Our nutrition modulates our cognition.

A fascinating study from Strang et al.:

Food intake is essential for maintaining homeostasis, which is necessary for survival in all species. However, food intake also impacts multiple biochemical processes that influence our behavior. Here, we investigate the causal relationship between macronutrient composition, its bodily biochemical impact, and a modulation of human social decision making. Across two studies, we show that breakfasts with different macronutrient compositions modulated human social behavior. Breakfasts with a high-carbohydrate/protein ratio increased social punishment behavior in response to norm violations compared with that in response to a low carbohydrate/protein meal. We show that these macronutrient-induced behavioral changes in social decision making are causally related to a lowering of plasma tyrosine levels. The findings indicate that, in a limited sense, “we are what we eat” and provide a perspective on a nutrition-driven modulation of cognition. The findings have implications for education, economics, and public policy, and emphasize that the importance of a balanced diet may extend beyond the mere physical benefits of adequate nutrition.

Working memory isn’t just in the frontal lobes.

An inportant open access paper from Johnson et al.:

The ability to represent and select information in working memory provides the neurobiological infrastructure for human cognition. For 80 years, dominant views of working memory have focused on the key role of prefrontal cortex (PFC). However, more recent work has implicated posterior cortical regions, suggesting that PFC engagement during working memory is dependent on the degree of executive demand. We provide evidence from neurological patients with discrete PFC damage that challenges the dominant models attributing working memory to PFC-dependent systems. We show that neural oscillations, which provide a mechanism for PFC to communicate with posterior cortical regions, independently subserve communications both to and from PFC—uncovering parallel oscillatory mechanisms for working memory. Fourteen PFC patients and 20 healthy, age-matched controls performed a working memory task where they encoded, maintained, and actively processed information about pairs of common shapes. In controls, the electroencephalogram (EEG) exhibited oscillatory activity in the low-theta range over PFC and directional connectivity from PFC to parieto-occipital regions commensurate with executive processing demands. Concurrent alpha-beta oscillations were observed over parieto-occipital regions, with directional connectivity from parieto-occipital regions to PFC, regardless of processing demands. Accuracy, PFC low-theta activity, and PFC → parieto-occipital connectivity were attenuated in patients, revealing a PFC-independent, alpha-beta system. The PFC patients still demonstrated task proficiency, which indicates that the posterior alpha-beta system provides sufficient resources for working memory. Taken together, our findings reveal neurologically dissociable PFC and parieto-occipital systems and suggest that parallel, bidirectional oscillatory systems form the basis of working memory.

Cognitive control as a double-edged sword.

Amer et al. offer an implicit critique of the attention and resources dedicated to brain-training programs that aim to modify the cognitive performance of older adults to mirror that of younger adults, suggesting that reduced attentional control [on aging] can actually be beneficial in a range of cognitive tasks.

We elaborate on this idea using aging as a model of reduced control, and we propose that the broader scope of attention of older adults is well suited for tasks that rely less on top-down driven goals, and more on intuitive, automatic, and implicit-based learning. These tasks may involve learning statistical patterns and regularities over time, using accrued knowledge and experiences for wise decision-making, and solving problems by generating novel and creative solutions.

We review behavioral and neuroimaging evidence demonstrating that reduced control can enhance the performance of both older and, under some circumstances, younger adults. Using healthy aging as a model, we demonstrate that decreased cognitive control benefits performance on tasks ranging from acquiring and using environmental information to generating creative solutions to problems. Cognitive control is thus a double-edged sword – aiding performance on some tasks when fully engaged, and many others when less engaged.

I pass on the author's comments questioning the usefulness of brain training programs that seek to restore youth-like cognition:

Reduced cognitive control is typically seen as a source of cognitive failure. Brain-training programs, which form a growing multimillion-dollar industry, focus on improving cognitive control to enhance general cognitive function and moderate age-related cognitive decline. While several studies have reported positive training effects in both old and young adults, the efficacy and generalizability of these training programs has been a topic of increasing debate. For example, several reports have demonstrated a lack of far-transfer effects, or general improvement in cognitive function, as a result of cognitive training. In healthy older adults, in particular, a recent meta-analysis (which does not even account for unpublished negative results) showed small to non-existent training effects, depending on the training task and procedure, and other studies demonstrated a lack of maintenance and far-transfer effects. Moreover, even when modest intervention effects are reported, there is no evidence that these improvements influence the rate of cognitive decline over time.

Collectively, these results question whether interventions aimed at restoring youth-like levels of cognitive control in older adults are the best approach. One alternative to training is to take advantage of the natural pattern of cognition of older adults and capitalize on their propensity to process irrelevant information. A recent set of studies demonstrated that distractors can be used to enhance memory for previously or newly learned information in older adults. For example, one study illustrated that, unlike younger adults, older adults show minimal to no forgetting of words they learned on a previous memory task, when those words are presented again as distractors in a delay period between the initial and subsequent, surprise memory task. That is, exposure to distractors in the delay period served as a rehearsal episode to boost memory for previously learned information. Similarly, other studies showed that older adults show better learning for new target information that was previously presented as distraction. In one study, for example, older adults showed enhanced associative memory for faces and names (a task which typically shows large age deficits) when the names were previously presented as distractors on the same faces in an earlier task. Taken together, these findings suggest that greater gains may be made by interventions that capitalize on reduced control by designing environments or applications that enhance learning and memory through presentation of distractors.

Describing aging - metastability in senescence

Naik et al. suggest a whole brain computational modeling approach to understand how our brains maintain a high level of cognitive ability even as their structures deteriorate.

We argue that whole-brain computational models are well-placed to achieve this objective. In line with our dynamic hypothesis, we suggest that aging needs to be studied on a continuum rather than at discrete phases such as ‘adolescence’, ‘youth’, ‘middle-age’, and ‘old age’. We propose that these significant epochs of the lifespan can be related to shifts in the dynamical working point of the system. We recommend that characterization of metastability (wherein the state changes in the dynamical system occur constantly with time without a seeming preference for a particular state) would enable us to track the shift in the dynamical working point across the lifespan. This may also elucidate age-related changes in cognitive performance. Thus, the changing structure–function–cognition relationships with age can be conceptualized as a (new) normal response of the healthy brain in an attempt to successfully cope with the molecular, genetic, or neural changes in the physiological substrate that take place with aging, and this can be achieved by the exploration of the metastable behavior of the aging brain.

The authors proceed to illustrate structural and functional connectivity changes during aging, as white-matter fiber counts reduce, roles of hub, feeder and local connections change, and brain function becomes less modular. I want to pass on their nice description of the healthy aging brain:

Age differences in cognitive function have been studied to a great extent by both longitudinal and cross-sectional studies. While some cognitive functions − such as numerical and verbal skills, vocabulary, emotion processing, and general knowledge about the world − remain intact with age, other mental capabilities decline from middle age onwards: these mainly include episodic memory (ability to recall a sequence of events as they occurred), processing speed, working memory, and executive control. Age-related structural changes measured by voxel-based morphometry (VBM) studies have reported expansion of ventricles, global cortical thinning, and non-uniform trajectories of volumetric reduction of regional grey matter, mostly in the prefrontal and the medial temporal regions. While the degeneration of temporal–parietal circuits is often associated with pathological aging, healthy aging is often associated with atrophy of frontostriatal circuits. Network-level changes are measured indirectly by deriving covariance network of regional grey matter thickness or directly by diffusion weighted imaging methods which can reconstruct the white matter fiber tracts by tracking the diffusion of water molecules. These studies have revealed a linear reduction of white matter fiber counts across the lifespan. The hub architecture that helps in information integration remains consistent between young adults and elderly adults, but exhibits a subtle decrease in fiber lengths of connections between hub-to-hub and non-hub regions. The role of the frontal hub regions deteriorates more than that of other regions. The global and local measures of efficiency show a characteristic inverted U-shaped curve, with peak age in the third decade of life. While tractography-based studies report no significant trends in modularity across the lifespan, cortical network-based studies report decreased modularity in the elderly population. Functional changes derived from the level of BOLD signal of the fMRI during task and rest (i.e., in the absence of a task) demonstrate more-complex patterns such as task-dependent regional over-recruitment or reduced specificity. More interesting changes take place in functional networks determined by second-order linear correlations between regional BOLD time-series in the task-free condition. Modules in the functional brain networks represent groups of brain regions that are collectively involved in one or more cognitive domains. An age-related decrease in modularity, with increased inter-module connectivity and decreased intra-module connectivity, is commonly reported. Distinct modules that are functionally independent in young adults tend to merge into a single module in the elderly adults. Global efficiency is preserved with age, while local efficiency and rich-club index show inverted U-shaped curves with peak ages at around 30 years and 40 years, respectively. Patterns of functional efficiency across the cortex are not the same. Networks associated with primary functions such as the somatosensory and the motor networks maintain efficiency in the elderly, while higher-level processing networks such as the default mode network (DMN), frontoparietal control network (FPCN), and the cingulo-opercular network often show decline in efficiency. Any comprehensive aging theory requires an account of all these changes in a single framework.

The human fetus engages face like stimuli.

Reid et al. are able to show that we prefer face-like stimuli even in utero:

Highlights

•The third trimester human fetus looks toward three dots configured like a face 

•The human fetus does not look toward three inverted configuration dots 

•Postnatal experience of faces is not required for this predisposition 

•Projecting patterned stimuli through maternal tissue to the fetus is feasible

Summary

In the third trimester of pregnancy, the human fetus has the capacity to process perceptual information. With advances in 4D ultrasound technology, detailed assessment of fetal behavior is now possible. Furthermore, modeling of intrauterine conditions has indicated a substantially greater luminance within the uterus than previously thought. Consequently, light conveying perceptual content could be projected through the uterine wall and perceived by the fetus, dependent on how light interfaces with maternal tissue. We do know that human infants at birth show a preference to engage with a top-heavy, face-like stimulus when contrasted with all other forms of stimuli. However, the viability of performing such an experiment based on visual stimuli projected through the uterine wall with fetal participants is not currently known. We examined fetal head turns to visually presented upright and inverted face-like stimuli. Here we show that the fetus in the third trimester of pregnancy is more likely to engage with upright configural stimuli when contrasted to inverted visual stimuli, in a manner similar to results with newborn participants. The current study suggests that postnatal experience is not required for this preference. In addition, we describe a new method whereby it is possible to deliver specific visual stimuli to the fetus. This new technique provides an important new pathway for the assessment of prenatal visual perceptual capacities.

Neural measures reveal lower social conformity among non-religious individuals.

An interesting bit from Thiruchselvam et al.:

Even in predominantly religious societies, there are substantial individual differences in religious commitment. Why is this? One possibility is that differences in social conformity (i.e. the tendency to think and behave as others do) underlie inclination towards religiosity. However, the link between religiosity and conformity has not yet been directly examined. In this study, we tested the notion that non-religious individuals show dampened social conformity, using both self-reported and neural (EEG-based ERPs) measures of sensitivity to others’ influence. Non-religious vs religious undergraduate subjects completed an experimental task that assessed levels of conformity in a domain unrelated to religion (i.e. in judgments of facial attractiveness). Findings showed that, although both groups yielded to conformity pressures at the self-report level, non-religious individuals did not yield to such pressures in their neural responses. These findings highlight a novel link between religiosity and social conformity, and hold implications for prominent theories about the psychological functions of religion.

Maybe Trump’s behavior is explained by a simple Machine Learning (A.I.) algorithm.

Burton offers an intriguing explanation for our inability to predict Donald Trump’s next move suggesting:

...that Trump doesn’t operate within conventional human cognitive constraints, but rather is a new life form, a rudimentary artificial intelligence-based learning machine. When we strip away all moral, ethical and ideological considerations from his decisions and see them strictly in the light of machine learning, his behavior makes perfect sense.

Consider how deep learning occurs in neural networks such as Google’s Deep Mind or IBM’s Deep Blue and Watson. In the beginning, each network analyzes a number of previously recorded games, and then, through trial and error, the network tests out various strategies. Connections for winning moves are enhanced; losing connections are pruned away. The network has no idea what it is doing or why one play is better than another. It isn’t saddled with any confounding principles such as what constitutes socially acceptable or unacceptable behavior or which decisions might result in negative downstream consequences.

Now up the stakes…ask a neural network to figure out the optimal strategy…for the United States presidency. In this hypothetical, let’s input and analyze all available written and spoken word — from mainstream media commentary to the most obscure one-off crank pamphlets. After running simulations of various hypotheses, the network will serve up its suggestions. It might show Trump which areas of the country are most likely to respond to personal appearances, which rallies and town hall meetings will generate the greatest photo op and TV coverage, and which publicly manifest personality traits will garner the most votes. If it determines that outrage is the only road to the presidency, it will tell Trump when and where his opinions must be scandalous and offensively polarizing.

Following the successful election, it chews on new data. When it recognizes that Obamacare won’t be easily repealed or replaced, that token intervention in Syria can’t be avoided, that NATO is a necessity and that pulling out of the Paris climate accord may create worldwide resentment, it has no qualms about changing policies and priorities. From an A.I. vantage point, the absence of a coherent agenda is entirely understandable. For example, a consistent long-term foreign policy requires a steadfastness contrary to a learning machine’s constant upgrading in response to new data.

As there are no lines of reasoning driving the network’s actions, it is not possible to reverse engineer the network to reveal the “why” of any decision. Asking why a network chose a particular action is like asking why Amazon might recommend James Ellroy and Elmore Leonard novels to someone who has just purchased “Crime and Punishment.” There is no underlying understanding of the nature of the books; the association is strictly a matter of analyzing Amazon’s click and purchase data. Without explanatory reasoning driving decision making, counterarguments become irrelevant.

Once we accept that Donald Trump represents a black-box, first-generation artificial-intelligence president driven solely by self-selected data and widely fluctuating criteria of success, we can get down to the really hard question confronting our collective future: Is there a way to affect changes in a machine devoid of the common features that bind humanity?

Mechanism of adult brain changes caused by early life stress.

Peña et al., working with mice, demonstrate a mechanisms by which early life stress encodes lifelong susceptibility to stress by changing a reward region of adult brains that increases susceptibility to adult social defeat stress and depression-like behaviors. While early stress could establish the groundwork for later depression, this priming could be undone by intervention at the right moment. Their work suggests the relevance of follow up studies in humans compromised by early life stress to see whether similar genetic regulatory changes have occurred. Their abstract:

Early life stress increases risk for depression. Here we establish a “two-hit” stress model in mice wherein stress at a specific postnatal period increases susceptibility to adult social defeat stress and causes long-lasting transcriptional alterations that prime the ventral tegmental area (VTA)—a brain reward region—to be in a depression-like state. We identify a role for the developmental transcription factor orthodenticle homeobox 2 (Otx2) as an upstream mediator of these enduring effects. Transient juvenile—but not adult—knockdown of Otx2 in VTA mimics early life stress by increasing stress susceptibility, whereas its overexpression reverses the effects of early life stress. This work establishes a mechanism by which early life stress encodes lifelong susceptibility to stress via long-lasting transcriptional programming in VTA mediated by Otx2.

Positive trends over time in personality traits as well as in intelligence.

Jokela et al. add an interesting dimension to numerous studies that have shown a steady increase in people's intelligence over the past 100 years, concluding that there is a “Flynn effect” for personality that mirrors the original Flynn effect for cognitive ability. They document similar trends in economically valuable personality traits of young adult males, as measured by a standardized test:

Significance

The secular rise in intelligence across birth cohorts is one of the most widely documented facts in psychology. This finding is important because intelligence is a key predictor of many outcomes such as education, occupation, and income. Although noncognitive skills may be equally important, there is little evidence on the long-term trends in noncognitive skills due to lack of data on consistently measured noncognitive skills of representative populations of successive cohorts. Using test score data based on an unchanged test taken by the population of Finnish military conscripts, we find steady positive trends in personality traits that are associated with high income. These trends are similar in magnitude and economic importance to the simultaneous rise in intelligence.

Abstract

Although trends in many physical characteristics and cognitive capabilities of modern humans are well-documented, less is known about how personality traits have evolved over time. We analyze data from a standardized personality test administered to 79% of Finnish men born between 1962 and 1976 (n = 419,523) and find steady increases in personality traits that predict higher income in later life. The magnitudes of these trends are similar to the simultaneous increase in cognitive abilities, at 0.2–0.6 SD during the 15-y window. When anchored to earnings, the change in personality traits amounts to a 12% increase. Both personality and cognitive ability have consistent associations with family background, but the trends are similar across groups defined by parental income, parental education, number of siblings, and rural/urban status. Nevertheless, much of the trends in test scores can be attributed to changes in the family background composition, namely 33% for personality and 64% for cognitive ability. These composition effects are mostly due to improvements in parents’ education. We conclude that there is a “Flynn effect” for personality that mirrors the original Flynn effect for cognitive ability in magnitude and practical significance but is less driven by compositional changes in family background.

It's complicated....more on Sapolsky's new book.

In a recent MindBlog post I urged you to read Robert Sapolsky’s new book, "Behave - The Biology of Humans at Our Best and Worst." This was when I was only through the third chapter, and as usual being impressed with his style and clarity. I’ve finished the book. It is a quirky, irreverent, clear, and magisterial effort. I feel like he’s almost managed to condense the take home message from my ~4,200 MindBlog posts that have appeared since 2006 into one book. I want to pass on some of the items in the take home messages he offers in his epilogue, slightly re-ordering his list:

While it’s cool that there’s so much plasticity in the brain, it’s no surprise— it has to work that way.

Adolescence shows us that the most interesting part of the brain evolved to be shaped minimally by genes and maximally by experience; that’s how we learn— context, context, context.

Childhood adversity can scar everything from our DNA to our cultures, and effects can be lifelong, even multigenerational. However, more adverse consequences can be reversed than used to be thought. But the longer you wait to intervene, the harder it will be.

Brains and cultures coevolve.

Things that seem morally obvious and intuitive now weren’t necessarily so in the past; many started with nonconforming reasoning.

It’s great if your frontal cortex lets you avoid temptation, allowing you to do the harder, better thing. But it’s usually more effective if doing that better thing has become so automatic that it isn’t hard. And it’s often easiest to avoid temptation with distraction and reappraisal rather than willpower.

Repeatedly, biological factors (e.g., hormones) don’t so much cause a behavior as modulate and sensitize, lowering thresholds for environmental stimuli to cause it.

Cognition and affect always interact. What’s interesting is when one dominates.

Genes have different effects in different environments; a hormone can make you nicer or crummier, depending on your values; we haven’t evolved to be “selfish” or “altruistic” or anything else— we’ve evolved to be particular ways in particular settings. Context, context, context.

Biologically, intense love and intense hate aren’t opposites. The opposite of each is indifference.

Arbitrary boundaries on continua can be helpful. But never forget that they are arbitrary.

Often we’re more about the anticipation and pursuit of pleasure than about the experience of it.

You can’t understand aggression without understanding fear (and what the amygdala has to do with both).

Genes aren’t about inevitabilities; they’re about potentials and vulnerabilities. And they don’t determine anything on their own. Gene/ environment interactions are everywhere. Evolution is most consequential when altering regulation of genes, rather than genes themselves.

We implicitly divide the world into Us and Them, and prefer the former. We are easily manipulated, even subliminally and within seconds, as to who counts as each.

We aren’t chimps, and we aren’t bonobos. We’re not a classic pair-bonding species or a tournament species. We’ve evolved to be somewhere in between in these and other categories that are clear-cut in other animals. It makes us a much more malleable and resilient species. It also makes our social lives much more confusing and messy, filled with imperfection and wrong turns.

While traditional nomadic hunter-gatherer life over hundreds of thousands of years might have been a little on the boring side, it certainly wasn’t ceaselessly bloody. In the years since most humans abandoned a hunter-gatherer lifestyle, we’ve obviously invented many things. One of the most interesting and challenging is social systems where we can be surrounded by strangers and can act anonymously.

Saying a biological system works “well” is a value-free assessment; it can take discipline, hard work, and willpower to accomplish either something wondrous or something appalling. “Doing the right thing” is always context dependent.

Many of our best moments of morality and compassion have roots far deeper and older than being mere products of human civilization. Be dubious about someone who suggests that other types of people are like little crawly, infectious things.

When humans invented socioeconomic status, they invented a way to subordinate like nothing that hierarchical primates had ever seen before.

“Me” versus “us” (being prosocial within your group) is easier than “us” versus “them” (prosociality between groups).

It’s not great if someone believes it’s okay for people to do some horrible, damaging act. But more of the world’s misery arises from people who, of course, oppose that horrible act . . . but cite some particular circumstances that should make them exceptions. The road to hell is paved with rationalization.

The certainty with which we act now might seem ghastly not only to future generations but to our future selves as well.

Neither the capacity for fancy, rarefied moral reasoning nor for feeling great empathy necessarily translates into actually doing something difficult, brave, and compassionate.

People kill and are willing to be killed for symbolic sacred values. Negotiations can make peace with Them; understanding and respecting the intensity of their sacred values can make lasting peace.

We are constantly being shaped by seemingly irrelevant stimuli, subliminal information, and internal forces we don’t know a thing about.

Our worst behaviors, ones we condemn and punish, are the products of our biology. But don’t forget that the same applies to our best behaviors.

Individuals no more exceptional than the rest of us provide stunning examples of our finest moments as humans.

(The above quotes are taken from Sapolsky, Robert M. (2017-05-02). Behave: The Biology of Humans at Our Best and Worst (pp. 671-673). Penguin Publishing Group. Kindle Edition.)

Why it is impossible to tune a piano.

Here is a 'random curious stuff' item, per the MindBlog description above.  I want to pass on this great explanation of why physics requires that piano notes have to be slightly out of tune, except for the octave, resulting in the equal temperament tuning system most piano tuners use. I suggest you expand the video to full screen, and pause it occasionally to catch up with its rapid pace.
 

Sorting out complex thoughts and messy emotions

Here is a nice perky piece from Stephen Matheson, editor of Cell Reports, on the genetics of behavior, which I pass along in its entirety (references are in the link):

Cognition. Intelligence. Emotion. Sexuality. These are not merely complicated traits, invoking awed respect. These are aspects of animal life and human nature that are daunting in their biological complexity and in their existential importance. Curious biologists have been tackling animal behavior for centuries, but some topics and behaviors still remain opaque to biological understanding. While the demystification of human nature might give some unease, more of us are simply skeptical of any attempt to unravel the genetic underpinnings of such things.

For years now, genome-wide association studies (GWAS) have been mining ever-growing genetic datasets for clues to the genetic bases of complex traits and diseases that include behaviors and disabilities in cognition, intelligence, sexuality, social interaction, and emotion. Along with a few breakthroughs, there have been significant disappointments and legitimate questions about the limits of potential success (Visscher et al., 2012).

Some geneticists don’t seem to have gotten the memo.

Discussing the biology of human intelligence is a good way to start a scholarly brawl, and yet this complex trait is strongly heritable. Previous GWAS have found hints and candidates for causative genes, but the results are thought to be statistically underpowered. However, in May an international collaborative group published a large meta-analysis of data combined from these previous GWAS (and with new data), and reported 30 new and very promising candidate genes influencing human intelligence (Sniekers et al., 2017). By increasing the cohort (nearly 80,000 people) and using some new tools (such as MAGMA), the work substantially expanded the list of genetic players. One new candidate is FOXO3, a transcription factor involved in insulin/IGF signaling.

What of love? Shakespeare claimed that the course of true love never did run smooth, but geneticists recently claimed that assortative mating occurs in humans, meaning that humans tend to select mates that resemble themselves to some extent (Robinson et al., 2017). This operates phenotypically, separate from confounding influences (such as socialization), and has implications for human population genetics and evolution. Another recent report found 12 genes associated with human reproductive behavior, specifically age at first birth and number of children (Barban et al., 2016). Romantic.

Not even parenting practices are sacred. Hopi Hoekstra and her group study the evolution and genetics of behavior in closely related species of mice—the mice exhibit significant behavioral differences but can interbreed. This facilitates quantitative genetics and whole-genome analysis of behavioral traits. In a paper in April, the group reports on the genetics of parenting (Bendesky et al., 2017). Their tour de force showed heritability of a suite of parental behaviors (such as nest-making and baby-licking) and then dissected the genetic infrastructure. Even though the behaviors seem very similar in males and females, the underlying genetics can differ significantly. One behavior, nest-building, stands out, both because it seems genetically independent of other parenting tasks and because it has evolved through changes in the expression of vasopressin.

Quantitative genetics is bringing powerful tools to old questions, including some deemed sacred or hopelessly complex. More drama is certain to come. Be sure to get a good seat.

Dogs can know what you know.

Catela et al. offer evidence in dogs for theory of mind ability (recognizing that others have a different perspective, shown for humans, apes, and corvids). They show that dogs prefer to follow the pointing of a human who witnessed a food hiding event over a human who did not, and can distinguish two individuals who are showing identical looking behaviors, only one of which had the opportunity to see where the food was hidden by a third person. This perspective taking ability may occur more widely in the animal kingdom than previously supposed.

Currently, there is still no consensus about whether animals can ascribe mental states (Theory of Mind) to themselves and others. Showing animals can respond to cues that indicate whether another has visual access to a target or not, and that they are able to use this information as a basis for whom to rely on as an informant, is an important step forward in this direction. Domestic dogs (Canis familiaris) with human informants are an ideal model, because they show high sensitivity towards human eye contact, they have proven able to assess the attentional state of humans in food-stealing or food-begging contexts, and they follow human gaze behind a barrier when searching for food. With 16 dogs, we not only replicated the main results of Maginnity and Grace (Anim Cogn 17(6):1375–1392, 2014) who recently found that dogs preferred to follow the pointing of a human who witnessed a food hiding event over a human who did not (the Guesser–Knower task), but also extended this finding with a further, critical control for behaviour-reading: two informants showed identical looking behaviour, but due to their different position in the room, only one had the opportunity to see where the food was hidden by a third person. Preference for the Knower in this critical test provides solid evidence for geometrical gaze following and perspective taking in dogs.

Metabolic and physical decline that occurs during aging promoted by a DNA repair enzyme.

Damage to our DNA accumulates during our aging, and Park et al. show a link between this damage and the loss of metabolic function associated with physical decline and aging-associated diseases. They show that DNA breaks activate the repair promoting enzyme DNA-dependent protein kinase (DNA-PK) in skeletal muscle, but the kinase also suppresses mitochondrial function, energy metabolism, and physical fitness. A small-molecule inhibitor of DNA-PK improves the physical fitness of young obese mice and older mice. Whether there is therapeutic potential in such small inhibitors depends on whether inhibition of DNA repair has deleterious effects, such as increasing the potential for cancer. Here is the abstract:

Hallmarks of aging that negatively impact health include weight gain and reduced physical fitness, which can increase insulin resistance and risk for many diseases, including type 2 diabetes. The underlying mechanism(s) for these phenomena is poorly understood. Here we report that aging increases DNA breaks and activates DNA-dependent protein kinase (DNA-PK) in skeletal muscle, which suppresses mitochondrial function, energy metabolism, and physical fitness. DNA-PK phosphorylates threonines 5 and 7 of HSP90α, decreasing its chaperone function for clients such as AMP-activated protein kinase (AMPK), which is critical for mitochondrial biogenesis and energy metabolism. Decreasing DNA-PK activity increases AMPK activity and prevents weight gain, decline of mitochondrial function, and decline of physical fitness in middle-aged mice and protects against type 2 diabetes. In conclusion, DNA-PK is one of the drivers of the metabolic and fitness decline during aging, and therefore DNA-PK inhibitors may have therapeutic potential in obesity and low exercise capacity.

A conclusion from one of my lectures.

While mulling over possible topics I might develop for a next lecture, I have looked back over previous efforts on dericbownds.net and found several bits of text that I like. I'm pasting in below the concluding paragraphs from my Lecture/Web Lecture "Upstairs/Downstairs in our Brain - What's running our show?"

I would submit that those mind therapies, meditations, or exercises that are the most effective in generating new more functional behaviors are those that come close to resolving what we could call the category error (in the spirit of the philosophical term) in considering mind and brain. And, that error is to confuse a product with its source, the source being the fundamental impersonal downstairs machinery that generates the varieties of functional or dysfunctional selves that are its product, that we mistakenly imagine ourselves to be. Mental exercises like meditation permit the intuition of, perhaps come closest to, that more refined metacognitive underlying generative space that permits viewing of, and choice between, more or less functional self options.

A less wordy, maybe more useful, way of putting this is to say that third person introspection, viewing yourself as if looking at another actor, and placing this a historical story line, is more useful than immersed rumination (coulda, shoulda, woulda). It is the difference between residing mainly in the attentional versus default modes of cognition.

If there is a practical take-home message, it is that maintaining awareness of, and exercising, focused upstairs frontal attentional mechanisms is important to mental vitality and longevity. Such awareness is central in resisting the attacks on our attentional competence that comes from the confusing media jungle that tempts our passive default mode receptivity and reactivity.

Some outstanding books on the biology of our behaviors.

If you are wanting to find a humorous, fascinating, engaging, authoritative account of why we humans behave the way we do, you should immediately buy a copy of Robert Sapolsky's new book, "Behave - The Biology of Humans at Our Best and Worst." I've been a fan of Sapolsky ever since reading his "Why Zebras don't get Ulcers," whose 3rd edition dates to 2004. His writing has a flexibility, lightness and sense of humor that I wish I could even begin to emulate. I'm only up to the third chapter (of 17), and wish I could suspend all my other activities and read this book. I'm familiar with virtually all of the material he presents, but I could never present it with his clarity and lucid organization.

Another book I want to make a positive comment about is Richard Haier's "The Neuroscience of Intelligence," part of the Cambridge Fundamentals of Neuroscience in Psychology series. It is a bit more academic and weighty, beginning by dispelling popular misinformation on intelligence and then describing how it is defined and measured for scientific research. The book reviews evidence for the importance of genetics and epigenetics, and has chapters that do a nice synthesis of neuroimaging and other new technologies. The final two chapters focus on approaches to enhancing intelligence, and also how intelligence research may inform education policies.

Finally, I want to mention a book by Ken Richardson, "Genes, Brains, and Human Potential," that discusses how the ideology of human intelligence has infiltrated genetics,  brain science, and psychology, so that (from the dust jacket) "ideology, more than pure science, has come to dominate our institutions, especially education, encouraging fatalism about the development of human intelligence among individuals and societies. Build on work being done in molecular biology, epigenetics, dynamical systems, evolution theory, and complexity theory, Richardson maps a fresh understanding of intelligence and the development of human potential informed by a more complete and nuanced understanding of both ideology and science."

Watching our brains construct linguistic phrases

From Nelson et al.:

Significance

According to most linguists, the syntactic structure of sentences involves a tree-like hierarchy of nested phrases, as in the sentence [happy linguists] [draw [a diagram]]. Here, we searched for the neural implementation of this hypothetical construct. Epileptic patients volunteered to perform a language task while implanted with intracranial electrodes for clinical purposes. While patients read sentences one word at a time, neural activation in left-hemisphere language areas increased with each successive word but decreased suddenly whenever words could be merged into a phrase. This may be the neural footprint of “merge,” a fundamental tree-building operation that has been hypothesized to allow for the recursive properties of human language.

Abstract

Although sentences unfold sequentially, one word at a time, most linguistic theories propose that their underlying syntactic structure involves a tree of nested phrases rather than a linear sequence of words. Whether and how the brain builds such structures, however, remains largely unknown. Here, we used human intracranial recordings and visual word-by-word presentation of sentences and word lists to investigate how left-hemispheric brain activity varies during the formation of phrase structures. In a broad set of language-related areas, comprising multiple superior temporal and inferior frontal sites, high-gamma power increased with each successive word in a sentence but decreased suddenly whenever words could be merged into a phrase. Regression analyses showed that each additional word or multiword phrase contributed a similar amount of additional brain activity, providing evidence for a merge operation that applies equally to linguistic objects of arbitrary complexity. More superficial models of language, based solely on sequential transition probability over lexical and syntactic categories, only captured activity in the posterior middle temporal gyrus. Formal model comparison indicated that the model of multiword phrase construction provided a better fit than probability-based models at most sites in superior temporal and inferior frontal cortices. Activity in those regions was consistent with a neural implementation of a bottom-up or left-corner parser of the incoming language stream. Our results provide initial intracranial evidence for the neurophysiological reality of the merge operation postulated by linguists and suggest that the brain compresses syntactically well-formed sequences of words into a hierarchy of nested phrases.

Brain-to-Brain symmetry tracks classroom interactions.

From Dikker et al.:

Highlights

•We report a real-world group EEG study, in a school, during normal class activities 

•EEG was recorded from 12 students simultaneously, repeated over 11 sessions 

•Students’ brain-to-brain group synchrony predicts classroom engagement 

•Students’ brain-to-brain group synchrony predicts classroom social dynamics

Summary

The human brain has evolved for group living. Yet we know so little about how it supports dynamic group interactions that the study of real-world social exchanges has been dubbed the “dark matter of social neuroscience”. Recently, various studies have begun to approach this question by comparing brain responses of multiple individuals during a variety of (semi-naturalistic) tasks. These experiments reveal how stimulus properties, individual differences, and contextual factors may underpin similarities and differences in neural activity across people. However, most studies to date suffer from various limitations: they often lack direct face-to-face interaction between participants, are typically limited to dyads, do not investigate social dynamics across time, and, crucially, they rarely study social behavior under naturalistic circumstances. Here we extend such experimentation drastically, beyond dyads and beyond laboratory walls, to identify neural markers of group engagement during dynamic real-world group interactions. We used portable electroencephalogram (EEG) to simultaneously record brain activity from a class of 12 high school students over the course of a semester (11 classes) during regular classroom activities. A novel analysis technique to assess group-based neural coherence demonstrates that the extent to which brain activity is synchronized across students predicts both student class engagement and social dynamics. This suggests that brain-to-brain synchrony is a possible neural marker for dynamic social interactions, likely driven by shared attention mechanisms. This study validates a promising new method to investigate the neuroscience of group interactions in ecologically natural settings.

Our mental models predict emotion transitions.

Thornton and Tamir (open source) demonstrate that we use mental models to allow us to predict, during a currently perceived emotion in another person, the next one or two emotional transition that person is likely to undergo.

Significance

People naturally understand that emotions predict actions: angry people aggress, tired people rest, and so forth. Emotions also predict future emotions: for example, tired people become frustrated and guilty people become ashamed. Here we examined whether people understand these regularities in emotion transitions. Comparing participants’ ratings of transition likelihood to others’ experienced transitions, we found that raters’ have accurate mental models of emotion transitions. These models could allow perceivers to predict others’ emotions up to two transitions into the future with above-chance accuracy. We also identified factors that inform—but do not fully determine—these mental models: egocentric bias, the conceptual properties of valence, social impact, and rationality, and the similarity and co-occurrence between different emotions.

Abstract

Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

A chemical link between early life stress and adult schizophrenia

A massive collaboration finds that schizophrenia-like symptoms induced by early life stress in mice correlates with expression of a DNA altering enzyme. Inhibition of that enzyme (whose levels are also increased in human patients with early life stress) reduces schizophrenia-like symptoms:

Significance

Early life stress (ELS) is an important risk factor for schizophrenia. Our study shows that ELS in mice increases the levels of histone-deacetylase (HDAC) 1 in brain and blood. Although altered Hdac1 expression in response to ELS is widespread, increased Hdac1 levels in the prefrontal cortex are responsible for the development of schizophrenia-like phenotypes. In turn, administration of an HDAC inhibitor ameliorates ELS-induced schizophrenia-like phenotypes. We also show that Hdac1 levels are increased in the brains of patients with schizophrenia and in blood from patients who suffered from ELS, suggesting that the analysis of Hdac1 expression in blood could be used for patient stratification and individualized therapy.

Abstract

Schizophrenia is a devastating disease that arises on the background of genetic predisposition and environmental risk factors, such as early life stress (ELS). In this study, we show that ELS-induced schizophrenia-like phenotypes in mice correlate with a widespread increase of histone-deacetylase 1 (Hdac1) expression that is linked to altered DNA methylation. Hdac1 overexpression in neurons of the medial prefrontal cortex, but not in the dorsal or ventral hippocampus, mimics schizophrenia-like phenotypes induced by ELS. Systemic administration of an HDAC inhibitor rescues the detrimental effects of ELS when applied after the manifestation of disease phenotypes. In addition to the hippocampus and prefrontal cortex, mice subjected to ELS exhibit increased Hdac1 expression in blood. Moreover, Hdac1 levels are increased in blood samples from patients with schizophrenia who had encountered ELS, compared with patients without ELS experience. Our data suggest that HDAC1 inhibition should be considered as a therapeutic approach to treat schizophrenia.