Self regulation of brain areas underlying our emotional arousal.

Our body arousal is controlled by very ancient nerve centers deep inside our brains. I am quite clear that for myself and many others these areas have ramped up their activity in response to the political uncertainty surrounding us. I would like to understand and regulate this arousal in myself more effectively. Thus I have been fascinated by the article by Sabat et al. in the Feb. 3 issue of PNAS that uses uses natural language processing tools to define the 7 chief varieties of arousal, and then runs meta-analyses of the brain imaging literature to reveal that all varieties of arousal converge onto a cortical network composed of the presupplementary motor area and the left and right dorsal anterior insula.

This suggests that biofeedback or meditation techniques that reduce activity in these brain areas might be useful in allowing us to face adversity without unnecessary levels of arousal. In this vein, the same issue of PNAS has an article by Maher et al.   demonstrating the potential of using loving-kindness meditation (by novice meditators) to induce neural changes in beta and gamma activity in the amygdala and hippocampus - areas associated with emotional regulation and mood disorders.

Below, I pass on the abstracts of these two articles:

The Sabat  et al. article has the title "Evidence for domain-general arousal from semantic and neuroimaging meta-analyses reconciles opposing views on arousal" :

Significance

Arousal is a central concept linking brain and body, often put forward to explain motivated behavior. Although the term is widely used, its definition remains elusive, with diverging views in classical textbooks. Is arousal an abstraction of the mind reflecting a myriad of distinct biological processes, or is there some common neuronal feature? We used large-scale text mining methods and neuroimaging meta-analyses to reveal the existence of domain-general arousal, a cortical process shared by situations as different as a cognitive task, an emotional context, the transition to wakefulness or sexual behavior, involving notably a specific area of the anterior insula in humans. Our results pave the way for refined taxonomies of arousal, where concepts and neural data are well aligned.

Abstract

Arousal refers to changes in brain-body state underpinning motivated behavior but lacks a proper definition and taxonomy. Neuroscience and psychology textbooks offer surprisingly different views on what arousal is, from a global brain-wide modulation of neuronal activity to a multidimensional construct, with specific brain-body patterns tuned to a given situation. The huge number of scientific articles mentioning arousal (~50,000) highlights the importance of the concept but also explains why such a vast literature has never been systematically reviewed so far. Here, we leverage the tools of natural language processing to probe the nature of arousal in a data-driven, comprehensive manner. We show that arousal comes in seven varieties: cognitive, emotional, physiological, sexual, related to stress disorders, to sleep, or to sleep disorders. We then ask whether domain-general arousal exists at the cortical level, and run meta-analyses of the brain imaging literature to reveal that all varieties of arousal, except arousal in sleep disorders for lack of data, converge onto a cortical network composed of the presupplementary motor area and the left and right dorsal anterior insula. More precisely, we find that activity in dysgranular insular area 7 (Jülich atlas), the region with the highest convergence across varieties of arousal, is also specifically associated with arousal. The domain-general arousal network might trigger the reorganization of large-scale brain networks—a global mechanism—resulting in a context-specific configuration—in line with the multidimensional view. Future taxonomies of arousal refining the alignment between concepts and data should include domain-general arousal as a central component.

**********************************

The Maher et al. article has the title: "Intracranial substrates of meditation-induced neuromodulation in the amygdala and hippocampus" 

Significance

We leverage rare chronic, invasive electrophysiology recordings while participants engage in loving-kindness meditation to demonstrate that meditation induces neural changes in beta and gamma activity in the amygdala and hippocampus of novice meditators. These results build on previous findings in experienced meditators and reveal meditation’s potential for noninvasive neuromodulation of brain activity associated with emotional regulation and mood disorders.

Abstract

Meditation is an accessible mental practice associated with emotional regulation and well-being. Loving-kindness meditation (LKM), a specific subtype of meditative practice, involves focusing one’s attention on thoughts of well-being for oneself and others. Meditation has been proven to be beneficial in a variety of settings, including therapeutic applications, but the neural activity underlying meditative practices and their positive effects are not well understood. It has been difficult to understand the contribution of deep limbic structures given the difficulty of studying neural activity directly in the human brain. Here, we leverage a unique patient population, epilepsy patients chronically implanted with responsive neurostimulation devices that allow chronic, invasive electrophysiology recording to investigate the physiological correlates of LKM in the amygdala and hippocampus of novice meditators. We find that LKM-associated changes in physiological activity were specific to periodic, but not aperiodic, features of neural activity. LKM was associated with an increase in γ (30 to 55 Hz) power and an alternation in the duration of β (13 to 30 Hz) and γ oscillatory bursts in both the amygdala and hippocampus, two regions associated with mood disorders. These findings reveal the nature of LKM-induced modulation of limbic activity in first-time meditators.

 

Evidence for a 'Theory of Mind' in Bonobo Chimps - they attribute knowledge or ignorance to social partners

 Interesting work from Rownrow and Krupenye (open source):

Numerous uniquely human phenomena, from teaching to our most complex forms of cooperation, depend on our ability to tailor our communication to the knowledge and ignorance states of our social partners. Despite four decades of research into the “theory of mind” capacities of nonhuman primates, there remains no evidence that primates can communicate on the basis of their mental state attributions, to enable feats of coordination. Moreover, recent reevaluation of the experimental literature has questioned whether primates can represent others’ ignorance at all. The present preregistered study investigated whether bonobos are capable of attributing knowledge or ignorance about the location of a hidden food reward to a cooperative human partner, and utilizing this attribution to modify their communicative behavior in the service of coordination. Bonobos could receive a reward that they had watched being hidden under one of several cups, if their human partner could locate the reward. If bonobos can represent a partner’s ignorance and are motivated to communicate based on this mental state attribution, they should point more frequently, and more quickly, to the hidden food’s location when their partner is ignorant about that location than when he is knowledgeable. Bonobos indeed flexibly adapted the frequency and speed of their communication to their partner’s mental state. These findings suggest that apes can represent (and act on) others’ ignorance in some form, strategically and appropriately communicating to effectively coordinate with an ignorant partner and change his behavior.

How complex brains and cognition first arose

I have received a draft of an upcoming paper in Behavioral and Brain Sciences by Coombs and Trestman titled "A Multi-Trait Embodied Framework for the Evolution of Brains and Cognition across Animal Phyla "  It has a nice graphic indicating different brain regions whose functionalities are common to humans and phylogenetically different animals with complex brains  (crows, octopuses and honeybees).  Motivated readers can obtain a PDF of the article from me.  Here is the abstract :

Among non-human animals, crows, octopuses and honeybees are well-known for their complex brains and cognitive abilities. Widening the lens from the idiosyncratic abilities of exemplars like these to those of animals across the phylogenetic spectrum begins to reveal the ancient evolutionary process by which complex brains and cognition first arose in different lineages. The distribution of 35 phenotypic traits in 17 metazoan lineages reveals that brain and cognitive complexity in only three lineages (vertebrates, cephalopod mollusks, and euarthropods) can be attributed to the pivotal role played by body, sensory, brain and motor traits in active visual sensing and visuomotor skills. Together, these pivotal traits enabled animals to transition from largely reactive to more proactive behaviors, and from slow and two-dimensional motion to more rapid and complex three-dimensional motion. Among pivotal traits, high-resolution eyes and laminated visual regions of the brain stand out because they increased the processing demands on and the computational power of the brain by several orders of magnitude. The independent acquisition of pivotal traits in cognitively complex (CC) lineages can be explained as the completion of several multi-trait transitions over the course of evolutionary history, each resulting in an increasing level of complexity that arises from a distinct combination of traits. Whereas combined pivotal traits represent the highest level of complexity in CC lineages, combined traits at lower levels characterize many non-CC lineages, suggesting that certain body, sensory and brain traits may have been linked (the trait-linkage hypothesis) during the evolution of both CC and non-CC lineages.

Accepting being alone

Another cryptic clip from my personal journal: .

To make feeling alone (all-one) be a comfortable space, be a courteous guest in one's own strange body and in the presence of the strange bodies of even closest friends, being gently curious about them, realizing that everything "I" think about myself or them is a fantasy construction for predicting what I or they might feel or do next.  

 

 

Life sets off a cascade of machines

A fascinating PNAS article by Tiusty and Libchaber offers 'an oversimplified language of life.’ It is a long article, but I found it a very worthwhile read. (Motivated readers can obtain a PDF of the article from me.) Here I pass on the Significance and Abstract paragraphs, and the first figure. 

Significance

This paper follows an idea by Leibniz that life can be seen as an infinite cascade of machine-making machines, down to atomic machines. It proposes an oversimplified language of life, highlighting certain scaling aspects and the key step of self-reproduction, with a singular point at one micron and a thousand seconds.  (click on figure to enlarge)

 

Abstract

Life is invasive, occupying all physically accessible scales, stretching between almost nothing (protons, electrons, and photons) and almost everything (the whole biosphere). Motivated by seventeenth-century insights into this infinity, this paper proposes a language to discuss life as an infinite double cascade of machines making machines. Using this simplified language, we first discuss the micro-cascade proposed by Leibniz, which describes how the self-reproducing machine of the cell is built of smaller submachines down to the atomic scale. In the other direction, we propose that a macro-cascade builds from cells larger, organizational machines, up to the scale of the biosphere. The two cascades meet at the critical point of 10³ s in time and 1 micron in length, the scales of a microbial cell. We speculate on how this double cascade evolved once a self-replicating machine emerged in the salty water of prebiotic earth.

 

 

 

 

The perceptual primacy of feeling

A fascinating perspective from Conwell et al. (open source). Affectless visual machines explain a majority of variance in human visually evoked affect: 

Significance

Human visual experience is defined not only by the light reflecting on our eyes (sensation), but by the feelings (affect) we feel concurrently. Psychological theories about where these feelings come from often focus mostly on the role of changes in our bodily states (physiology) or on our conscious thoughts about the things we are seeing (cognition). Far less frequently do these theories focus on the role of seeing itself (perception). In this research, we show that machine vision systems—which have neither bodily states nor conscious thoughts—can predict with remarkable accuracy how humans will feel about the things they look at. This suggests that perceptual processes (built on rich sensory experiences) may shape what we feel about the world around us far more than many psychological theories suggest.

Abstract

Looking at the world often involves not just seeing things, but feeling things. Modern feedforward machine vision systems that learn to perceive the world in the absence of active physiology, deliberative thought, or any form of feedback that resembles human affective experience offer tools to demystify the relationship between seeing and feeling, and to assess how much of visually evoked affective experiences may be a straightforward function of representation learning over natural image statistics. In this work, we deploy a diverse sample of 180 state-of-the-art deep neural network models trained only on canonical computer vision tasks to predict human ratings of arousal, valence, and beauty for images from multiple categories (objects, faces, landscapes, art) across two datasets. Importantly, we use the features of these models without additional learning, linearly decoding human affective responses from network activity in much the same way neuroscientists decode information from neural recordings. Aggregate analysis across our survey, demonstrates that predictions from purely perceptual models explain a majority of the explainable variance in average ratings of arousal, valence, and beauty alike. Finer-grained analysis within our survey (e.g. comparisons between shallower and deeper layers, or between randomly initialized, category-supervised, and self-supervised models) point to rich, preconceptual abstraction (learned from diversity of visual experience) as a key driver of these predictions. Taken together, these results provide further computational evidence for an information-processing account of visually evoked affect linked directly to efficient representation learning over natural image statistics, and hint at a computational locus of affective and aesthetic valuation immediately proximate to perception.

 

The Coup has already happened.

It's a Coup! 

Go to dogegov.com and click on articles in the drop down menu to learn about our new masters.  

Even more cheerful reading....on civilizational war and oligarchic technocracy.

I hesitate to add to the ongoing flow of negativity in the infosphere,  but I will pass on my edited ChatGPT 4o summaries of articles by Venkatesh Rao and Timothy Snyder.  I think they describe our situation in appropriately dire terms.

Rao argues that contemporary U.S. politics has shifted from a “culture war” to a “civilizational war,” and suggests that Trump and Musk’s faction has undergone this shift by becoming more disciplined and warlike, while Democrats remain stuck in an outdated, ineffective culture-war mode. Unlike culture wars, which are low-intensity conflicts centered on optics and social skirmishes, civilizational wars resemble historical steppe-nomad conquests—high-tempo, ruthless, and strategically destructive. The piece draws parallels to the 30 Years’ War and Mongol tactics, suggesting that modern “warriors” operate in a decentralized, open-source insurgency mode, using social media as a kind of continuous intoxication (akin to fermented mare’s milk for nomads) to stay engaged and aggressive. The author critiques mainstream political analysis for misunderstanding this shift, misinterpreting legal checks and media discourse as signs of normalcy rather than symptoms of deeper conflict. Ultimately, they suggest this is a negative-sum war that cannot be stopped, only mitigated.

Snyder describes the U.S. ias undergoing an oligarchic coup aimed at dismantling democracy and concentrating power among a wealthy elite. It asserts that the current executive branch rejects the idea of America as a nation governed by its people and instead seeks to create disorder to strengthen its control. The systematic discrediting of government institutions, demonization of federal workers, and elevation of billionaires as heroes have paved the way for this takeover. The destruction is intentional, with no plan to govern—only to create chaos that justifies authoritarian rule. The author likens Trump’s tariffs, attacks on allies, and deportation spectacles to deliberate strategies designed to impoverish, divide, and weaken Americans while enriching a select few. The removal of experienced officials in law enforcement and intelligence, under the guise of ideological purges, aims to eliminate those who could resist lawlessness. The article warns that unless citizens act decisively—through legal challenges, state-level resistance, impeachment efforts, and corporate pushback—the country will descend into an anti-democratic system where oligarchs manipulate markets and power unchecked. The call to action is urgent: people must organize, resist demoralization, and recognize that self-governance requires collective action beyond just voting.

 

We are towers of fantasies

Another cryptic clip from my personal journal:

We are built of predictive fantasies at every level of our being - from single cells up through transient professional identities that seamlessly feedback down into and vitalize the physical body and nervous system that sustains them. We make each identity for ourselves by inferring what models are being performed by others, hopefully not doing total mimesis of one style, but rather cutting and pasting to come up with our own ‘unique’ personas.

Structural and Cognitive Mechanisms of Group Cohesion in Primates

I pass on the abstract of a draft version of a new article by Robin Dunbar that I am reading through. It will appear in Behavioral and Brain Sciences. Motivated readers can obtain a PDF of the article by emailing me. 

Group-living creates stresses that, all else equal, naturally lead to group fragmentation, and hence loss of the benefits that group-living provides. How species that live in large stable groups counteract these forces is not well understood. I use comparative data on grooming networks and cognitive abilities in primates to show that living in large, stable groups has involved a series of structural solutions designed to create chains of 'friendship' (friends-of-friends effects), increased investment in bonding behaviours (made possible by dietary adjustments) to ensure that coalitions work effectively, and neuronally expensive cognitive skills of the kind known to underpin social relationships in humans. The first ensures that individuals synchronise their activity cycles; the second allows the stresses created by group-living to be defused; and the third allows a large number of weak ties to be managed. Between them, these create a form of multilevel sociality based on strong versus weak ties similar to that found in human social networks. In primates, these strategies appear successively at quite specific group sizes, suggesting that they are solutions to 'glass ceilings' that would otherwise limit the range of group sizes that animals can live in (and hence the habitats they can occupy). This sequence maps closely onto the grades now known to underpin the Social Brain Hypothesis and the fractal pattern that is known to optimise information flow round networks. 

A human machine writes

Scanning back through previous MindBlog posts, I came across the following paragraph what I wrote and posted on 7/24/24. I like it, and decided to post it again:

Machinery here, pushing down keys of another machine, generating words, just like a human does. Much simpler than pretending to be one. Just nerves, muscles, and energy fluxes in and out. Curatorial rather than aspirational. Cooperating with other similar machines to make larger ensembles more effective at survival and replication. Generating a word cloud stored in higher brain areas to fabricate the value, purpose, and meaning myths that sometimes strengthen and sometimes diminish the downstairs animal presence generating them.

“Now Is the Time of Monsters”

I pass on links to two articles in the same vein, one by Ezra Klein, the other by Ventkatesh Rao, with Klein noting how we are facing four epoch-changing events, any one of which could utterly change the world we have know for the past 70 years.  Both articles cite the writing of the Marxist Italian philosopher Antonio Gramsci, who wrote a well know sentence usually translated as “The old world is dying, and the new world struggles to be born: Now is the time of monsters.”  Rao offers the following graphic of the transition:

 

Klein points to:
1. Authoritarian consolidation across the world and the death of democracies.
2. The poorly understood large language models of AI exponentially approaching problem solving and general intelligence capabilities that may exceed human abilities
3. whose hardware has voracious energy requirements that act against curing the global warming that is irreversibly changing our planet.
4.  Population collapse due to lowering birthrates presenting a larger immediate threat to civilization than global warming.

And Rao dissects the fine structures of the interregnum noted by Gramsci's original phrase "...in this interregnum a great variety of morbid symptoms appear."  Rao notes "an interesting idea that a "monster" is an instance of "morbid symptoms" appearings in either or both of the two building blocks of "world" - systems of rules and special people."

 

Tokens of sanity

I repeat my September 29, 2024 "Tokens of sanity" post with a few edits: 

  

-Being the calm space in which nothing can hurry

-An animal body that can dissociate itself from the word cloud and emotional reactivities of self and other selves.

-A courteous guest in its own body, and when with others, owning its own experience and letting others own theirs.

-Favoring reflectivity over reactivity, caressing novelty

-Clinging to nothing, the current self being a passing fantasy

-Letting each moment be what it is, not what it should be

-A blip in the flow of cosmic time

Everything we experience comes from inside

I pass on this cryptic paragraph from my personal journal:

Everything we experience is coming from inside us - our illusion of having a self, our sense of agency. This includes attributing causal agency to others, as in  'they are making me do this,’  This 'error' allows individuals in a kinship group or tribe who share the same error to form an imaginary 'we' hive mind supporting unified action. The higher metacognitive stance is to participate when necessary in the group illusion while maintaining clarity on the fact that the actual agency is within oneself.

 

Regions of our brains making multiple predictions of others' actions.

I want to point to an excellent review and summary by Lin and Wittmann in Trends in Neurosciences of work by Ma et al. in J.Neurosci. (both are open source texts) that deal with the role of evolutionarily younger primate cortical brain regions - such as posterior cingulate cortex and medial preforntal cortex - in social belief inference. Such combined modeling and imaging studies are revealing in greater and greater detail the anatomical correlates of social cognition strategies.  Here is the significance statement from the Ma et al. article:

In daily life, to adjust our decisions, we constantly predict others’ choices, but the inherent uncertainty means we face multiple scenarios for different choices by others. Using computational modeling-based fMRI, we identified a network in three-stage computations for such decision-making. Amygdala signals represent predictions of others’ choices. These signals then interact with the posterior cingulate cortex and dorsolateral prefrontal cortex, representing the decision variables with the prediction of others’ likely and unlikely choices, respectively. Finally, these signals modulate the medial prefrontal cortex, influencing our final choices. These pivotal variables and their corresponding brain signals play a fundamental role in a broad range of social cognitive processes. Our findings shed light on underlying mechanisms for complex social interactions in human behavior.

How much does language shape our thinking?

I want to pass on this link to Manvir Singh's article in The New Yorker which has the title of this post.  I enjoyed reading the article. 

Also, I've been comparing the responses of LLMs  (Chat GPT 4o, Perplexity, Anthropic, Gemini) to the very simple prompt:  "Please summarize the following essay with the title: ......".  I'm frequently finding the Perplexity response most useful. It provides a list of steps it is following and HTML links to the sources it is using.  I estimate it would take me at least 30 min to prepare a summary of similar quality to the following Perplexity summary of the Singh article:

The essay explores the profound question of how language shapes human thought, examining cultural, cognitive, and social dimensions of this relationship.

Key Themes and Arguments:

 1. Language as Empowerment: The essay opens with the story of Angrezi Devi, the “Goddess English,” created by Dalit writer Chandra Bhan Prasad in India to symbolize the liberating potential of English for marginalized communities. Prasad argues that English offers Dalits a pathway out of caste oppression, contrasting it with Hindi, which he sees as reinforcing caste biases. 

2. Global Dominance of English: English is highlighted as the world’s dominant lingua franca, used in international institutions and pursued globally for its economic and social opportunities. However, its spread is accompanied by concerns about cultural homogenization and “cognitive hegemony,” where English’s structures might shape thought in ways aligned with Western norms. 

3. Linguistic Relativity and Whorfianism: The essay revisits Benjamin Lee Whorf’s theory that language influences thought, contrasting “strong Whorfianism” (language determines thought) with “weak Whorfianism” (language subtly shapes cognition). Examples include studies showing how Russian speakers distinguish shades of blue more effectively than English speakers due to their language’s lexical distinctions. 

 4. Cultural Variations in Cognition: Research reveals striking differences in how languages shape perceptions of time, space, and sensory experiences. For instance: • Aymara speakers conceptualize time with the past “in front” and the future “behind,” reflecting their linguistic metaphors. • Jahai speakers possess a rich vocabulary for smells, unlike English speakers who struggle to describe odors abstractly. 

5. Critiques and Nuances: While critics like Steven Pinker dismiss extreme Whorfian claims as overblown, recent research supports nuanced effects of language on cognition. Language influences attention, memory, and problem-solving in culturally specific ways but does not wholly dictate thought. 

6. Language Evolution and Adaptation: The essay emphasizes that languages evolve to reflect local contexts. For example, Indian English integrates native linguistic features like honorifics and unique phrases, showing how English adapts to diverse cultural environments rather than imposing uniformity.

Conclusion:
The essay concludes that while language profoundly influences thought, this relationship is dynamic and bidirectional. Languages shape how we perceive the world, but human cognition also transforms languages over time. Linguistic diversity is celebrated as a testament to humanity’s ingenuity and adaptability.

The birth of aspirational multiethnic populism

I have pulled some clips from an excellent substack piece by Yascha Mounk to cement and archive his main points for myself and also pass on to MindBlog readers.  He points out that Trump won a more convincing victory in 2024 than 2016…

…by doing what academics are supposed to be expert in: recognizing that the popular understanding of some concept—in this case, populism—is actually constituted by two elements which are logically separable. In his more recent incarnation, Trump has held on to his disdain for longstanding norms and his populist belief in the unfettered prerogative of the majority. But he has also made more explicit than in the past that his political vision is open to supporters from every ethnic and religious group—and has been very shrewd in courting them with an aspirational vision of America.

Though the term is much-overused and often misapplied, the concept of populism remains the most accurate frame for understanding his actions: He believes that, as the rightful voice of the people, he should not suffer any artificial restrictions on his actions—whether by unwritten norms or by explicit limits on the powers of a president.
 
He took evident pleasure in the fact that he owes his victory in large part to his growing popularity among Hispanics, Asian-Americans and African-Americans. He explicitly thanked those demographic groups for their support. He even invoked Martin Luther King Jr., promising to turn his dream into a reality.

For the most part, the executive orders Trump announced in his Second Inaugural are tailor-made to support this vision. His promise to restore order to American cities will resonate among the poorer and more diverse segments of his electorate who are the prime victims of urban crime. His promise to restore free speech is broadly popular among voters without fancy degrees who feel that elites are using their arbitrary moral codes and linguistic conventions as cudgels to wield against them at will.

Indeed, what is most striking about Trump’s vision is that, for all of its exaggerated laments about the dilapidated state of America, it is profoundly aspirational. His paean to colorblindness and meritocracy resonates among many Hispanic and Asian-American voters who feel much more secure in their membership in the American mainstream than Democratic invocations of the distorting category of “people of color” would suggest. And his promise to plant the American flag on Mars recalls the collective ambition and grandeur of the 1960s space race.

The received wisdom for the last decade has been that Trump has made his political home among the “losers of globalization.” …his voters supposedly felt that they were stuck in a long line that did not budge, with the wrong kinds of people—notably women and ethnic minorities—cutting in line.

That was and likely remains Trump’s appeal for one part of his electorate. But another part of his base—just as important—has a very different view of America. Hailing from groups that had once been banished to the fringes of American society or have immigrated more recently, they don’t want to return to a supposedly golden past.

On the contrary, they are optimistic about the future and embrace entrepreneurial values precisely because they feel that their hard work is starting to pay off. They don’t picture themselves as standing in a long, static line to enter a destination they covet; rightly or wrongly, they believe that the doors to it would be wide open if gatekeepers—from journalists to Democrats to elites self-servingly insisting on outdated norms—hadn’t cruelly decided to bar their way.

There are good reasons to remain concerned about this version of populism. Democracies do in fact need rules and norms. When the separation of powers goes out of the window, bad policies and perilous constitutional crises usually follow suit. And, being capable of attracting genuine support among a much broader cross-section of the population than most observers recognized until recently, Trump’s brand of populism is more likely to succeed in transforming the country’s political culture this time around.

…the first step in understanding any political movement lies in taking seriously the sources of its popularity. Trump has forged a brand of populism that has wide appeal and makes big promises about the future. If you want to use a suitably academic term, you might call it aspirational, multiethnic populism. Therein lies the power, the promise and the peril posed by Trump’s second presidency.
 

Poof! I'm 15-20 years younger...

A Wall Street Journal article recently pointed me to two websites using AI to estimate one's biological age. So....I took a selfie of my 82 year old face with my iPhone to get novoslabs.com's and facialage.com's estimates that I am 63 and 67 years old, respectively!  Now, two weeks later, I have asked my stable of bots (GPT 4o, Perplexity, etc) for other vendors providing the same service and found four more sites to try. Here are the reactions of all six sites to a further selfie I just took with my iPhone:

https://novoslabs.com/faceage/#test  reported the same result, facial age 63 years old, , in reaction to the new picture, and also reported Eye Age (54 years), Eye Bags (72/100) and Facial Wrinkles (18/100)

https://www.facialage.com/   reported 66 years old,  close to the 67 years old estimate of the previous selfie

reports from other apps:

https://age.toolpie.com/       66 years old

https://faceagecalculator.com/   51  years old 

https://howolddoyoulook.com/    58 years old

https://www.howolddoilook.io/  29  years old

All of the 60-something estimates feel in the right ball park, but heading below that gets into fantasy territory. 

 

The Neurobiology of Aging

I want to point to the Jan. 8 issue of the journal "Neuron" which is largely devoted to the neuroscience of aging.  A number of its review articles are open source. The writing is mostly gibble-gabble, but many useful references can be extracted, particularly on interactions between the immune and nervous systems relevant to aging. 

The origin of color categories

Garside et al. make observations suggesting that cognitive mechanisms such as language are required for the expression of consensus color categories.

Significance

A hallmark of intelligence is the use of concepts. Are people innately equipped with concepts? Prior research has addressed the question using color, because color is experienced categorically: color categories reflect concepts of color. This study tested for color categories in macaque monkeys, a species with the same visual-encoding systems as humans. If color categories are innate products of vision, monkeys should have them. The data were analyzed with sensitive computational models, which showed that monkeys do not have consensus color categories, unlike humans. One monkey had a private color category, suggesting that the capacity to form color categories is innate. The results imply that cognitive mechanisms such as language are required for the expression of consensus color categories.

Abstract

To what extent does concept formation require language? Here, we exploit color to address this question and ask whether macaque monkeys have color concepts evident as categories. Macaques have similar cone photoreceptors and central visual circuits to humans, yet they lack language. Whether Old World monkeys such as macaques have consensus color categories is unresolved, but if they do, then language cannot be required. If macaques do not have color categories, then color categories in humans are unlikely to derive from innate properties of visual encoding and likely to depend on cognitive abilities such as language that differ between monkeys and humans. We tested macaques by adapting a match-to-sample paradigm used in humans to uncover color categories from errors in matches, and we analyzed the data using computational simulations that assess the possibility of unrecognized distortions in the perceptual uniformity of color space. The results provide evidence that humans have consensus cognitive color categories and macaques do not. One animal showed evidence for a private color category, demonstrating that monkeys have the capacity to form color categories even if they do not form consensus color categories. Taken together, the results imply that consensus color categories in humans, for which there is ample evidence, must depend upon language or other cognitive abilities.