Thinking through other minds: A variational approach to cognition and culture

Minds in movement: embodied cognition in the age of artificial intelligence

This theme issue brings together researchers from diverse fields to assess the current status and future prospects of embodied cognition in the age of generative artificial intelligence. In this introduction, we first clarify our view of embodiment as a potentially unifying concept in the study of cognition, characterizing this as a perspective that questions mind-body dualism and recognizes a profound continuity between sensorimotor action in the world and more abstract forms of cognition. We then consider how this unifying concept is developed and elaborated by the other contributions to this issue, identifying the following two key themes: (i) the role of language in cognition and its entanglement with the body and (ii) bodily mechanisms of interpersonal perception and alignment across the domains of social affiliation, teaching and learning. On balance, we consider that embodied approaches to the study of cognition, culture and evolution remain promising, but will require greater integration across disciplines to fully realize their potential. We conclude by suggesting that researchers will need to be ready and able to meet the various methodological, theoretical and practical challenges this will entail and remain open to encountering markedly different viewpoints about how and why embodiment matters. This article is the part of this theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'.

Nature heals: An informational entropy account of self-organization and change in field psychotherapy

This paper reviews biophysical models of psychotherapeutic change based on synergetics and the free energy principle. These models suggest that introducing sensory surprise into the patient-therapist system can lead to self-organization and the formation of new attractor states, disrupting entrenched patterns of thoughts, emotions, and behaviours. We propose that the therapist can facilitate this process by cultivating epistemic trust and modulating embodied attention to allow surprising affective states to enter shared awareness. Transient increases in free energy enable the update of generative models, expanding the range of experiences available within the patient-therapist phenomenal field. We hypothesize that patterns of disorganization at behavioural and physiological levels, indexed by increased entropy, complexity, and lower determinism, are key markers and predictors of psychotherapeutic gains. Future research should investigate how the therapist's openness to novelty shapes therapeutic outcomes.

An Integrated theory of false insights and beliefs under psychedelics

Psychedelics are recognised for their potential to re-orient beliefs. We propose a model of how psychedelics can, in some cases, lead to false insights and thus false beliefs. We first review experimental work on laboratory-based false insights and false memories. We then connect this to insights and belief formation under psychedelics using the active inference framework. We propose that subjective and brain-based alterations caused by psychedelics increases the quantity and subjective intensity of insights and thence beliefs, including false ones. We offer directions for future research in minimising the risk of false and potentially harmful beliefs arising from psychedelics. Ultimately, knowing how psychedelics may facilitate false insights and beliefs is crucial if we are to optimally leverage their therapeutic potential.

Narrative as active inference: an integrative account of cognitive and social functions in adaptation

While the ubiquity and importance of narratives for human adaptation is widely recognized, there is no integrative framework for understanding the roles of narrative in human adaptation. Research has identified several cognitive and social functions of narratives that are conducive to well-being and adaptation as well as to coordinated social practices and enculturation. In this paper, we characterize the cognitive and social functions of narratives in terms of active inference, to support the claim that one of the main adaptive functions of narrative is to generate more useful (i.e., accurate, parsimonious) predictions for the individual, as well as to coordinate group action (over multiple timescales) through shared predictions about collective behavior. Active inference is a theory that depicts the fundamental tendency of living organisms to adapt by proactively inferring the causes of their sensations (including their own actions). We review narrative research on identity, event segmentation, episodic memory, future projections, storytelling practices, enculturation, and master narratives. We show how this research dovetails with the active inference framework and propose an account of the cognitive and social functions of narrative that emphasizes that narratives are for the future-even when they are focused on recollecting or recounting the past. Understanding narratives as cognitive and cultural tools for mutual prediction in social contexts can guide research on narrative in adaptive behavior and psychopathology, based on a parsimonious mechanistic model of some of the basic adaptive functions of narrative.

Imagination vs. routines: festive time, weekly time, and the predictive brain

This paper examines the relationship between societal structures shaped by traditions, norms, laws, and customs, and creative expressions in arts and media through the lens of the predictive coding framework in cognitive science. The article proposes that both dimensions of culture can be viewed as adaptations designed to enhance and train the brain's predictive abilities in the social domain. Traditions, norms, laws, and customs foster shared predictions and expectations among individuals, thereby reducing uncertainty in social environments. On the other hand, arts and media expose us to simulated experiences that explore alternative social realities, allowing the predictive machinery of the brain to hone its skills through exposure to a wider array of potentially relevant social circumstances and scenarios. We first review key principles of predictive coding and active inference, and then explore the rationale of cultural traditions and artistic culture in this perspective. Finally, we draw parallels between institutionalized normative habits that stabilize social worlds and creative and imaginative acts that temporarily subvert established conventions to inject variability.

Neural representation in active inference: Using generative models to interact with-and understand-the lived world

This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize the discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that the brain learns generative models to navigate the world adaptively, not (or not solely) to understand it. Different living organisms may possess an array of generative models, spanning from those that support action-perception cycles to those that underwrite planning and imagination; namely, from explicit models that entail variables for predicting concurrent sensations, like objects, faces, or people-to action-oriented models that predict action outcomes. It then elucidates how generative models and belief dynamics might link to neural representation and the implications of different types of generative models for understanding an agent's cognitive capabilities in relation to its ecological niche. The paper concludes with open questions regarding the evolution of generative models and the development of advanced cognitive abilities-and the gradual transition from pragmatic to detached neural representations. The analysis on offer foregrounds the diverse roles that generative models play in cognitive processes and the evolution of neural representation.

Clere Smithe T, Friedman DA, Friston K, Ramstead MJD. Shared Protentions in Multi-Agent Active Inference

In this paper, we unite concepts from Husserlian phenomenology, the active inference framework in theoretical biology, and category theory in mathematics to develop a comprehensive framework for understanding social action premised on shared goals. We begin with an overview of Husserlian phenomenology, focusing on aspects of inner time-consciousness, namely, retention, primal impression, and protention. We then review active inference as a formal approach to modeling agent behavior based on variational (approximate Bayesian) inference. Expanding upon Husserl's model of time consciousness, we consider collective goal-directed behavior, emphasizing shared protentions among agents and their connection to the shared generative models of active inference. This integrated framework aims to formalize shared goals in terms of shared protentions, and thereby shed light on the emergence of group intentionality. Building on this foundation, we incorporate mathematical tools from category theory, in particular, sheaf and topos theory, to furnish a mathematical image of individual and group interactions within a stochastic environment. Specifically, we employ morphisms between polynomial representations of individual agent models, allowing predictions not only of their own behaviors but also those of other agents and environmental responses. Sheaf and topos theory facilitates the construction of coherent agent worldviews and provides a way of representing consensus or shared understanding. We explore the emergence of shared protentions, bridging the phenomenology of temporal structure, multi-agent active inference systems, and category theory. Shared protentions are highlighted as pivotal for coordination and achieving common objectives. We conclude by acknowledging the intricacies stemming from stochastic systems and uncertainties in realizing shared goals.

The police hunch: the Bayesian brain, active inference, and the free energy principle in action

In the realm of law enforcement, the "police hunch" has long been a mysterious but crucial aspect of decision-making. Drawing on the developing framework of Active Inference from cognitive science, this theoretical article examines the genesis, mechanics, and implications of the police hunch. It argues that hunches - often vital in high-stakes situations - should not be described as mere intuitions, but as intricate products of our mind's generative models. These models, shaped by observations of the social world and assimilated and enacted through active inference, seek to reduce surprise and make hunches an indispensable tool for officers, in exactly the same way that hypotheses are indispensable for scientists. However, the predictive validity of hunches is influenced by a range of factors, including experience and bias, thus warranting critical examination of their reliability. This article not only explores the formation of police hunches but also provides practical insights for officers and researchers on how to harness the power of active inference to fully understand policing decisions and subsequently explore new avenues for future research.

A hole in a piece of cardboard and predictive brain: the incomprehension of modern art in the light of the predictive coding paradigm

Incomprehension of and resistance to contemporaneous art have been constant features in the development of modern art. The predictive coding framework can be used to analyse this response by outlining the difference between the misunderstanding of (i) contemporary conceptual/minimalist art and (ii) early modern avant-garde art and by elucidating their underlying cognitive mechanisms. In both of these cases, incomprehension and its behavioural consequences are tied to the failure of the optimal prediction error (PE) minimization that is involved in the perception of such art works. In the case of contemporary conceptual/minimalist art the failure stems from the fact that the encounter results in non-salient visual sensations and generates no PE. In early modern avant-garde art, the occasional inability of viewers to recognize pictorial content using new pictorial conventions reflected the absence of suitable priors to explain away ambiguous sensory data. The capacity to recognize pictorial content in modernist painting, as a prerequisite for a satisfying encounter with such works and ultimately a wider acceptance of new artistic styles, required an updating of a number of expectations in order to optimize the fit between priors and sensations, from low-level perceptual priors to the development of higher-level, culturally determined expectations. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

Rethinking Norm Psychology

Norms permeate human life. Most of people's activities can be characterized by rules about what is appropriate, allowed, required, or forbidden-rules that are crucial in making people hyper-cooperative animals. In this article, I examine the current cognitive-evolutionary account of "norm psychology" and propose an alternative that is better supported by evidence and better placed to promote interdisciplinary dialogue. The incumbent theory focuses on rules and claims that humans genetically inherit cognitive and motivational mechanisms specialized for processing these rules. The cultural-evolutionary alternative defines normativity in relation to behavior-compliance, enforcement, and commentary-and suggests that it depends on implicit and explicit processes. The implicit processes are genetically inherited and domain-general; rather than being specialized for normativity, they do many jobs in many species. The explicit processes are culturally inherited and domain-specific; they are constructed from mentalizing and reasoning by social interaction in childhood. The cultural-evolutionary, or "cognitive gadget," perspective suggests that people alive today-parents, educators, elders, politicians, lawyers-have more responsibility for sustaining normativity than the nativist view implies. People's actions not only shape and transmit the rules, but they also create in each new generation mental processes that can grasp the rules and put them into action.

Motivated Categories: Social Structures Shape the Construction of Social Categories Through Attentional Mechanisms

PUBLIC ABSTRACT

Social categories like race and gender often give rise to stereotypes and prejudice, and a great deal of research has focused on how motivations influence these biased beliefs. Here, we focus on potential biases in how these categories are even formed in the first place, suggesting that motivations can influence the very categories people use to group others. We propose that motivations to share schemas with other people and to gain resources shape people's attention to dimensions like race, gender, and age in different contexts. Specifically, people will pay attention to dimensions to the degree that the conclusions produced from using those dimensions align with their motivations. Overall, we suggest that simply examining the downstream effects of social categorization like stereotyping and prejudice is not enough, and that research should look earlier in the process at how and when we form the categories on which those stereotypes are based.

Disorganized Communication and Social Dysfunction in Schizophrenia: Emerging Concepts and Methods

PURPOSE OF REVIEW

In this review, we embrace the emerging field of second-person neuroscience to address disorganization in schizophrenia. We argue that the focus of interest for disorganization is the interpersonal space where shared mental processes ('social mind') occur based on the bio-behavioural synchrony between two (or more) interacting people. We lay out several bio-behavioural measures that can capture the component parts of this process. In particular, we highlight the real-time imaging technology of hyperscanning that enables multi-person analysis of naturalistic social interaction. We illustrate how these measures can be used in empirical studies by posing disorganization as a problem of interpersonal processing.

RECENT FINDINGS

Traditionally, disorganized speech and behaviour have been studied as the product of hidden cognitive processes ('private mind'). A dysfunction in these processes was attributed to the brain afflicted by the illness ('brain-bound mechanisms'). But this approach has contributed to challenges in measuring and quantifying disorganization. Consequently, the single-brain focus has not provided satisfactory clarity or led to effective treatments for persistent social dysfunction in schizophrenia. Social dysfunction is a core feature of schizophrenia. This dysfunction arises from disorganized interpersonal interaction that typifies the social profile of affected individuals. We outline challenges in employing several emerging concepts and methods and how they can be addressed to investigate the mechanisms of social dysfunction in schizophrenia.

Music in the Middle: A Culture-Cognition-Mediator Model of Musical Functionality

Music is both universal, appearing in every known human culture, and culture-specific, often defying intelligibility across cultural boundaries. This duality has been the source of debate within the broad community of music researchers, and there have been significant disagreements both on the ontology of music as an object of study and the appropriate epistemology for that study. To help resolve this tension, I present a culture-cognition-mediator model that situates music as a mediator in the mutually constitutive cycle of cultures and selves representing the ways individuals both shape and are shaped by their cultural environments. This model draws on concepts of musical grammars and schema, contemporary theories in developmental and cultural psychology that blur the distinction between nature and nurture, and recent advances in cognitive neuroscience. Existing evidence of both directions of causality is presented, providing empirical support for the conceptual model. The epistemological consequences of this model are discussed, specifically with respect to transdisciplinarity, hybrid research methods, and several potential empirical applications and testable predictions as well as its import for broader ontological conversations around the evolutionary origins of music itself.

Cognitive modeling, ecological psychology, and musical improvisation

Understanding novelty and improvisation in music requires gathering insight from a variety of disciplines. One fruitful path for synthesizing these insights is via modeling. As such, my aim in this paper is to start building a bridge between traditional cognitive models and contemporary embodied and ecological approaches to cognitive science. To achieve this task, I offer a perspective on a model that would combine elements of ecological psychology (especially affordances) and the Learning Intelligent Decision Agent (LIDA) cognitive architecture. Jeff Pressing's cognitive model of musical improvisation will also be a central link between these elements. While some overlap between these three areas already exists, there are several points of tension between them, notably concerning the nature of perception and the function of artificial general intelligence modeling. I thus aim to alleviate the most worrisome concerns here, introduce several future research questions, and conclude with several points on how my account is part of a general theory, rather than merely a redescription of existent work.

Really radical?

I enjoyed reading this compelling account of Conviction Narrative Theory (CNT). As a theoretical neurobiologist, I recognised - and applauded - the tenets of CNT. My commentary asks whether its claims could be installed into a Bayesian mechanics of decision-making, in a way that would enable theoreticians to model, reproduce and predict decision-making.

Intertwining the social and the cognitive loops: socially enactive cognition for human-compatible interactive systems

It is increasingly important for technical systems to be able to interact flexibly, robustly and fluently with humans in real-world scenarios. However, while current AI systems excel at narrow task competencies, they lack crucial interaction abilities for the adaptive and co-constructed social interactions that humans engage in. We argue that a possible avenue to tackle the corresponding computational modelling challenges is to embrace interactive theories of social understanding in humans. We propose the notion of socially enactive cognitive systems that do not rely solely on abstract and (quasi-)complete internal models for separate social perception, reasoning and action. By contrast, socially enactive cognitive agents are supposed to enable a close interlinking of the enactive socio-cognitive processing loops within each agent, and the social-communicative loop between them. We discuss theoretical foundations of this view, identify principles and requirements for according computational approaches, and highlight three examples of our own research that showcase the interaction abilities achievable in this way. This article is part of a discussion meeting issue 'Face2face: advancing the science of social interaction'.

Evolution of cortical geometry and its link to function, behaviour and ecology

Studies in comparative neuroanatomy and of the fossil record demonstrate the influence of socio-ecological niches on the morphology of the cerebral cortex, but have led to oftentimes conflicting theories about its evolution. Here, we study the relationship between the shape of the cerebral cortex and the topography of its function. We establish a joint geometric representation of the cerebral cortices of ninety species of extant Euarchontoglires, including commonly used experimental model organisms. We show that variability in surface geometry relates to species' ecology and behaviour, independent of overall brain size. Notably, ancestral shape reconstruction of the cortical surface and its change during evolution enables us to trace the evolutionary history of localised cortical expansions, modal segregation of brain function, and their association to behaviour and cognition. We find that individual cortical regions follow different sequences of area increase during evolutionary adaptations to dynamic socio-ecological niches. Anatomical correlates of this sequence of events are still observable in extant species, and relate to their current behaviour and ecology. We decompose the deep evolutionary history of the shape of the human cortical surface into spatially and temporally conscribed components with highly interpretable functional associations, highlighting the importance of considering the evolutionary history of cortical regions when studying their anatomy and function.

A cultural-ecosocial systems view for psychiatry

While contemporary psychiatry seeks the mechanisms of mental disorders in neurobiology, mental health problems clearly depend on developmental processes of learning and adaptation through ongoing interactions with the social environment. Symptoms or disorders emerge in specific social contexts and involve predicaments that cannot be fully characterized in terms of brain function but require a larger social-ecological view. Causal processes that result in mental health problems can begin anywhere within the extended system of body-person-environment. In particular, individuals' narrative self-construal, culturally mediated interpretations of symptoms and coping strategies as well as the responses of others in the social world contribute to the mechanisms of mental disorders, illness experience, and recovery. In this paper, we outline the conceptual basis and practical implications of a hierarchical ecosocial systems view for an integrative approach to psychiatric theory and practice. The cultural-ecosocial systems view we propose understands mind, brain and person as situated in the social world and as constituted by cultural and self-reflexive processes. This view can be incorporated into a pragmatic approach to clinical assessment and case formulation that characterizes mechanisms of pathology and identifies targets for intervention.

Therapeutic touch and therapeutic alliance in pediatric care and neonatology: An active inference framework

Therapeutic affective touch has been recognized as essential for survival, nurturing supportive interpersonal interactions, accelerating recovery-including reducing hospitalisations, and promoting overall health and building robust therapeutic alliances. Through the lens of active inference, we present an integrative model, combining therapeutic touch and communication, to achieve biobehavioural synchrony. This model speaks to how the brain develops a generative model required for recovery, developing successful therapeutic alliances, and regulating allostasis within paediatric manual therapy. We apply active inference to explain the neurophysiological and behavioural mechanisms that underwrite the development and maintenance of synchronous relationships through touch. This paper foregrounds the crucial role of therapeutic touch in developing a solid therapeutic alliance, the clinical effectiveness of paediatric care, and triadic synchrony between health care practitioner, caregiver, and infant in a variety of clinical situations. We start by providing a brief overview of the significance and clinical role of touch in the development of social interactions in infants; facilitating a positive therapeutic alliance and restoring homeostasis through touch to allow a more efficient process of allostatic regulation. Moreover, we explain the role of CT tactile afferents in achieving positive clinical outcomes and updating prior beliefs. We then discuss how touch is implemented in treatment sessions to promote cooperative interactions in the clinic and facilitate theory of mind. This underwrites biobehavioural synchrony, epistemic trust, empathy, and the resolution of uncertainty. The ensuing framework is underpinned by a critical application of the active inference framework to the fields of pediatrics and neonatology.

Interpersonal attunement in social interactions: from collective psychophysiology to inter-personalized psychiatry and beyond

In this article, we analyse social interactions, drawing on diverse points of views, ranging from dialectics, second-person neuroscience and enactivism to dynamical systems, active inference and machine learning. To this end, we define interpersonal attunement as a set of multi-scale processes of building up and materializing social expectations-put simply, anticipating and interacting with others and ourselves. While cultivating and negotiating common ground, via communication and culture-building activities, are indispensable for the survival of the individual, the relevant multi-scale mechanisms have been largely considered in isolation. Here, collective psychophysiology, we argue, can lend itself to the fine-tuned analysis of social interactions, without neglecting the individual. On the other hand, an interpersonal mismatch of expectations can lead to a breakdown of communication and social isolation known to negatively affect mental health. In this regard, we review psychopathology in terms of interpersonal misattunement, conceptualizing psychiatric disorders as disorders of social interaction, to describe how individual mental health is inextricably linked to social interaction. By doing so, we foresee avenues for an inter-personalized psychiatry, which moves from a static spectrum of disorders to a dynamic relational space, focusing on how the multi-faceted processes of social interaction can help to promote mental health. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Small steps for mankind: Modeling the emergence of cumulative culture from joint active inference communication

Although the increase in the use of dynamical modeling in the literature on cultural evolution makes current models more mathematically sophisticated, these models have yet to be tested or validated. This paper provides a testable deep active inference formulation of social behavior and accompanying simulations of cumulative culture in two steps: First, we cast cultural transmission as a bi-directional process of communication that induces a generalized synchrony (operationalized as a particular convergence) between the belief states of interlocutors. Second, we cast social or cultural exchange as a process of active inference by equipping agents with the choice of who to engage in communication with. This induces trade-offs between confirmation of current beliefs and exploration of the social environment. We find that cumulative culture emerges from belief updating (i.e., active inference and learning) in the form of a joint minimization of uncertainty. The emergent cultural equilibria are characterized by a segregation into groups, whose belief systems are actively sustained by selective, uncertainty minimizing, dyadic exchanges. The nature of these equilibria depends sensitively on the precision afforded by various probabilistic mappings in each individual's generative model of their encultured niche.

Resilience and active inference

In this article, we aim to conceptualize and formalize the construct of resilience using the tools of active inference, a new physics-based modeling approach apt for the description and analysis of complex adaptive systems. We intend this as a first step toward a computational model of resilient systems. We begin by offering a conceptual analysis of resilience, to clarify its meaning, as established in the literature. We examine an orthogonal, threefold distinction between meanings of the word "resilience": (i) inertia, or the ability to resist change (ii) elasticity, or the ability to bounce back from a perturbation, and (iii) plasticity, or the ability to flexibly expand the repertoire of adaptive states. We then situate all three senses of resilience within active inference. We map resilience as inertia onto high precision beliefs, resilience as elasticity onto relaxation back to characteristic (i.e., attracting) states, and resilience as plasticity onto functional redundancy and structural degeneracy.

Cognition as Morphological/Morphogenetic Embodied Computation In Vivo

Cognition, historically considered uniquely human capacity, has been recently found to be the ability of all living organisms, from single cells and up. This study approaches cognition from an info-computational stance, in which structures in nature are seen as information, and processes (information dynamics) are seen as computation, from the perspective of a cognizing agent. Cognition is understood as a network of concurrent morphological/morphogenetic computations unfolding as a result of self-assembly, self-organization, and autopoiesis of physical, chemical, and biological agents. The present-day human-centric view of cognition still prevailing in major encyclopedias has a variety of open problems. This article considers recent research about morphological computation, morphogenesis, agency, basal cognition, extended evolutionary synthesis, free energy principle, cognition as Bayesian learning, active inference, and related topics, offering new theoretical and practical perspectives on problems inherent to the old computationalist cognitive models which were based on abstract symbol processing, and unaware of actual physical constraints and affordances of the embodiment of cognizing agents. A better understanding of cognition is centrally important for future artificial intelligence, robotics, medicine, and related fields.

The seductive allure of cargo cult computationalism

Bruineberg and colleagues report a striking confusion, in which the formal Bayesian notion of a "Markov blanket" has been frequently misunderstood and misapplied to phenomena of mind and life. I argue that misappropriation of formal concepts is pervasive in the "predictive processing" literature, and echo Richard Feynman in suggesting how we might resist the allure of cargo cult computationalism.

A New Look at Young Children's Referential Informativeness

In this article, I review experimental evidence for the dependence of 2- to 5-year-olds' linguistic referential informativeness on cues to common ground (CG) and propose a process model. Cues to CG provide evidence for CG, that is, for the shared knowledge, beliefs, and attitudes of interlocutors. The presence of cues to CG (e.g., unimpeded listener line of regard or prior mention) is shown to be associated with less informative reference (e.g., pronouns). In contrast, the absence of cues to CG (e.g., impeded listener line of regard or new mention) is shown to be associated with more informative reference (e.g., nouns). Informativeness is sensitive to linguistic before nonlinguistic cues to CG (i.e., 2.0 vs. 2.5 years old, respectively). Reference is cast as a process of active inference, a formulation of Bayesian belief-guided control in biological systems. Child speakers are hierarchical generative models that, characteristically, expect sensory evidence for the evolved, prior Bayesian belief that interlocutor mental states are aligned (i.e., that CG exists). Referential control emerges as an embodied tool to gather evidence for this prior belief. Bottom-up cues to CG elicited by action drive updates to beliefs about CG. In turn, beliefs about CG guide efficient referential control.

A glimpse into social perception in light of vitality forms

The American psychoanalyst and developmental psychologist Daniel Stern's idea of vitality forms might suggest a new solution to explain how other minds are intensely expressed in their actions. Vitality forms characterize the expressive style of actions. The effective perception of vitality forms allows people to recognize the affective states and intentions of others in their actions, and could even open the possibility of properties of objects that are indicated by the given actions. Currently, neurophysiological studies present that there might be a neural mirror mechanism in the dorso-central insula (DCI), middle cingulate cortex (MCC), and other related cerebral areas, which serve to preferably perceive and deliver vitality forms of actions. In this article, possible types of vitality forms related to other minds, which have been brought to particular attention in recent years, have been collected and discussed in the following four areas: (1) Vitality forms on understanding non-verbal intention, (2) on understanding verbal intention, (3) vitality forms as grounding social cognition, and (4) as grounding social emotion. These four areas, however, might refer to an entirety of a binary actor-observer communicative landscape. In this review, we try to simplify the analysis by relying on two fundamental dimensions of criteria: first, the idea of vitality forms is conceived as the most basic way of observing subsequent higher-order dimensions of action, that is, understanding intention in the style of action. Thus, in the first two subsections, the relationships between vitality forms and their roles in understanding non-verbal and verbal intention have been discussed. Second, vitality forms could also be conceived as background conditions of all the other mental categories, that is, vitality forms can ground cognition and emotion in a social context. In the second dimension, the existence of social cognition or emotion depends on the existence of the stylistic kinematics of action. A grounding relation is used to distinguish a ground, that is, vitality forms, and its grounded mental categories. As relating with the domain of social perception, in this review, it has been discussed vitality forms possibly could ground social cognition and social emotion, respectively.

Understanding Motivation, Career Planning, and Socio-Cultural Adaptation Difficulties as Determinants of Higher Education Institution Choice Decision by International Students in the Post-pandemic Era

The world is facing an unprecedented health crisis with the spread of COVID-19 across different corners of the globe. This pandemic has raised more significant concerns about international students’ learning environment, personality development, and career planning, particularly in high-ranked institutes in China. Now the question concerning this dilemma is, would the COVID-19 pandemic negatively affect students’ education and the country culture where they are bound to seek information and the subject education? Therefore, this study examines the impact of innovative learning environment, career planning, and socio-cultural adaptation-related difficulties faced by international students as determinants of higher education institution choice decisions made by international students in the post-pandemic era. This quantitative study examined international students in high-ranked universities across China. The data from 260 students were collected through a structured questionnaire and analyzed using the AMOS technique. Moreover, it has been observed that the current global health crisis has intensified social inequalities across different international higher education systems. Countries fail to maintain the scale of the innovative international learning environment. The results further indicated that international students are more considerate of innovative learning environments, cultural adoption, career planning, and personality development, specifically after the outbreak of the COVID-19 pandemic, which has drastically affected the global higher education system. Unusually, more than half of the participants wanted to maintain the option of overall distance education after the pandemic. However, apart from this argument, it is appropriate to demand significant changes in post-pandemic education adapted to the post-digital era and to satisfy the concerns and expectations of the students.

Autistic-Like Traits and Positive Schizotypy as Diametric Specializations of the Predictive Mind

According to the predictive-processing framework, only prediction errors (rather than all sensory inputs) are processed by an organism's perceptual system. Prediction errors can be weighted such that errors from more reliable sources will be more influential in updating prior beliefs. It has previously been argued that autism-spectrum conditions can be understood as resulting from a predictive-processing mechanism in which an inflexibly high weight is given to sensory-prediction errors that results in overfitting their predictive models to the world. Deficits in executive functioning, theory of mind, and central coherence are all argued to flow naturally from this core underlying mechanism. The diametric model of autism and psychosis suggests a simple extension of this hypothesis. If people on the autism spectrum give an inflexibly high weight to sensory input, could it be that people with a predisposition to psychosis (i.e., people high in positive schizotypy) give an inflexibly low weight to sensory input? In this article I argue that evidence strongly supports this hypothesis. An inflexibly low weight given to sensory input can explain such disparate features of positive schizotypy as increased exploratory behavior, apophenia, hyper theory of mind, hyperactive imagination, attentional differences, and having idiosyncratic worldviews.

Therapeutic Alliance as Active Inference: The Role of Therapeutic Touch and Biobehavioural Synchrony in Musculoskeletal Care

Touch is recognised as crucial for survival, fostering cooperative communication, accelerating recovery, reducing hospital stays, and promoting overall wellness and the therapeutic alliance. In this hypothesis and theory paper, we present an entwined model that combines touch for alignment and active inference to explain how the brain develops "priors" necessary for the health care provider to engage with the patient effectively. We appeal to active inference to explain the empirically integrative neurophysiological and behavioural mechanisms that underwrite synchronous relationships through touch. Specifically, we offer a formal framework for understanding - and explaining - the role of therapeutic touch and hands-on care in developing a therapeutic alliance and synchrony between health care providers and their patients in musculoskeletal care. We first review the crucial importance of therapeutic touch and its clinical role in facilitating the formation of a solid therapeutic alliance and in regulating allostasis. We then consider how touch is used clinically - to promote cooperative communication, demonstrate empathy, overcome uncertainty, and infer the mental states of others - through the lens of active inference. We conclude that touch plays a crucial role in achieving successful clinical outcomes and adapting previous priors to create intertwined beliefs. The ensuing framework may help healthcare providers in the field of musculoskeletal care to use hands-on care to strengthen the therapeutic alliance, minimise prediction errors (a.k.a., free energy), and thereby promote recovery from physical and psychological impairments.

Augmenting Human Selves Through Artificial Agents – Lessons From the Brain

Much of current artificial intelligence (AI) and the drive toward artificial general intelligence (AGI) focuses on developing machines for functional tasks that humans accomplish. These may be narrowly specified tasks as in AI, or more general tasks as in AGI – but typically these tasks do not target higher-level human cognitive abilities, such as consciousness or morality; these are left to the realm of so-called “strong AI” or “artificial consciousness.” In this paper, we focus on how a machine can augment humans rather than do what they do, and we extend this beyond AGI-style tasks to augmenting peculiarly personal human capacities, such as wellbeing and morality. We base this proposal on associating such capacities with the “self,” which we define as the “environment-agent nexus”; namely, a fine-tuned interaction of brain with environment in all its relevant variables. We consider richly adaptive architectures that have the potential to implement this interaction by taking lessons from the brain. In particular, we suggest conjoining the free energy principle (FEP) with the dynamic temporo-spatial (TSD) view of neuro-mental processes. Our proposed integration of FEP and TSD – in the implementation of artificial agents – offers a novel, expressive, and explainable way for artificial agents to adapt to different environmental contexts. The targeted applications are broad: from adaptive intelligence augmenting agents (IA’s) that assist psychiatric self-regulation to environmental disaster prediction and personal assistants. This reflects the central role of the mind and moral decision-making in most of what we do as humans.

Biology, Buddhism, and AI: Care as the Driver of Intelligence

Intelligence is a central feature of human beings' primary and interpersonal experience. Understanding how intelligence originated and scaled during evolution is a key challenge for modern biology. Some of the most important approaches to understanding intelligence are the ongoing efforts to build new intelligences in computer science (AI) and bioengineering. However, progress has been stymied by a lack of multidisciplinary consensus on what is central about intelligence regardless of the details of its material composition or origin (evolved vs. engineered). We show that Buddhist concepts offer a unique perspective and facilitate a consilience of biology, cognitive science, and computer science toward understanding intelligence in truly diverse embodiments. In coming decades, chimeric and bioengineering technologies will produce a wide variety of novel beings that look nothing like familiar natural life forms; how shall we gauge their moral responsibility and our own moral obligations toward them, without the familiar touchstones of standard evolved forms as comparison? Such decisions cannot be based on what the agent is made of or how much design vs. natural evolution was involved in their origin. We propose that the scope of our potential relationship with, and so also our moral duty toward, any being can be considered in the light of Care-a robust, practical, and dynamic lynchpin that formalizes the concepts of goal-directedness, stress, and the scaling of intelligence; it provides a rubric that, unlike other current concepts, is likely to not only survive but thrive in the coming advances of AI and bioengineering. We review relevant concepts in basal cognition and Buddhist thought, focusing on the size of an agent's goal space (its cognitive light cone) as an invariant that tightly links intelligence and compassion. Implications range across interpersonal psychology, regenerative medicine, and machine learning. The Bodhisattva's vow ("for the sake of all sentient life, I shall achieve awakening") is a practical design principle for advancing intelligence in our novel creations and in ourselves.

Applying the Free Energy Principle to Complex Adaptive Systems

The free energy principle (FEP) is a formulation of the adaptive, belief-driven behaviour of self-organizing systems that gained prominence in the early 2000s as a unified model of the brain [...].

Enactive-Dynamic Social Cognition and Active Inference

This aim of this paper is two-fold: it critically analyses and rejects accounts blending active inference as theory of mind and enactivism; and it advances an enactivist-dynamic understanding of social cognition that is compatible with active inference. While some social cognition theories seemingly take an enactive perspective on social cognition, they explain it as the attribution of mental states to other people, by assuming representational structures, in line with the classic Theory of Mind (ToM). Holding both enactivism and ToM, we argue, entails contradiction and confusion due to two ToM assumptions widely known to be rejected by enactivism: that (1) social cognition reduces to mental representation and (2) social cognition is a hardwired contentful 'toolkit' or 'starter pack' that fuels the model-like theorising supposed in (1). The paper offers a positive alternative, one that avoids contradictions or confusion. After rejecting ToM-inspired theories of social cognition and clarifying the profile of social cognition under enactivism, that is without assumptions (1) and (2), the last section advances an enactivist-dynamic model of cognition as dynamic, real-time, fluid, contextual social action, where we use the formalisms of dynamical systems theory to explain the origins of socio-cognitive novelty in developmental change and active inference as a tool to demonstrate social understanding as generalised synchronisation.

Empathic Narrative of Online Political Communication

With the rapid development of the Internet, political culture plays an increasingly prominent role in ethical guidance and value orientation, and the intergenerational inheritance of political culture in various countries needs to be carried out in a sophisticated way. From the perspective of empathic narrative, this study applies the network text analysis method to detect the cultural communication regularities to the contemporary young adults in online political communication and explores contemporary young adults' perception of online political culture through empirical analysis. Moreover, it proposes the empathic narrative logic of online political communication by comparing the existing communication elements and the urgently needed communication elements. Our findings suggest that we need to deepen the cognitive empathy, stabilize the emotional empathy, and adjust the emotional bias in online political communication.

Integrating Evolutionary, Cultural, and Computational Psychiatry: A Multilevel Systemic Approach

This paper proposes an integrative perspective on evolutionary, cultural and computational approaches to psychiatry. These three approaches attempt to frame mental disorders as multiscale entities and offer modes of explanations and modeling strategies that can inform clinical practice. Although each of these perspectives involves systemic thinking, each is limited in its ability to address the complex developmental trajectories and larger social systemic interactions that lead to mental disorders. Inspired by computational modeling in theoretical biology, this paper aims to integrate the modes of explanation offered by evolutionary, cultural and computational psychiatry in a multilevel systemic perspective. We apply the resulting Evolutionary, Cultural and Computational (ECC) model to Major Depressive Disorder (MDD) to illustrate how this integrative approach can guide research and practice in psychiatry.

Epistemic Communities under Active Inference

The spread of ideas is a fundamental concern of today's news ecology. Understanding the dynamics of the spread of information and its co-option by interested parties is of critical importance. Research on this topic has shown that individuals tend to cluster in echo-chambers and are driven by confirmation bias. In this paper, we leverage the active inference framework to provide an in silico model of confirmation bias and its effect on echo-chamber formation. We build a model based on active inference, where agents tend to sample information in order to justify their own view of reality, which eventually leads to them to have a high degree of certainty about their own beliefs. We show that, once agents have reached a certain level of certainty about their beliefs, it becomes very difficult to get them to change their views. This system of self-confirming beliefs is upheld and reinforced by the evolving relationship between an agent's beliefs and observations, which over time will continue to provide evidence for their ingrained ideas about the world. The epistemic communities that are consolidated by these shared beliefs, in turn, tend to produce perceptions of reality that reinforce those shared beliefs. We provide an active inference account of this community formation mechanism. We postulate that agents are driven by the epistemic value that they obtain from sampling or observing the behaviours of other agents. Inspired by digital social networks like Twitter, we build a generative model in which agents generate observable social claims or posts (e.g., 'tweets') while reading the socially observable claims of other agents that lend support to one of two mutually exclusive abstract topics. Agents can choose which other agent they pay attention to at each timestep, and crucially who they attend to and what they choose to read influences their beliefs about the world. Agents also assess their local network's perspective, influencing which kinds of posts they expect to see other agents making. The model was built and simulated using the freely available Python package pymdp. The proposed active inference model can reproduce the formation of echo-chambers over social networks, and gives us insight into the cognitive processes that lead to this phenomenon.

From Generative Models to Generative Passages: A Computational Approach to (Neuro) Phenomenology

This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. Our approach can be described as computational phenomenology because it applies methods originally developed in computational modelling to provide a formal model of the descriptions of lived experience in the phenomenological tradition of philosophy (e.g., the work of Edmund Husserl, Maurice Merleau-Ponty, etc.). The first section presents a brief review of the overall project to naturalize phenomenology. The second section presents and evaluates philosophical objections to that project and situates our version of computational phenomenology with respect to these projects. The third section reviews the generative modelling framework. The final section presents our approach in detail. We conclude by discussing how our approach differs from previous attempts to use generative modelling to help understand consciousness. In summary, we describe a version of computational phenomenology which uses generative modelling to construct a computational model of the inferential or interpretive processes that best explain this or that kind of lived experience.

Osteopathic Care as (En)active Inference: A Theoretical Framework for Developing an Integrative Hypothesis in Osteopathy

Osteopathy is a person-centred healthcare discipline that emphasizes the body’s structure-function interrelationship—and its self-regulatory mechanisms—to inform a whole-person approach to health and wellbeing. This paper aims to provide a theoretical framework for developing an integrative hypothesis in osteopathy, which is based on the enactivist and active inference accounts. We propose that osteopathic care can be reconceptualised under (En)active inference as a unifying framework. Active inference suggests that action-perception cycles operate to minimize uncertainty and optimize an individual’s internal model of the lived world and, crucially, the consequences of their behaviour. We argue that (En)active inference offers an integrative framework for osteopathy, which can evince the mechanisms underlying dyadic and triadic (e.g., in paediatric care) exchanges and osteopathic care outcomes. We propose that this theoretical framework can underpin osteopathic care across the lifespan, from preterm infants to the elderly and those with persistent pain and other physical symptoms. In situations of chronicity, as an ecological niche, the patient-practitioner dyad provides the osteopath and the patient with a set of affordances, i.e., possibilities for action provided by the environment, that through shared intentionally, can promote adaptations and restoration of productive agency. Through a dyadic therapeutic relationship, as they engage with their ecological niche’s affordances—a structured set of affordances shared by agents—osteopath and patient actively construct a shared sense-making narrative and realise a shared generative model of their relation to the niche. In general, touch plays a critical role in developing a robust therapeutic alliance, mental state alignment, and biobehavioural synchrony between patient and practitioner. However, its role is particularly crucial in the fields of neonatology and paediatrics, where it becomes central in regulating allostasis and restoring homeostasis. We argue that from an active inference standpoint, the dyadic shared ecological niche underwrites a robust therapeutic alliance, which is crucial to the effectiveness of osteopathic care. Considerations and implications of this model—to clinical practice and research, both within- and outside osteopathy—are critically discussed.

Therapeutic Alliance as Active Inference: The Role of Therapeutic Touch and Synchrony

Recognizing and aligning individuals' unique adaptive beliefs or "priors" through cooperative communication is critical to establishing a therapeutic relationship and alliance. Using active inference, we present an empirical integrative account of the biobehavioral mechanisms that underwrite therapeutic relationships. A significant mode of establishing cooperative alliances-and potential synchrony relationships-is through ostensive cues generated by repetitive coupling during dynamic touch. Established models speak to the unique role of affectionate touch in developing communication, interpersonal interactions, and a wide variety of therapeutic benefits for patients of all ages; both neurophysiologically and behaviorally. The purpose of this article is to argue for the importance of therapeutic touch in establishing a therapeutic alliance and, ultimately, synchrony between practitioner and patient. We briefly overview the importance and role of therapeutic alliance in prosocial and clinical interactions. We then discuss how cooperative communication and mental state alignment-in intentional communication-are accomplished using active inference. We argue that alignment through active inference facilitates synchrony and communication. The ensuing account is extended to include the role of (C-) tactile afferents in realizing the beneficial effect of therapeutic synchrony. We conclude by proposing a method for synchronizing the effects of touch using the concept of active inference.

The evolution of brain architectures for predictive coding and active inference

This article considers the evolution of brain architectures for predictive processing. We argue that brain mechanisms for predictive perception and action are not late evolutionary additions of advanced creatures like us. Rather, they emerged gradually from simpler predictive loops (e.g. autonomic and motor reflexes) that were a legacy from our earlier evolutionary ancestors-and were key to solving their fundamental problems of adaptive regulation. We characterize simpler-to-more-complex brains formally, in terms of generative models that include predictive loops of increasing hierarchical breadth and depth. These may start from a simple homeostatic motif and be elaborated during evolution in four main ways: these include the multimodal expansion of predictive control into an allostatic loop; its duplication to form multiple sensorimotor loops that expand an animal's behavioural repertoire; and the gradual endowment of generative models with hierarchical depth (to deal with aspects of the world that unfold at different spatial scales) and temporal depth (to select plans in a future-oriented manner). In turn, these elaborations underwrite the solution to biological regulation problems faced by increasingly sophisticated animals. Our proposal aligns neuroscientific theorising-about predictive processing-with evolutionary and comparative data on brain architectures in different animal species. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

Permutation Entropy as a Universal Disorder Criterion: How Disorders at Different Scale Levels Are Manifestations of the Same Underlying Principle

What do bacteria, cells, organs, people, and social communities have in common? At first sight, perhaps not much. They involve totally different agents and scale levels of observation. On second thought, however, perhaps they share everything. A growing body of literature suggests that living systems at different scale levels of observation follow the same architectural principles and process information in similar ways. Moreover, such systems appear to respond in similar ways to rising levels of stress, especially when stress levels approach near-lethal levels. To explain such communalities, we argue that all organisms (including humans) can be modeled as hierarchical Bayesian controls systems that are governed by the same biophysical principles. Such systems show generic changes when taxed beyond their ability to correct for environmental disturbances. Without exception, stressed organisms show rising levels of 'disorder' (randomness, unpredictability) in internal message passing and overt behavior. We argue that such changes can be explained by a collapse of allostatic (high-level integrative) control, which normally synchronizes activity of the various components of a living system to produce order. The selective overload and cascading failure of highly connected (hub) nodes flattens hierarchical control, producing maladaptive behavior. Thus, we present a theory according to which organic concepts such as stress, a loss of control, disorder, disease, and death can be operationalized in biophysical terms that apply to all scale levels of organization. Given the presumed universality of this mechanism, 'losing control' appears to involve the same process anywhere, whether involving bacteria succumbing to an antibiotic agent, people suffering from physical or mental disorders, or social systems slipping into warfare. On a practical note, measures of disorder may serve as early warning signs of system failure even when catastrophic failure is still some distance away.

An active inference account of protective behaviours during the COVID-19 pandemic

Newly emerging infectious diseases, such as the coronavirus (COVID-19), create new challenges for public healthcare systems. Before effective treatments, countering the spread of these infections depends on mitigating, protective behaviours such as social distancing, respecting lockdown, wearing masks, frequent handwashing, travel restrictions, and vaccine acceptance. Previous work has shown that the enacting protective behaviours depends on beliefs about individual vulnerability, threat severity, and one's ability to engage in such protective actions. However, little is known about the genesis of these beliefs in response to an infectious disease epidemic, and the cognitive mechanisms that may link these beliefs to decision making. Active inference (AI) is a recent approach to behavioural modelling that integrates embodied perception, action, belief updating, and decision making. This approach provides a framework to understand the behaviour of agents in situations that require planning under uncertainty. It assumes that the brain infers the hidden states that cause sensations, predicts the perceptual feedback produced by adaptive actions, and chooses actions that minimize expected surprise in the future. In this paper, we present a computational account describing how individuals update their beliefs about the risks and thereby commit to protective behaviours. We show how perceived risks, beliefs about future states, sensory uncertainty, and outcomes under each policy can determine individual protective behaviours. We suggest that these mechanisms are crucial to assess how individuals cope with uncertainty during a pandemic, and we show the interest of these new perspectives for public health policies.

The Markov blanket trick: On the scope of the free energy principle and active inference

The free energy principle (FEP) has been presented as a unified brain theory, as a general principle for the self-organization of biological systems, and most recently as a principle for a theory of every thing. Additionally, active inference has been proposed as the process theory entailed by FEP that is able to model the full range of biological and cognitive events. In this paper, we challenge these two claims. We argue that FEP is not the general principle it is claimed to be, and that active inference is not the all-encompassing process theory it is purported to be either. The core aspects of our argumentation are that (i) FEP is just a way to generalize Bayesian inference to all domains by the use of a Markov blanket formalism, a generalization we call the Markov blanket trick; and that (ii) active inference presupposes successful perception and action instead of explaining them.

Stuck in a lockdown: Dreams, bad dreams, nightmares, and their relationship to stress, depression and anxiety during the COVID-19 pandemic

BACKGROUND

An upsurge in dream and nightmare frequency has been noted since the beginning of the COVID-19 pandemic and research shows increases in levels of stress, depression and anxiety during this time. Growing evidence suggests that dream content has a bi-directional relationship with psychopathology, and that dreams react to new, personally significant and emotional experiences. The first lockdown experience was an acute event, characterized by a combination of several unprecedent factors (new pandemic, threat of disease, global uncertainty, the experience of social isolation and exposure to stressful information) that resulted in a large-scale disruption of life routines. This study aimed at investigating changes in dream, bad dream and nightmare recall; most prevalent dream themes; and the relationship between dreams, bad dreams, nightmares and symptoms of stress, depression and anxiety during the first COVID-19 lockdown (April-May 2020) through a national online survey.

METHODS

968 participants completed an online survey. Dream themes were measured using the Typical Dreams Questionnaire; stress levels were measured by the Cohen's Perceived Stress Scale; symptoms of anxiety were assessed by Generalized Anxiety Disorder (GAD-7) scale; and symptoms of depression were assessed using the Quick Inventory of Depressive Symptomatology.

RESULTS

34% (328) of participants reported increased dream recall during the lockdown. The most common dream themes were centered around the topics of 1) inefficacy (e.g., trying again and again, arriving late), 2) human threat (e.g., being chased, attacked); 3) death; and 4) pandemic imagery (e.g., being separated from loved ones, being sick). Dream, bad dream and nightmare frequency was highest in individuals with moderate to severe stress levels. Frequency of bad dreams, nightmares, and dreams about the pandemic, inefficacy, and death were associated with higher levels of stress, as well as with greater symptoms of depression and anxiety.

CONCLUSIONS

Results support theories of dream formation, environmental susceptibility and stress reactivity. Dream content during the lockdown broadly reflected existential concerns and was associated with increased symptoms of mental health indices.

Intersubjectivity and social learning: Representation of beliefs enables the accumulation of cultural knowledge

I accept the main thesis of the article according to which representation of knowledge is more basic than representation of belief. But I question the authors' contention that humans' unique capacity to represent belief does not underwrite the capacity for the accumulation of cultural knowledge.