 2013).
Displacement aggression (“punching down”) is a significant outlet for frustration. Here’s Sapolsky (2004):
A variant of Weiss’s experiment uncovers a special feature of the outlet-for-frustration reaction. This time, when the rat gets the identical series of electric shocks and is upset, it can run across the cage, sit next to another rat and.. bite the hell out of it. Stress-induced displacement of aggression: the practice works wonders at minimizing the stressfulness of a stressor. It’s a real primate specialty as well. A male baboon loses a fight. Frustrated, he spins around and attacks a subordinate male who was minding his own business. An extremely high percentage of primate aggression represents frustration displaced onto innocent bystanders. Humans are pretty good at it, too. Taking it out on someone else–how well it works at minimizing the impact of a stressor.
I wish that I understood the reason why outlets have such effects.
Until next time.
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Aschbacher et al (2013). Good stress, bad stress and oxidative stress: insights from anticipatory cortisol reactivity
Bandura (1977) Self-efficacy: toward a unifying theory of behavioral change
Bandura & Cervone (1983). Self-evaluative and self-efficacy mechanisms governing the motivational effects of goal systems.
Berger et al (2019). Mediation of the Acute Stress Response by the Skeleton
Berkman & Syme (1979). Social integration, social networks, social support and health
Berridge et al (2010). Hypocretin/Orexin in Arousal and Stress
Dallman et al (2003). Chronic stress and obesity: a new view of comfort food
Deussing & Chen (2018). The Corticotropin-Releasing Factor Family: Physiology of the Stress Response
Dooley & Cohen (1988). The clinical significance of Campylobacter pylori
Epel et al (2001). Stress may add bite to appetite in women: a laboratory study of stress-induced cortisol and eating behavior
Epel et al (2000). Stress and body shape: stress-induced cortisol secretion is consistently greater among women with central fat
Friedman et al (1996) Effects of Type A behavioral counseling on frequency of episodes of silent myocardial ischemia in coronary patients
Guillemin et al (1977). Beta-endorphin and adrenocorticotropin are secreted concomitantly by pituitary gland.
Heinrichs et al (2003). Social support and oxytocin interact to suppress cortisol and subjective responses to psychosocial stress
Hopkin (1997). Show me where it hurts: tracing the pathways of pain
Humphreys et al (2012). Telomere shortening in formerly abused and never abused women.
Lefcourt (1992) Durability and impact of the locus of control construct
Levenstein (1998). Stress and peptic ulcer
Marmot et al (1978). Employment grade and coronary heart disease in British civil servants
Mohiyeddini et al (2013). Displacement behavior is associated with reduced stress levels among men but not women.
Mohiyeddini et al (2015). Neuroticism and stress: the role of displacement behavior
Overmeier & Leaf (1965). Effects of discriminative Pavlovian fear conditioning upon previously or subsequently acquired avoidance responding.
Parent et al (2017). Dynamic stress-related epigenetic regulation of the glucocorticoid receptor gene promoter during early development: The role of child maltreatment.
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Picard & McEwen (2018). Psychological Stress and Mitochondria: A Systematic Review
Price (2000). Psychological and Neural Mechanisms of the Affective Dimension of Pain
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Sapolsky (2004). Why zebras don’t get ulcers, third edition
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Weiss (1972). Psychological factors in stress and disease
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Part Of: Biology sequence Content Summary: 1800 words, 9 min read.
The Disposable Soma
Many people interpret aging as an inevitability: heat death is coming for us all. And it is true that most organisms experience senescence, i.e., age-related deterioration (Nussey et al 2012), even some bacteria (Ackermann et al 2003).
But some organisms experience negligible senescence (e.g., hydra Martinez 1998 or rockfish Finch 2009). Why isn’t negligible senescence the norm? As Williams (1957) put it,
It is remarkable that after a seemingly miraculous feat of morphogenesis, a complex metazoan should be unable to perform the much simpler task of merely maintaining what is already formed.
A clue: organisms rarely die from old age. Rather, environmental mortality (accidents, predation, starvation, disease, cold, etc) usually strike well before senescence does (Finch 1990). Why invest in maintaining a body that will be dead anyway for other reasons?
For example, 90% of wild field mice die in their first year (Phelan and Austad 1989), typically from cold. The three-year lifespan potential of the mouse is sufficient for its actual needs in the wild, and yet it is not excessive.
Consider the trade-offs associated with energy allocation. Because energy is scarce, the mouse will benefit by investing any spare energy into thermogenesis or reproduction, rather than better somatic maintenance, even though this means that damage will eventually accumulate to cause aging.
In metazoans, we saw cellular differentiation between somatic cells (which could specialize to ultimately become muscle, bone, etc) and germ cells (which promote reproduction). The germ line requires biological immortality: individual germ cells can die, but the lineage cannot be allowed to deteriorate. Germ cells accomplish this in part by better maintenance: for example, the protective enzyme telomerase only exists in germ cells and in certain adult stem cells. Once embryonic stem cells differentiate into somatic cells, there is a generalized downregulation of cell maintenance systems (Saretzki et al 2004).
This is the disposable soma theory of aging (Kirkwood 1977).
Aging vs Mortality
The idea that intrinsic longevity is tuned to the prevailing level of extrinsic mortality is supported by extensive observations on natural populations (Ricklefs 1998).
It’s not just observational evidence.
Stearns et al (2000) imposed a high mortality regime on one group of fruit flies, and observed that their experimental group lived a shorter life and a reduced age of sexual maturity.
In a natural experiment, opossums naturally evolving on a predator-free island lived longer than their phylogenetic siblings on a normal-predation population (Austad 1993).
Differences in mortality explains a large fraction of lifespan variance between species. For example, flying species enjoy weaker senescence than non-flying species, due to the shelter against mortality (Healy et al 2014). The lifespan-extending effect of mortality reduction is also seen…
… in arboreal species (Shattuck & Williams 2010),
… in fossorial species (Healy et al 2014),
… in species that hibernate (Turbill et al 2011)
… in species that evolve protective shells (Phillip & Abele 2010)
In most species, males senesce faster than females (Brooks & Garrett 2017). This is considered to be a direct investment of the male involvement in intrasexual (and intersexual) competition (Bonduriansky et al 2008), and the resultant increase in male mortality.
We might distinguish between two kinds of environmental mortality:
Non-selective mortality (e.g., the onset of winter) which strikes at random
Selective mortality (e.g., predation) which preferentially strikes certain demographics
The above experimental results above relate to non-selective mortality. But Abrams (1993) has shown that evolutionary predictions can be considerably altered when density dependence is taken into account; selective mortality affects per capita resource availability. Chen & Maklakov (2012) found that lifespan decreases with random mortality, but increases with condition-dependent mortality (application of heat shock: only especially robust worms survive).
Aging vs Growth
Growth also drives senescence, because growth affects fecundity. Unceasing, indeterminate growth allows increasing fecundity with age. Indeed, senescence is negligible in organisms displaying indeterminate growth (Vaupel et al. 2004). But senescence is the rule in determinate growth organisms such as birds and mammals (Nussey et al. 2013).
Experimentally induction of catch-up growth reduces lifespan (Lee et al 2013).
In fact, growth rate is composed of two biologically distinct mechanisms. Development time is differentiation of the soma; under sexual selection during scramble competition (Andersson 1994). Growth is an increase in mass. When these are decoupled, only development time was found to be coupled to longevity (Lind et al 2017).
Many studies suggest that the hypothalamus-pituitary-somatotropic (HPS) axis mediates the tradeoff between growth and senescence (Dantzer & Swanson 2012). Fast species tend to have higher plasma insulin-like growth factor (IGF-1) than slow species (Swanson and Dantzer 2014; but see Stuart and Page 2010).
Two Genetic Theories of Aging
90% of wild rats die from cold in their first year, but in a protected laboratory environment those same rats live for three years, before dying of age-related diseases. From an evolutionary biologist’s perspective, senescence can evolve because selection gradients on mortality and fertility decline with age. Modeling by Hamilton (1966), and extended in Charlesworth (1994), found that selection is simply much weaker in old age; it casts a selection shadow.
Medawar (1952) noted the similarities between aging and Huntington’s disease. If the disease is inherited and always fatal why hasn’t natural selection expunged the responsible alleles from our gene pool? The answer, of course, has to do with the fact that Huntington’s disease typically strikes late in life history. He wrote “the force of natural selection weakens with increasing age… if a genetic disorder happens late enough in life, its fitness consequences may be completely unimportant”.
This is the mutation accumulation theory of senescence (MATS). It appeals tothe ubiquity of pleiotropy: one gene can produce multiple, different effects across the life course.
Williams (1957) proposed the antagonistic pleiotropy theory of senescence (APTS). Rather than neutrality, some age-related genes are selected for their benefits to early life, despite those very same genes being deleterious later.
There are important differences between these two theories. Because mutations occur randomly, MATS predicts that aging will be fairly idiosyncratic to that lineage; whereas APTS suggests that the mechanisms underlying aging are comparatively more shared. If APTS is true, biogerontology research on model organisms should prove more informative to human therapeutics.
IGF-1 genes promote growth yet inhibit somatic maintenance. They are excellent candidates for antagonistic pleiotropy, and showcase how the disposable soma theory can bridge genetic and microbiological perspectives.
Some weak evidence has been found for MATS. In contrast, the evidence for APTS is fairly strong (Austad & Hoffman 2018), including identification of dozens of candidate genes. When these genes are knocked out, such as an IGF receptor gene in C elegans, the resultant stains live longer, but ultimately disappear due to a small reduction in early life fertility (Jenkins et al 2004). William’s APTS model generated nine predictions about senescence; today, six of these have found strong support (Gaillard & Lemaitre 2017).
The Search For Mechanism
A quote from Kirkwood (2005)
One oddity about aging is its inherent complexity. Almost every aspect of an organism’s phenotype undergoes modification with aging, and this phenomenological complexity has led, over the years, to a bewildering proliferation of ideas about specific cellular and molecular causes.
In the disposable soma theory, senescence is caused by failures to maintain the soma. But which specific mechanisms are involved? Microbiologists have not yet achieved consensus of causal mechanism. But they have achieved a consensus list of candidates: Lopez-Otin et al (2013) motivates nine hallmarks of aging.
Perhaps someday we will have therapeutics that effectively promote somatic maintenance.
Until next time.
Abrams (1993). Does increased mortality favor the evolution of more rapid senescence?
Ackermann et al (2003). Senescence in a bacterium with asymmetric division
Andersson (1994). Sexual selection.
Austad (1993). Retarded senescence in an insular population of Virginia opossums
Austad & Hoffman (2018). Is antagonistic pleiotropy ubiquitous in aging biology?
Bonduriansky et al (2008). Sexual selection, sexual conflict and the evolution of ageing and life span
Brooks & Garrett (2017). Life history evolution, reproduction, and the origins of sex-dependent aging and longevity
Charlesworth (1994). Evolution in Age-Structured Populations
Chen & Maklakov (2012). Longer Life Span Evolves under High Rates of Condition-Dependent Mortality
Cole (1954). The population consequences of life history phenomena
Danson & Swanson (2012). Mediation of vertebrate life histories via insulin-like growth factor-1.
Finch (1990). Longevity, senescence and the genome
Finch (2009). Update on slow aging and negligible senescence – a mini-review
Gaillard & Lemaitre (2017). The Williams’ legacy: A critical reappraisal of his nine predictions about the evolution of senescence
Hamilton (1966) The moulding of senescence by natural selection
Healy et al (2014). Ecology and mode-of-life explain lifespan variation in birds and mammals
Jenkins et al (2004). Fitness cost of extended lifespan in Caenorhabditis elegans
Jones et al (2008). Senescence rates are determined by ranking on the fast-slow life-history continuum.
Kirkwood (1977). Evolution of ageing
Kirkwood (2005). Understanding the odd science of aging
Lee et al (2013). Experimental demonstration of the growth rate–lifespan trade-off
Lind et al (2017). Slow development as an evolutionary cost of long life
Lopez-Otin et al (2013). Hallmarks of aging
Martinez (1998). Mortality patterns suggest lack of senescence in hydra.
Medawar (1952). An unsolved problem of biology.
Nussey et al (2013). Senescence in natural populations of animals: widespread evidence and its implications for bio-gerontology
Omholt & Amdam (2004). Epigenetic regulation of aging in honeybee workers
Phelan and Austad (1989). Natural selection, dietary restriction and extended longevity
Phillip & Abele (2010). Masters of Longevity: Lessons from Long-Lived Bivalves – A Mini-Review
Ricklefs (2010). Embryo development and ageing in birds and mammals
Saretzski et al (2004). Stress Defense in Murine Embryonic Stem Cells Is Superior to That of Various Differentiated Murine Cells
Shattuck & Williams (2010). Arboreality has allowed for the evolution of increased longevity in mammals.
Stearns et al (2000) Experimental evolution of aging, growth, and reproduction in fruitflies.
Stenvinkel & Shiels (2019). Long-lived animals with negligible senescence: clues for ageing research
Stuart & Page 2010). Plasma IGF-1 is negatively correlated with body mass in a comparison of 36 mammalian species
Swanson & Dantzer (2014). Insulin-like growth factor-1 is associated with life-history variation across Mammalia
Turbill et al (2011). Hibernation is associated with increased survival and the evolution of slow life histories among mammals.
Vaupel et al (2004) The case for negative senescence
Wensink et al (2017). The rarity of survival to old age does not drive the evolution of senescence
Williams (1957). Pleiotropy, natural selection and evolution of senescence
Excerpt From: Sapolsky (2004). Why Zebras Don’t Get Ulcers
Of all the hormones that inhibit the reproductive system during stress, prolactin is probably the most interesting. It is extremely powerful and versatile; if you don’t want to ovulate, this is the hormone to have lots of in your bloodstream. It not only plays a major role in the suppression of reproduction during stress and exercise, but it also is the main reason that breastfeeding is such an effective form of contraception. Oh, you are shaking your head smugly at the ignorance of this author with that Y chromosome; that’s an old wives’ tale; nursing isn’t an effective contraceptive. On the contrary, nursing works fabulously . It probably prevents more pregnancies than any other type of contraception (Djerassi 1979). All you have to do is do it right.
Breast feeding causes prolactin secretion. There is a reflex loop that goes straight from the nipples to the hypothalamus. If there is nipple stimulation for any reason (in males as well as females), the hypothalamus signals the pituitary to secrete prolactin. And as we now know, prolactin in sufficient quantities causes reproduction to cease.
The problem with nursing as a contraceptive is how it is done in Western societies. During the six months or so that she breast-feeds, the average mother in the West allows perhaps half a dozen periods of nursing a day, each for 30 to 60 minutes. Each time she nurses, prolactin levels go up in the bloodstream within seconds, and at the end of the feeding, prolactin settles back to pre-nursing levels fairly quickly. This most likely produces a scalloping sort of pattern in prolactin release.
This is not how most women on earth nurse (Konner & Worthman 1980). When a hunter-gatherer woman gives birth, she begins to breast-feed her child for a minute or two approximately every fifteen minutes. Around the clock. For the next three years. (Suddenly this doesn’t seem like such a hot idea after all, does it?) The young child is carried in a sling on the mother’s hip so he can nurse easily and frequently. At night, he sleeps near his mother and will nurse every so often without even waking her.
Consider the life history of a hunter-gatherer woman. She reaches puberty at about age thirteen or fourteen (a bit later than in our society). Soon she is pregnant. She nurses for three years, weans her child, has a few menstrual cycles, becomes pregnant again, and repeats the pattern until she reaches menopause. Think about it: over the course of her life span, she has perhaps two dozen periods. Contrast that with modern Western women, who typically experience hundreds of periods over their lifetime. Huge difference. The hunter-gatherer pattern, the one that has occurred throughout most of human history, is what you see in nonhuman primates.
Perhaps some of the gynecological diseases that plague modern westernized women have something to do with this activation of a major piece of physiological machinery hundreds of times when it may have evolved to be used only twenty times (MacDonald et al 1991). An example of this is probably endometriosis (having uterine lining thickening and sloughing off in places in the pelvis and abdominal wall where it doesn’t belong), which is more common among women with fewer pregnancies and who start at a later age. Remarkably, the same is now being reported in zoo animals who, because of the circumstances of their captivity, reproduce far less often than those in the wild (Vogel 2001).
Djerassi (1979). The politics of contraception
Konner & Worthman (1980). Nursing frequency, gonadal function, and birth spacing among !Kung hunter-gatherers
MacDonald et al (1991). Recurrent secretion of progesterone in large amounts: an endocrine/metabolic disorder unique to young women?
Vogel (2001). A fertile mind on wildlife conservation’s front lines
Chart-topping original movies have gone extinct. People have a lot of explanations for this, but they’re all incomplete because they don’t realize the same thing is happening everywhere. An oligopoly has conquered all of popular culture.
Gato, a scalable generalist agent that uses a single transformer with exactly the same weights to play Atari, follow text instructions, caption images, chat with people, control a real robot arm, and more.
How does literature evolve? One birth at a time. Contrary to belief that literature changes due to external events like 9/11, 54% of the style of literature is solely driven by when its popular authors were born. After their 20s, authors don’t change much.
The Backwards March of Christology is a theory of how Christian interpretations of Jesus evolved over time. In the earliest writings, many Christians seemed to view him as a human prophet elevated to divinity at his resurrection: “God fulfilled his promise by resurrecting Jesus, as also it is written in the second psalm, ‘You are my Son; today I have fathered you.” These views became more elaborate as the decades passed.