On the Self-Organizing Origins of Agency

Promises and limits of an agency perspective in evolutionary developmental biology

An agent-based perspective in the study of complex systems is well established in diverse disciplines, yet is only beginning to be applied to evolutionary developmental biology. In this essay, we begin by defining agency and associated terminology formally. We then explore the assumptions and predictions of an agency perspective, apply these to select processes and key concept areas relevant to practitioners of evolutionary developmental biology, and consider the potential epistemic roles that an agency perspective might play in evo devo. Throughout, we discuss evidence supportive of agential dynamics in biological systems relevant to evo devo and explore where agency thinking may enrich the explanatory reach of research efforts in evolutionary developmental biology.

2D Capsule Networks Detect Perceived Changes in Infant∼Environment Relationship Reflected in 3D Movement Dynamics

Can infant exploration and causal discovery be detected using Artificial Intelligence (AI)? A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment (i.e., tethering one foot to a colorful mobile). Vicon motion capture data from multiple infant joints were used here to create Histograms of Joint Displacements (HJDs) to generate pose-based descriptors for 3D infant spatial trajectories. Using HJDs as inputs, machine and deep learning systems were tasked with classifying the experimental state from which snippets of movement data were sampled. The architectures tested included k-Nearest Neighbour (kNN), Linear Discriminant Analysis (LDA), Fully connected network (FCNet), 1D-Convolutional Neural Network (1D-Conv), 1D-Capsule Network (1D-CapsNet), 2D-Conv and 2D-CapsNet. Sliding window scenarios were used for temporal analysis to search for topological changes in infant movement related to functional context. kNN and LDA achieved higher classification accuracy with single joint features, while deep learning approaches, particularly 2D-CapsNet, achieved higher accuracy on full-body features. For each AI architecture tested, measures of foot activity displayed the most distinct and coherent pattern alterations across different experimental stages (reflected in the highest classification accuracy rate), indicating that interaction with the world impacts the infant behaviour most at the site of organism∼world connection. Pairing theory-driven experimentation with AI tools thus opens a path to developing functionally-relevant assessments of infant behaviour that are likely to be useful in clinical settings.

Dynamical systems model of development of the action differentiation in early infancy: a requisite of physical agency

Young infants are sensitive to whether their body movements cause subsequent events or not during the interaction with the environment. This ability has been revealed by empirical studies on the reinforcement of limb movements when a string is attached between an infant limb and a mobile toy suspended overhead. A previous study reproduced the experimental observation by modeling both the infant's limb and a mobile toy as a system of coupled oscillators. The authors then argued that emergence of agency could be explained by a phase transition in the dynamical system: from a weakly coupled state to a state where the both movements of the limb and the toy are highly coordinated. However, what remains unexplained is the following experimental observation: When the limb is connected to the mobile toy by a string, the infant increases the average velocity of the arm's movement. On the other hand, when the toy is controlled externally, the average arm's velocity is greatly reduced. Since young infants produce exuberant spontaneous movements even with no external stimuli, the inhibition of motor action to suppress the formation of spurious action-perception coupling should be also a crucial sign for the emergence of agency. Thus, we present a dynamical system model for the development of action differentiation, to move or not to move, in the mobile task. In addition to the pair of limb and mobile oscillators for providing positive feedback for reinforcement in the previous model, bifurcation dynamics are incorporated to enhance or inhibit self-movements in response to detecting contingencies between the limb and mobile movements. The results from computer simulations reproduce experimental observations on the developmental emergence of action differentiation between 2 and 3 months of age in the form of a bifurcation diagram. We infer that the emergence of physical agency entails young infants' ability not only to enhance a specific action-perception coupling, but also to decouple it and create a new mode of action-perception coupling based on the internal state dynamics with contingency detection between self-generated actions and environmental events.

Mind the matter: Active matter, soft robotics, and the making of bio-inspired artificial intelligence

Philosophical and theoretical debates on the multiple realisability of the cognitive have historically influenced discussions of the possible systems capable of instantiating complex functions like memory, learning, goal-directedness, and decision-making. These debates have had the corollary of undermining, if not altogether neglecting, the materiality and corporeality of cognition-treating material, living processes as "hardware" problems that can be abstracted out and, in principle, implemented in a variety of materials-in particular on digital computers and in the form of state-of-the-art neural networks. In sum, the matter in se has been taken not to matter for cognition. However, in this paper, we argue that the materiality of cognition-and the living, self-organizing processes that it enables-requires a more detailed assessment when understanding the nature of cognition and recreating it in the field of embodied robotics. Or, in slogan form, that the matter matters for cognitive form and function. We pull from the fields of Active Matter Physics, Soft Robotics, and Basal Cognition literature to suggest that the imbrication between material and cognitive processes is closer than standard accounts of multiple realisability suggest. In light of this, we propose upgrading the notion of multiple realisability from the standard version-what we call 1.0-to a more nuanced conception 2.0 to better reflect the recent empirical advancements, while at the same time averting many of the problems that have been raised for it. These fields are actively reshaping the terrain in which we understand materiality and how it enables, mediates, and constrains cognition. We propose that taking the materiality of our embodied, precarious nature seriously furnishes an important research avenue for the development of embodied robots that autonomously value, engage, and interact with the environment in a goal-directed manner, in response to existential needs of survival, persistence, and, ultimately, reproduction. Thus, we argue that by placing further emphasis on the soft, active, and plastic nature of the materials that constitute cognitive embodiment, we can move further in the direction of autonomous embodied robots and Artificial Intelligence.

Modelling brain dynamics by Boolean networks

Understanding the relationship between brain architecture and brain function is a central issue in neuroscience. We modeled realistic spatio-temporal patterns of brain activity on a human connectome with a Boolean networks model with the aim of computationally replicating certain cognitive functions as they emerge from the standardization of many fMRI studies, identified as patterns of human brain activity. Results from the analysis of simulation data, carried out for different parameters and initial conditions identified many possible paths in the space of parameters of these network models, with normal (ordered asymptotically constant patterns), chaotic (oscillating or disordered) but also highly organized configurations, with countless spatial–temporal patterns. We interpreted these results as routes to chaos, permanence of the systems in regimes of complexity, and ordered stationary behavior, associating these dynamics to cognitive processes. The most important result of this work is the study of emergent neural circuits, i.e., configurations of areas that synchronize over time, both locally and globally, determining the emergence of computational analogues of cognitive processes, which may or may not be similar to the functioning of biological brain. Furthermore, results put in evidence the creation of how the brain creates structures of remote communication. These structures have hierarchical organization, where each level allows for the emergence of brain organizations which behave at the next superior level. Taken together these results allow the interplay of dynamical and topological roots of the multifaceted brain dynamics to be understood.

Developmental shifts in computations used to detect environmental controllability

Accurate assessment of environmental controllability enables individuals to adaptively adjust their behavior—exploiting rewards when desirable outcomes are contingent upon their actions and minimizing costly deliberation when their actions are inconsequential. However, it remains unclear how estimation of environmental controllability changes from childhood to adulthood. Ninety participants (ages 8–25) completed a task that covertly alternated between controllable and uncontrollable conditions, requiring them to explore different actions to discover the current degree of environmental controllability. We found that while children were able to distinguish controllable and uncontrollable conditions, accuracy of controllability assessments improved with age. Computational modeling revealed that whereas younger participants’ controllability assessments relied on evidence gleaned through random exploration, older participants more effectively recruited their task structure knowledge to make highly informative interventions. Age-related improvements in working memory mediated this qualitative shift toward increased use of an inferential strategy. Collectively, these findings reveal an age-related shift in the cognitive processes engaged to assess environmental controllability. Improved detection of environmental controllability may foster increasingly adaptive behavior over development by revealing when actions can be leveraged for one’s benefit.

The ability to determine when one’s actions are consequential organizes learning and decision making across the lifespan. However, few studies have examined how the ability to detect control over our environment changes from childhood to adulthood. Here, we leveraged a computational modeling framework to characterize the component learning processes underlying controllability assessment in children, adolescents, and adults. We observed age-related improvements in controllability assessment that stemmed from an increasing ability to represent contingencies between states and actions and to use that knowledge to make informative interventions that yield diagnostic evidence of the current degree of control. Increasing ability to accurately assess environmental controllability may confer greater recognition of opportunities to adaptively pursue rewards through goal-directed action across development.

The verb-self link: An implicit association test study

Agency is defined as the ability to assign and pursue goals. Given people’s focus on achieving their own goals, agency has been found to be strongly linked to the self. In two studies (N = 168), we examined whether this self–agency link is visible from a linguistic perspective. As the preferred grammatical category to convey agency is verbs, we hypothesize that, in the Implicit Association Test (IAT), verbs (vs. nouns) would be associated more strongly with the self (vs. others). Our results confirmed this hypothesis. Participants exhibited particularly fast responses when reading self-related stimuli (e.g., “me” or “my”) and verb stimuli (e.g., “deflect” or “contemplate”) both necessitated pressing an identical rather than different response keys in the IAT (d = .25). The finding connects two streams of literature—on the link between agency and verbs and on the link between self and agency—suggesting a triad between self, agency, and verbs. We argue that this verb–self link (1) opens up new perspectives for understanding linguistic expressions of agency and (2) expands our understanding of how word choice impacts socio-cognitive processing.

The Cognitive, Ecological, and Developmental Origins of Self-Disturbance in Borderline Personality Disorder

Self-disturbance is recognized as a key symptom of Borderline Personality Disorder (BPD). Although it is the source of significant distress and significant costs to society, it is still poorly specified. In addition, current research and models on the etiology of BPD do not provide sufficient evidence or predictions about who is at risk of developing BPD and self-disturbance, and why. The aim of this review is to lay the foundations of a new model inspired by recent developments at the intersection of social cognition, behavioral ecology, and developmental biology. We argue that the sense of agency is an important dimension to consider when characterizing self-disturbances in BPD. Second, we address the poorly characterized relation between self-disturbances and adverse life conditions encountered early in life. We highlight the potential relevance of Life-History Theory-a major framework in evolutionary developmental biology-to make sense of this association. We put forward the idea that the effect of early life adversity on BPD symptomatology depends on the way individuals trade their limited resources between competing biological functions during development.

Reciprocity and alignment: quantifying coupling in dynamic interactions

Recent accounts of social cognition focus on how we do things together, suggesting that becoming aligned relies on a reciprocal exchange of information. The next step is to develop richer computational methods that quantify the degree of coupling and describe the nature of the information exchange. We put forward a definition of coupling, comparing it to related terminology and detail, available computational methods and the level of organization to which they pertain, presenting them as a hierarchy from weakest to richest forms of coupling. The rationale is that a temporally coherent link between two dynamical systems at the lowest level of organization sustains mutual adaptation and alignment at the highest level. Postulating that when we do things together, we do so dynamically over time and we argue that to determine and measure instances of true reciprocity in social exchanges is key. Along with this computationally rich definition of coupling, we present challenges for the field to be tackled by a diverse community working towards a dynamic account of social cognition.

Metacybernetics: Towards a General Theory of Higher Order Cybernetics

Metacybernetics refers to the higher cybernetic orders that arise in living system agencies. Agencies are complex, and for them to be viable and hence survive, they require both stability and uncertainty reduction. Metacybernetics is defined through a metasystem hierarchy, and is mostly known through 1st and 2nd order cybernetics. In this exploratory paper the purpose is to create a framework that can underpin metacybernetics and explain the relationship between different cybernetic orders. The framework is built on agency theory which has both substructural and superstructural dimensions. Substructure has an interest in stability, is concerned with the generation of higher cybernetic orders, and is serviced by horizontal recursion. Superstructure is concerned with uncertainty reduction by uncovering hidden material or regulatory relationships, and is serviced by vertical recursion. Philosophical aspects to the framework are discussed, making distinction between global rationality through critical realism, and local rationality that relates to different cybernetic orders that correspond to bounding paradigms like positivism and constructivism.

Making the World Behave: A New Embodied Account on Mobile Paradigm

In this review article, we describe the mobile paradigm, a method used for more than 50 years to assess how infants learn and remember sensorimotor contingencies. The literature on the mobile paradigm demonstrates that infants below 6 months of age can remember the learning environment weeks after when reminded periodically and integrate temporally distributed information across modalities. The latter ability is only possible if events occur within a temporal window of a few days, and the width of this required window changes as a function of age. A major critique of these conclusions is that the majority of this literature has neglected the embodied experience, such that motor behavior was considered an equivalent developmental substitute for verbal behavior. Over recent years, simulation and empirical work have highlighted the sensorimotor aspect and opened up a discussion for possible learning mechanisms and variability in motor preferences of young infants. In line with this recent direction, we present a new embodied account on the mobile paradigm which argues that learning sensorimotor contingencies is a core feature of development forming the basis for active exploration of the world and body. In addition to better explaining recent findings, this new framework aims to replace the dis-embodied approach to the mobile paradigm with a new understanding that focuses on variance and representations grounded in sensorimotor experience. Finally, we discuss a potential role for the dorsal stream which might be responsible for guiding action according to visual information, while infants learn sensorimotor contingencies in the mobile paradigm.

An Algorithmic Metaphysics of Self-Patterns

The paper draws on an algorithmic criterion to demonstrate that the self (as initially described in Shaun Gallagher’s a pattern theory of self) is a composite, scattered, and patterned object. It also addresses the question of extendedness of the self-pattern. Based on the criteria drawn from algorithmic complexity, I argue that although the self-pattern possesses a genuinely extended aspect (and in this sense, the self-pattern is minimally extended) the self-pattern and its environment do not constitute a genuine composite object.

Intentional Binding Effects in the Experience of Noticing the Regularity of a Perceptual-Motor Task

Noticing the regularity of the task is necessary to enhance motor performance. The experience of noticing further motivates improvement in motor performance. Motor control is explained by a comparator model that modifies the motor command to reduce discrepancies between sensory predictions and actual outcomes. A similar model could apply to sense of agency (SoA). SoA refers to the sensation of controlling one’s own actions and, through them, the outcomes in the external world. SoA may also be enhanced by the experience of noticing errors. We recently reported gradual enhancement of SoA in participants with high perceptual-motor performance. However, what component of the motor task changed the SoA is unclear. In this study, we aimed to investigate the influence over time of the experience of noticing during a motor task on SoA. Participants performed an implicit regularity perceptual-motor task and an intentional binding task (a method that can quantitatively measure SoA) simultaneously. We separated participants into groups after the experiment based on noticing or not noticing the regularity. SoA was gradually enhanced in the noticing group, compared with that of the non-noticing group. The results suggest that the experience of noticing may enhance SoA during perceptual-motor tasks.

Coordination Dynamics: A Foundation for Understanding Social Behavior

Humans' interactions with each other or with socially competent machines exhibit lawful coordination patterns at multiple levels of description. According to Coordination Dynamics, such laws specify the flow of coordination states produced by functional synergies of elements (e.g., cells, body parts, brain areas, people…) that are temporarily organized as single, coherent units. These coordinative structures or synergies may be mathematically characterized as informationally coupled self-organizing dynamical systems (Coordination Dynamics). In this paper, we start from a simple foundation, an elemental model system for social interactions, whose behavior has been captured in the Haken-Kelso-Bunz (HKB) model. We follow a tried and tested scientific method that tightly interweaves experimental neurobehavioral studies and mathematical models. We use this method to further develop a body of empirical research that advances the theory toward more generalized forms. In concordance with this interdisciplinary spirit, the present paper is written both as an overview of relevant advances and as an introduction to its mathematical underpinnings. We demonstrate HKB's evolution in the context of social coordination along several directions, with its applicability growing to increasingly complex scenarios. In particular, we show that accommodating for symmetry breaking in intrinsic dynamics and coupling, multiscale generalization and adaptation are principal evolutions. We conclude that a general framework for social coordination dynamics is on the horizon, in which models support experiments with hypothesis generation and mechanistic insights.

A World Unto Itself: Human Communication as Active Inference

Recent theoretical work in developmental psychology suggests that humans are predisposed to align their mental states with those of other individuals. One way this manifests is in cooperative communication; that is, intentional communication aimed at aligning individuals' mental states with respect to events in their shared environment. This idea has received strong empirical support. The purpose of this paper is to extend this account by proposing an integrative model of the biobehavioral dynamics of cooperative communication. Our formulation is based on active inference. Active inference suggests that action-perception cycles operate to minimize uncertainty and optimize an individual's internal model of the world. We propose that humans are characterized by an evolved adaptive prior belief that their mental states are aligned with, or similar to, those of conspecifics (i.e., that 'we are the same sort of creature, inhabiting the same sort of niche'). The use of cooperative communication emerges as the principal means to gather evidence for this belief, allowing for the development of a shared narrative that is used to disambiguate interactants' (hidden and inferred) mental states. Thus, by using cooperative communication, individuals effectively attune to a hermeneutic niche composed, in part, of others' mental states; and, reciprocally, attune the niche to their own ends via epistemic niche construction. This means that niche construction enables features of the niche to encode precise, reliable cues about the deontic or shared value of certain action policies (e.g., the utility of using communicative constructions to disambiguate mental states, given expectations about shared prior beliefs). In turn, the alignment of mental states (prior beliefs) enables the emergence of a novel, contextualizing scale of cultural dynamics that encompasses the actions and mental states of the ensemble of interactants and their shared environment. The dynamics of this contextualizing layer of cultural organization feedback, across scales, to constrain the variability of the prior expectations of the individuals who constitute it. Our theory additionally builds upon the active inference literature by introducing a new set of neurobiologically plausible computational hypotheses for cooperative communication. We conclude with directions for future research.

Cooperative Phase Adaptation and Amplitude Amplification of Neuronal Activity in the Vagal Complex: An Interplay Between Microcircuits and Macrocircuits

Clusters of neurons can communicate with others through the cross-frequency coupling mechanism of oscillatory synchrony. We addressed the hypothesis that neuronal networks at various levels from micro- to macrocircuits implement this communication strategy. An abundance of local recurrent axons of vagal complex (VC) cells establish dense local microcircuits and seem to generate high-frequency noise-causing stochastic resonance (reverberation) and coherence resonance, even in in vitro slice preparations. These phenomena were observed in vitro as the generation of episodes of higher-frequency noise after an external stimulation and as stimulus-induced or spontaneous high-amplitude signals (postsynaptic activities). The in vitro microcircuit networks rarely sustained the stochastic resonance and coherence resonance cooperatively; however, in vivo networks involving additional intrabulbar mesocircuits and large-scale macrocircuits were able to sustain them cooperatively. This gave rise to large-scale oscillatory synchrony leading to robust power and coherence of signals with high amplitudes, reaching several millivolts in amplitude from a noise level of ~100 microV through cardiorespiratory frequency coupling. A regenerative mechanism of neuronal circuits might work for the generation of large-scale oscillatory synchrony. The amplitude and phase of neuronal activity in vivo may interact cooperatively to give rise to varying degrees of power and coherence of robust rhythmic activity for distinct physiological roles. The cooperative interaction between phase adaptation and amplitude amplification of neuronal activity may provide diverse nervous systems with both robustness and resilience.

Thematic roles: Core knowledge or linguistic construct?

The status of thematic roles such as Agent and Patient in cognitive science is highly controversial: To some they are universal components of core knowledge, to others they are scholarly fictions without psychological reality. We address this debate by posing two critical questions: to what extent do humans represent events in terms of abstract role categories, and to what extent are these categories shaped by universal cognitive biases? We review a range of literature that contributes answers to these questions: psycholinguistic and event cognition experiments with adults, children, and infants; typological studies grounded in cross-linguistic data; and studies of emerging sign languages. We pose these questions for a variety of roles and find that the answers depend on the role. For Agents and Patients, there is strong evidence for abstract role categories and a universal bias to distinguish the two roles. For Goals and Recipients, we find clear evidence for abstraction but mixed evidence as to whether there is a bias to encode Goals and Recipients as part of one or two distinct categories. Finally, we discuss the Instrumental role and do not find clear evidence for either abstraction or universal biases to structure instrumental categories.

A match does not make a sense: on the sufficiency of the comparator model for explaining the sense of agency

The development of a sense of agency is indispensable for a cognitive entity (biological or artificial) to become a cognitive agent. In developmental psychology, researchers have taken inspiration from adult cognitive psychology and neuroscience literature and use the comparator model to assess the presence of a sense of agency in early infancy. Similarly, robotics researchers have taken components of the proposed mechanism in attempts to build a sense of agency into artificial systems. In this article, we identify an invalidating theoretical flaw in the reasoning underlying this conversion from adult studies to developmental science and cognitive systems research, rooted in an oversight in the conceptualization of the comparator model as currently used in experimental practice. In these experiments, the emphasis has been put solely on testing for a match between predicted and observed sensory consequences. We argue that the match by itself can exclusively generate a simple categorization or a representation of equality between predicted and observed sensory consequences, both of which are insufficient to generate the causal representations required for a sense of agency. Consequently, the comparator model, as it has been described in the context of the sense of agency and as it is commonly used in experimental designs, is insufficient to generate the sense of agency: infants and robots require more than developing the ability to match predicted and observed sensory consequences for a sense of agency. We conclude with outlining possible solutions and future directions for researchers in developmental science and artificial intelligence.

Distributed cognition criteria: Defined, operationalized, and applied to human-dog systems

Distributed cognition generally refers to situations in which task requirements are shared among multiple agents or, potentially, off-loaded onto the environment. With few exceptions, socially distributed cognition has largely been discussed in terms of intraspecific interactions. This conception fails to capture some forms of group-level cognition among human and non-human animals that are not readily measured or explained in mentalistic or verbal terms. In response to these limitations, we argue for a more stringent set of empirically-verifiable criteria for assessing whether a system is an instance of distributed cognition: interaction-dominant dynamics, agency, and shared task orientation. We apply this framework to humans and working dogs, and contrast the human-dog socially distributed cognitive system with humans using non-biological tools and human interaction with draft animals. The human-dog system illustrates three operationalizable factors for classifying phenomena as socially distributed cognition and extends the framework to interspecies distributed cognition.

Can infants' sense of agency be found in their behavior? Insights from babybot simulations of the mobile-paradigm

The development of a sense of agency is essential for understanding the causal structure of the world. Previous studies have shown that infants tend to increase the frequency of an action when it is followed by an effect. This was shown, for instance, in the mobile-paradigm, in which infants were in control of moving an overhead mobile by means of a ribbon attached to one of their limbs. These findings have been interpreted as evidence for a sense of agency early in life, as infants were thought to have detected the causal action-movement relation. We argue that solely the increase in action frequency is insufficient as evidence for this claim. Computer simulations are used to demonstrate that systematic, limb-specific increase in movement frequency found in mobile-paradigm studies can be produced by an artificial agent (a 'babybot') implemented with a mechanism that does not represent cause-effect relations at all. Given that a sense of agency requires representing one's actions as the cause of the effect, a behavior that is reproduced with this non-representational babybot can be argued to be, in itself, insufficient as evidence for a sense of agency. However, a behavioral pattern that to date has received little attention in the context of sense of agency, namely an additional increase in movement frequency after the action-effect relation is discontinued, is not produced by the babybot. Future research could benefit from focusing on patterns whose production cannot be reproduced by our babybot as these may require the capacity for causal learning.