Wednesday Round Up #42

This round up brings research papers, but first a taste of sublime.

Chasing the Sublime
The video features one of the better definitions of human agency I’ve heard – speaking to the power of choice, experience, love – as well as being a gorgeous short film itself about swimming and friendship.

“It’s the getting in that we find hard, not the being in. That step forward from the shoreline, Carrie calls it her Eeyore moment, when we stand on the water’s edge, warm and dry and regret what’s ahead. But we love the intensity… [and] we will continue to seek these discomforts, to get cold and too tired, to find and overcome fears, but simultaneously, to experience what feels like life’s biggest freedom, by the simplest of choices, sink or swim, float or flounder. To transform from ordinary to briefly extraordinary.”

Research Papers

From Urban Stress to Neurourbanism: How Should We Research City Well-Being?

Urbanicity has long been associated with stress, anxiety, and mental disorders. A new field of neurourbanism addresses these issues, applying neuroscience laboratory methods to tackle global urban problems and promote happier and healthier cities. Exploratory studies have trialed psychophysiological measurement beyond laboratories, capitalizing on the availability of biosensing technologies to capture geo-located physiological markers of emotional responses to urban environments.

This article reviews the emerging conceptual and methodological debates for urban stress research. City authorities increasingly favor new data-driven and technology-enabled approaches to governing smart cities, with the aim that governments will be enabled to pursue evidence-based urban well-being policies. Yet there are few signs that our cities are undergoing the transformative, structural changes necessary to promote well-being.

To face this urgent challenge and to interrogate the technological promises of our future cities, this article advances the conceptual framework of critical neurogeography and illustrates its application to a comparative international study of urban workers. It is argued that biosensing data can be used to elicit socially and politically relevant narrative data that centers on body–mind–environment relations but exceeds the individualistic and often behaviorist confines that have come to be associated with the quantifying technologies of the emerging field of neurourbanism.

On stress and subjectivity

This article offers a critical analysis of contemporary mainstream stress research, focusing particularly on the way subjectivity is conceptualized. The article shows in detail how researchers in areas from biology to sociology and psychology commonly split stress into two concepts, namely objective, environmental “stressors” and subjective responses. Simultaneously, most research also readily acknowledges that stressors are only stressors insofar as the individual perceives or appraises them to be so. At the heart of stress research today, this paper shows, is a situation wherein the binary between the “objective” stressor and the “subjective” response is dependent upon the very subjectivity that is parsed out and cast aside. This paper critically examines this divide and discusses some possible ways forward for exploring subjectivity vis-à-vis contemporary stress research, arguing for the need for entangled and critical interdisciplinary explorations of subjectivity and stress.

Brains that Fire Together Wire Together: Interbrain Plasticity Underlies Learning in Social Interactions

Social interactions are powerful determinants of learning. Yet the field of neuroplasticity is deeply rooted in probing changes occurring in synapses, brain structures, and networks within an individual brain. Here I synthesize disparate findings on network neuroplasticity and mechanisms of social interactions to propose a new approach for understanding interaction-based learning that focuses on the dynamics of interbrain coupling.

I argue that the facilitation effect of social interactions on learning may be explained by interbrain plasticity, defined here as the short- and long-term experience-dependent changes in interbrain coupling. The interbrain plasticity approach may radically change our understanding of how we learn in social interactions.

Genetic Causation in Complex Regulatory Systems: An Integrative Dynamic Perspective

The logic of genetic discovery has changed little over time, but the focus of biology is shifting from simple genotype–phenotype relationships to complex metabolic, physiological, developmental, and behavioral traits. In light of this, the traditional reductionist view of individual genes as privileged difference‐making causes of phenotypes is re‐examined. The scope and nature of genetic effects in complex regulatory systems, in which dynamics are driven by regulatory feedback and hierarchical interactions across levels of organization are considered.

This review argues that it is appropriate to treat genes as specific actual difference‐makers for the molecular regulation of gene expression. However, they are often neither stable, proportional, nor specific as causes of the overall dynamic behavior of regulatory networks. Dynamical models, properly formulated and validated, provide the tools to probe cause‐and‐effect relationships in complex biological systems, allowing to go beyond the limitations of genetic reductionism to gain an integrative understanding of the causal processes underlying complex phenotypes.

A Technical Critique of Some Parts of the Free Energy Principle

We summarize the original formulation of the free energy principle and highlight some technical issues. We discuss how these issues affect related results involving generalised coordinates and, where appropriate, mention consequences for and reveal, up to now unacknowledged, differences from newer formulations of the free energy principle. In particular, we reveal that various definitions of the “Markov blanket” proposed in different works are not equivalent. We show that crucial steps in the free energy argument, which involve rewriting the equations of motion of systems with Markov blankets, are not generally correct without additional (previously unstated) assumptions. We prove by counterexamples that the original free energy lemma, when taken at face value, is wrong.

We show further that this free energy lemma, when it does hold, implies the equality of variational density and ergodic conditional density. The interpretation in terms of Bayesian inference hinges on this point, and we hence conclude that it is not sufficiently justified. Additionally, we highlight that the variational densities presented in newer formulations of the free energy principle and lemma are parametrised by different variables than in older works, leading to a substantially different interpretation of the theory. Note that we only highlight some specific problems in the discussed publications. These problems do not rule out conclusively that the general ideas behind the free energy principle are worth pursuing.

A dynamical approach to the phenomenology of body memory: Past interactions can shape present capacities without neuroplasticity.

Body memory comprises the acquired dispositions that constitute an individual’s present capacities and experiences. Phenomenological accounts of body memory describe its effects using dynamical metaphors: it is conceived of as curvatures in an agent–environment relational field, leading to attracting and repelling forces that shape ongoing sensorimotor interaction. This relational perspective stands in tension with traditional cognitive science, which conceives of the underlying basis of memory in representational-internal terms: it is the encoding and storing of informational content via structural changes inside the brain.

We propose that this tension can be resolved by replacing the traditional approach with the dynamical approach to cognitive science. Specifically, we present three of our simulation models of embodied cognition that can help us to rethink the basis of several types of body memory. The upshot is that, at least in principle, there is no need to explain their basis in terms of content or to restrict their basis to neuroplasticity alone. Instead these models support the perspective developed by phenomenology: body memory is a relational property of a whole brain–body–environment system that emerges out of its history of interactions.

Systematic detection of brain protein-coding genes under positive selection during primate evolution and their roles in cognition

The human brain differs from that of other primates, but the genetic basis of these differences remains unclear. We investigated the evolutionary pressures acting on almost all human protein-coding genes (N = 11,667; 1:1 orthologs in primates) based on their divergence from those of early hominins, such as Neanderthals, and non-human primates. We confirm that genes encoding brain-related proteins are among the most strongly conserved protein-coding genes in the human genome. Combining our evolutionary pressure metrics for the protein-coding genome with recent data sets, we found that this conservation applied to genes functionally associated with the synapse and expressed in brain structures such as the prefrontal cortex and the cerebellum.

Conversely, several genes presenting signatures commonly associated with positive selection appear as causing brain diseases or conditions, such as micro/macrocephaly, Joubert syndrome, dyslexia, and autism. Among those, a number of DNA damage response genes associated with microcephaly in humans such as BRCA1, NHEJ1, TOP3A, and RNF168 show strong signs of positive selection and might have played a role in human brain size expansion during primate evolution. We also showed that cerebellum granule neurons express a set of genes also presenting signatures of positive selection and that may have contributed to the emergence of fine motor skills and social cognition in humans. This resource is available online and can be used to estimate evolutionary constraints acting on a set of genes and to explore their relative contributions to human traits.

*The above paper provides a counter-intuitive result, where most theories assume positive selection on genes for the brain. But this result highlights how much having a well-functioning brain is for being a reproductively successful human ancestor. Given the conservation, it also implies that getting this wrong early in life really matters – humans need a well-functioning brain as they develop, not just when they’re developed.

Back to Square One: from Embodied Experiences in Utero to Theories of Consciousness

This paper argues that consciousness science may be put on a fruitful track for its future evolution by endorsing a bottom-up developmental perspective. Specifically, we propose to go back to ‘square one’ and to examine the nature of subjective experiences as they emerge in early human life, in utero. We build upon the observation that current theories of consciousness tacitly endorse an adult-centric and vision-biased approach in tackling the
problem of subjective experiences.

Indeed, one basic yet overlooked aspect of current discussions on consciousness is that in humans, experiences and experiencing subjects first develop within another human body. Hence, this observation must be taken into account and incorporated by current theories of consciousness. We propose to zoom out from the classical conundrum of the relationship consciousness and its neural correlates. Rather we see consciousness necessarily related to experiences and from there to embodied experiencers.

Given that experiencers are subjects actively engaging with an environment in order to maintain self-organisation and self-preservation, consciousness cannot be addressed in isolation from self-consciousness. We make use of the ‘iceberg’ metaphor to argue that in order to understand the nature of the visible ‘tip’ of our conscious experiences one needs to go back to its pre-reflective and bodily roots. This is because the basis of the ‘experiential iceberg’ is conceptually and ontologically prior to its ‘tip’. Examining the primitive and prereflective basis of the iceberg may teach us something essential not only about its visible accessible side (i.e. the contents of conscious experiences that we can explicitly attend to and report), but also about its entire structure as a whole. We conclude with some implications of our hypothesis for future research for consciousness studies.

The sense of should: A biologically-based framework for modeling social pressure

What is social pressure, and how could it be adaptive to conform to others’ expectations? Existing accounts highlight the importance of reputation and social sanctions. Yet, conformist behavior is multiply determined: sometimes, a person desires social regard, but at other times she feels obligated to behave a certain way, regardless of any reputational benefit—i.e. she feels a sense of should. We develop a formal model of this sense of should, beginning from a minimal set of biological premises: that the brain is predictive, that prediction error has a metabolic cost, and that metabolic costs are prospectively avoided.

It follows that unpredictable environments impose metabolic costs, and in social environments these costs can be reduced by conforming to others’ expectations. We elaborate on a sense of should’s benefits and subjective experience, its likely developmental trajectory, and its relation to embodied mental inference. From this individualistic metabolic strategy, the emergent dynamics unify social phenomenon ranging from status quo biases, to communication and motivated cognition. We offer new solutions to long-studied problems (e.g. altruistic behavior), and show how compliance with arbitrary social practices is compelled without explicit sanctions. Social pressure may provide a foundation in individuals on which societies can be built.

Neural circuits of social behaviors: innate yet flexible

Social behaviors, such as mating, fighting, and parenting, are fundamental for survival of any vertebrate species. All members of a species express social behaviors in a stereotypical and species-specific way without training because of developmentally hardwired neural circuits dedicated to these behaviors.

Despite being innate, social behaviors are flexible. The readiness to interact with a social target or engage in specific social acts can vary widely based on reproductive state, social experience, and many other internal and external factors. Such high flexibility gives vertebrates the ability to release the relevant behavior at the right moment and toward the right target. This maximizes reproductive success while minimizing the cost and risk associated with behavioral expression.

Decades of research have revealed the basic neural circuits underlying each innate social behavior. The neural mechanisms that support behavioral plasticity have also started to emerge. Here we provide an overview of these social behaviors and their underlying neural circuits and then discuss in detail recent findings regarding the neural processes that support the flexibility of innate social behaviors.

Artificial Intelligence is stupid and causal reasoning won’t fix it

Artificial Neural Networks have reached Grandmaster and even super-human performance across a variety of games: from those involving perfect-information (such as Go) to those involving imperfect-information (such as Starcraft). Such technological developments from AI-labs have ushered concomitant applications across the world of business – where an AI brand tag is fast becoming ubiquitous. A corollary of such widespread commercial deployment is that when AI gets things wrong – an autonomous vehicle crashes; a chatbot exhibits racist behaviour; automated credit scoring processes discriminate on gender etc. – there are often significant financial, legal and brand consequences and the incident becomes major news.

As Judea Pearl sees it, the underlying reason for such mistakes is that, ‘all the impressive achievements of deep learning amount to just curve fitting’. The key, Judea Pearl suggests, is to replace reasoning by association with causal-reasoning – the ability to infer causes from observed phenomena. It is a point that was echoed by Gary Marcus and Ernest Davis in a recent piece for the New York Times: ‘we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets – often using an approach known as Deep Learning – and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space and causality’.

In this paper, foregrounding what in 1949 Gilbert Ryle termed a category mistake, I will offer an alternative explanation for AI errors: it is not so much that AI machinery cannot grasp causality, but that AI machinery – qua computation – cannot understand anything at all.

Beyond Correlation versus Causation: Multi-brain Neuroscience Needs Explanation

Recent advances in brain sciences have enabled the co-recording of multiple interacting brains (i.e., hyperscanning [1]). This technique has led to the discovery of inter-brain synchrony (IBS) between people involved in social and interactive scenarios. In a recent article, Novembre and Iannetti argued that studies using hyperscanning to understand social behaviors are crucial but limited to correlational analysis [2]. They further developed the idea that the causal role of IBS can only be apprehended through multi-brain stimulation (MBS).

Although we agree with Novembre and Iannetti that MBS is one of the most promising methods for investigating inter-brain coupling in the future, we disagree on their radical claim that it constitutes ‘the only validated empirical approach capable of teasing apart the mechanistic from the epiphenomenal interpretation of inter-brain synchrony’. In this Letter, we defend the idea that explaining IBS in terms of causal mechanisms is possible through adequate experimental designs and computational tools, with empirical approaches ranging from multi-brains (hyperscanning) to single-brain (classic social neuroscience) recordings, and even no-brain (i.e., in silico computational social neuroscience).

What nervous systems do: early evolution, input–output, and the skin brain thesis

Nervous systems are standardly interpreted as information processing input–output devices. They receive environmental information from their sensors as input, subsequently process or adjust this information, and use the result to control effectors, providing output. Through-conducting activity is here the key organizational feature of nervous systems. In this paper, we argue that this input–output interpretation is not the most fundamental feature of nervous system organization. Building on biological work on the early evolution of nervous systems, we provide an alternative proposal: the skin brain thesis (SBT).

The SBT postulates that early nervous systems evolved to organize a new multicellular effector: muscle tissue, the primary source of animal motility. Early nervous systems provided a new way of inducing and coordinating self-organized contractile activity across an extensive muscle surface underneath the skin. The main connectivity in such nervous systems runs across a spread out effector and is transverse to sensor-effector signaling. The SBT therefore constitutes a fundamental conceptual shift in understanding both nervous system operation and what nervous systems are. Nervous systems are foremost spatial organizers that turn large multi-cellular animal bodies into dynamic self-moving units. At the end, we briefly discuss some theoretical connections to central issues within the behavioral, cognitive and neurosciences.

Defiant hospitality: a grounded theory study of harm reduction psychotherapy

Harm reduction psychotherapy (HRP)is an approach to providing psychotherapy to people who use substances in which abstinence is considered neither a prerequisite to treatment nor its predominant mark of success. There is to date scant empirical research on this clinical approach despite its decades-long practice. Ourstudy aims to spur further investigations by asking:1) what are the basic building blocks of HRP; and (2) what theory might explain how its core strategies are unified?

Eight leading HRP proponents and practitioners participated in semi-structured interviews to explore the nature of their work and how they came to it. Through an analysis of the interviews guided by grounded theory, we propose an explanatory model of HRP as practiced in the U.S. In this model, practitioners, informed by an ethos of defiant hospitality, deploy a variety of therapeutic processes whose combined, complex effects are captured in the phrase making room, which conveys opening up space while simultaneously providing safe enclosure.

Making room is operationalized in processes comprising: inviting, meeting at, staying with, holding, reframing substance use, leveraging change from within, supporting agency, and signaling the limits. We discuss the model as deeply informed by its socio-historical roots within treatment spaces that participants experienced as failing to meet their clients’ needs. We also consider HRP’s implications for expanding the reach and capacity of addiction care for the majority of individuals with substance use disorders who may initially be unwilling or unable to abstain. Lastly, we describe its potential for furthering the field’s understanding of therapeutic practice with marginalized populations.

Communicating artificial neural networks develop efficient color-naming systems

Words categorize the semantic fields they refer to in ways that maximize communication accuracy while minimizing complexity. Focusing on the well-studied color domain, we show that artificial neural networks trained with deep-learning techniques to play a discrimination game develop communication systems whose distribution on the accuracy/complexity plane closely matches that of human languages. The observed variation among emergent color-naming systems is explained by different degrees of discriminative need, of the sort that might also characterize different human communities.

Like human languages, emergent systems show a preference for relatively low-complexity solutions, even at the cost of imperfect communication. We demonstrate next that the nature of the emergent systems crucially depends on communication being discrete (as is human word usage). When continuous message passing is allowed, emergent systems become more complex and eventually less efficient. Our study suggests that efficient semantic categorization is a general property of discrete communication systems, not limited to human language. It suggests moreover that it is exactly the discrete nature of such systems that, acting as a bottleneck, pushes them toward low complexity and optimal efficiency.

Tweetorial on our new paper, “Dump the Dimorphism: Comprehensive synthesis of brain studies finds few male-female differences beyond size.”

6/ Men have bigger bodies and average 11% larger brains. But other M/F differences are a PRODUCT OF SIZE, NOT SEX.
7/ These include: 1) gray/white matter ratio is 6% higher in women; 2) inter- vs intrahemispheric connectivity ratio also higher F>M. But both ratios vary comparably WITHIN SEX, depending on head size.
8/ Meaning the difference between the avg. man and woman is also found between small- and large-headed men (ditto among women).

Paper itself: Dump the “dimorphism”: Comprehensive synthesis of human brain studies reveals few male-female differences beyond size

With the explosion of neuroimaging, differences between male and female brains have been exhaustively analyzed. Here we synthesize three decades of human MRI and postmortem data, emphasizing meta-analyses and other large studies, which collectively reveal few reliable sex/gender differences and a history of unreplicated claims. Males’ brains are larger than females’ from birth, stabilizing around 11% in adults. This size difference accounts for other reproducible findings: higher white/gray matter ratio, intra- versus interhemispheric connectivity, and regional cortical and subcortical volumes in males.

But when structural and lateralization differences are present independent of size, sex/gender explains only about 1% of total variance. Connectome differences and multivariate sex/gender prediction are largely based on brain size, and perform poorly across diverse populations. Task-based fMRI has especially failed to find reproducible activation differences between men and women in verbal, spatial or emotion processing due to high rates of false discovery. Overall, male/female brain differences appear trivial and population-specific. The human brain is not “sexually dimorphic.”

Determining the effects of training duration on the behavioral expression of habitual control in humans: a multi-laboratory investigation

It has been suggested that there are two distinct and parallel mechanisms for controlling instrumental behavior in mammals: goal-directed actions and habits. To gain an understanding of how these two systems interact to control behavior, it is essential to characterize the mechanisms by which the balance between these systems is influenced by experience. Studies in rodents have shown that the amount of training governs the relative expression of these two systems: behavior is goal-directed following moderate training, but the more extensively an instrumental action is trained, the more it becomes habitual.

It is less clear whether humans exhibit similar training effects on the expression of goal-directed and habitual behavior, as human studies have reported contradictory findings. To tackle these contradictory findings, we formed a consortium, where four laboratories undertook a pre-registered experimental induction of habits by manipulating the amount of training. There was no statistical evidence for a main effect of the amount of training on the formation and expression of habits. However, exploratory analyses suggest a moderating effect of the affective component of stress on the impact of training over habit expression. Participants who were lower in affective stress appeared to be initially goal-directed, but became habitual with increased training, whereas participants who were high in affective stress were already habitual even after moderate training, thereby manifesting insensitivity to overtraining effects. Our findings highlight the importance of the role of moderating variables such as individual differences in stress and anxiety when studying the experimental induction of habits in humans.

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