The mechanics of embodiment: a dialog on embodiment and computational modeling

Divergent and Convergent Creativity Are Different Kinds of Foraging

According to accounts of neural reuse and embodied cognition, higher-level cognitive abilities recycle evolutionarily ancient mechanisms for perception and action. Here, building on these accounts, we investigate whether creativity builds on our capacity to forage in space ("creativity as strategic foraging"). We report systematic connections between specific forms of creative thinking-divergent and convergent-and corresponding strategies for searching in space. U.S. American adults completed two tasks designed to measure creativity. Before each creativity trial, participants completed an unrelated search of a city map. Between subjects, we manipulated the search pattern, with some participants seeking multiple, dispersed spatial locations and others repeatedly converging on the same location. Participants who searched divergently in space were better at divergent thinking but worse at convergent thinking; this pattern reversed for participants who had converged repeatedly on a single location. These results demonstrate a targeted link between foraging and creativity, thus advancing our understanding of the origins and mechanisms of high-level cognition.

Active reinforcement learning versus action bias and hysteresis: control with a mixture of experts and nonexperts

Active reinforcement learning enables dynamic prediction and control, where one should not only maximize rewards but also minimize costs such as of inference, decisions, actions, and time. For an embodied agent such as a human, decisions are also shaped by physical aspects of actions. Beyond the effects of reward outcomes on learning processes, to what extent can modeling of behavior in a reinforcement-learning task be complicated by other sources of variance in sequential action choices? What of the effects of action bias (for actions per se) and action hysteresis determined by the history of actions chosen previously? The present study addressed these questions with incremental assembly of models for the sequential choice data from a task with hierarchical structure for additional complexity in learning. With systematic comparison and falsification of computational models, human choices were tested for signatures of parallel modules representing not only an enhanced form of generalized reinforcement learning but also action bias and hysteresis. We found evidence for substantial differences in bias and hysteresis across participants-even comparable in magnitude to the individual differences in learning. Individuals who did not learn well revealed the greatest biases, but those who did learn accurately were also significantly biased. The direction of hysteresis varied among individuals as repetition or, more commonly, alternation biases persisting from multiple previous actions. Considering that these actions were button presses with trivial motor demands, the idiosyncratic forces biasing sequences of action choices were robust enough to suggest ubiquity across individuals and across tasks requiring various actions. In light of how bias and hysteresis function as a heuristic for efficient control that adapts to uncertainty or low motivation by minimizing the cost of effort, these phenomena broaden the consilient theory of a mixture of experts to encompass a mixture of expert and nonexpert controllers of behavior.

Social cognition in hyperkinetic movement disorders: a systematic review

Numerous lines of research indicate that our social brain involves a network of cortical and subcortical brain regions that are responsible for sensing and controlling body movements. However, it remains unclear whether movement disorders have a systematic impact on social cognition. To address this question, we conducted a systematic review examining the influence of hyperkinetic movement disorders (including Huntington disease, Tourette syndrome, dystonia, and essential tremor) on social cognition. Following the PRISMA guidelines and registering the protocol in the PROSPERO database (CRD42022327459), we analyzed 50 published studies focusing on theory of mind (ToM), social perception, and empathy. The results from these studies provide evidence of impairments in ToM and social perception in all hyperkinetic movement disorders, particularly during the recognition of negative emotions. Additionally, individuals with Huntington's Disease and Tourette syndrome exhibit empathy disorders. These findings support the functional role of subcortical structures (such as the basal ganglia and cerebellum), which are primarily responsible for movement disorders, in deficits related to social cognition.

An active inference model of hierarchical action understanding, learning and imitation

We advance a novel active inference model of the cognitive processing that underlies the acquisition of a hierarchical action repertoire and its use for observation, understanding and imitation. We illustrate the model in four simulations of a tennis learner who observes a teacher performing tennis shots, forms hierarchical representations of the observed actions, and imitates them. Our simulations show that the agent's oculomotor activity implements an active information sampling strategy that permits inferring the kinematic aspects of the observed movement, which lie at the lowest level of the action hierarchy. In turn, this low-level kinematic inference supports higher-level inferences about deeper aspects of the observed actions: proximal goals and intentions. Finally, the inferred action representations can steer imitative responses, but interfere with the execution of different actions. Our simulations show that hierarchical active inference provides a unified account of action observation, understanding, learning and imitation and helps explain the neurobiological underpinnings of visuomotor cognition, including the multiple routes for action understanding in the dorsal and ventral streams and mirror mechanisms.

Cognitive Science Progresses Toward Interactive Frameworks

Despite its many twists and turns, the arc of cognitive science generally bends toward progress, thanks to its interdisciplinary nature. By glancing at the last few decades of experimental and computational advances, it can be argued that-far from failing to converge on a shared set of conceptual assumptions-the field is indeed making steady consensual progress toward what can broadly be referred to as interactive frameworks. This inclination is apparent in the subfields of psycholinguistics, visual perception, embodied cognition, extended cognition, neural networks, dynamical systems theory, and more. This pictorial essay briefly documents this steady progress both from a bird's eye view and from the trenches. The conclusion is one of optimism that cognitive science is getting there, albeit slowly and arduously, like any good science should.

Cross-modal associations between paintings and sounds: Effects of embodiment

The present study investigated cross-modal associations between a series of paintings and sounds. We studied the effects of sound congruency (congruent vs. non-congruent sounds) and embodiment (embodied vs. synthetic sounds) on the evaluation of abstract and figurative paintings. Participants evaluated figurative and abstract paintings paired with congruent and non-congruent embodied and synthetic sounds. They also evaluated the perceived meaningfulness of the paintings, aesthetic value and immersive experience of the paintings. Embodied sounds (sounds associated with bodily sensations, bodily movements and touch) were more strongly associated with figurative paintings, while synthetic sounds (non-embodied sounds) were more strongly associated with abstract paintings. Sound congruency increased the perceived meaningfulness, immersive experience and aesthetic value of paintings. Sound embodiment increased immersive experience of paintings.

An enactivist-inspired mathematical model of cognition

In this paper we start from the philosophical position in cognitive science known as enactivism. We formulate five basic enactivist tenets that we have carefully identified in the relevant literature as the main underlying principles of that philosophy. We then develop a mathematical framework to talk about cognitive systems (both artificial and natural) which complies with these enactivist tenets. In particular we pay attention that our mathematical modeling does not attribute contentful symbolic representations to the agents, and that the agent's nervous system or brain, body and environment are modeled in a way that makes them an inseparable part of a greater totality. The long-term purpose for which this article sets the stage is to create a mathematical foundation for cognition which is in line with enactivism. We see two main benefits of doing so: (1) It enables enactivist ideas to be more accessible for computer scientists, AI researchers, roboticists, cognitive scientists, and psychologists, and (2) it gives the philosophers a mathematical tool which can be used to clarify their notions and help with their debates. Our main notion is that of a sensorimotor system which is a special case of a well studied notion of a transition system. We also consider related notions such as labeled transition systems and deterministic automata. We analyze a notion called sufficiency and show that it is a very good candidate for a foundational notion in the “mathematics of cognition from an enactivist perspective.” We demonstrate its importance by proving a uniqueness theorem about the minimal sufficient refinements (which correspond in some sense to an optimal attunement of an organism to its environment) and by showing that sufficiency corresponds to known notions such as sufficient history information spaces. In the end, we tie it all back to the enactivist tenets.

Grounding Context in Embodied Cognitive Robotics

Biological agents are context-dependent systems that exhibit behavioral flexibility. The internal and external information agents process, their actions, and emotions are all grounded in the context within which they are situated. However, in the field of cognitive robotics, the concept of context is far from being clear with most studies making little to no reference to it. The aim of this paper is to provide an interpretation of the notion of context and its core elements based on different studies in natural agents, and how these core contextual elements have been modeled in cognitive robotics, to introduce a new hypothesis about the interactions between these contextual elements. Here, global context is categorized as agent-related, environmental, and task-related context. The interaction of their core elements, allows agents to first select self-relevant tasks depending on their current needs, or for learning and mastering their environment through exploration. Second, to perform a task and continuously monitor its performance. Third, to abandon a task in case its execution is not going as expected. Here, the monitoring of prediction error, the difference between sensorimotor predictions and incoming sensory information, is at the core of behavioral flexibility during situated action cycles. Additionally, monitoring prediction error dynamics and its comparison with the expected reduction rate should indicate the agent its overall performance on executing the task. Sensitivity to performance evokes emotions that function as the driving element for autonomous behavior which, at the same time, depends on the processing of the interacting core elements. Taking all these into account, an interactionist model of contexts and their core elements is proposed. The model is embodied, affective, and situated, by means of the processing of the agent-related and environmental core contextual elements. Additionally, it is grounded in the processing of the task-related context and the associated situated action cycles during task execution. Finally, the model proposed here aims to guide how artificial agents should process the core contextual elements of the agent-related and environmental context to give rise to the task-related context, allowing agents to autonomously select a task, its planning, execution, and monitoring for behavioral flexibility.

Self-Concern Across Scales: A Biologically Inspired Direction for Embodied Artificial Intelligence

Intelligence in current AI research is measured according to designer-assigned tasks that lack any relevance for an agent itself. As such, tasks and their evaluation reveal a lot more about our intelligence than the possible intelligence of agents that we design and evaluate. As a possible first step in remedying this, this article introduces the notion of “self-concern,” a property of a complex system that describes its tendency to bring about states that are compatible with its continued self-maintenance. Self-concern, as argued, is the foundation of the kind of basic intelligence found across all biological systems, because it reflects any such system's existential task of continued viability. This article aims to cautiously progress a few steps closer to a better understanding of some necessary organisational conditions that are central to self-concern in biological systems. By emulating these conditions in embodied AI, perhaps something like genuine self-concern can be implemented in machines, bringing AI one step closer to its original goal of emulating human-like intelligence.

Grounding (fairly) complex numerical knowledge: an educational example

In this article, we contextualize and discuss an on-line contribution to this special issue in which a video-recorded lecture demonstrates the teaching of an abstract mathematical concept, namely regression to the mean. We first motivate the pertinence of this example from the perspective of embodied cognition. Then, we identify mechanisms of teaching that reflect embodied cognitive practices, such as the concreteness fading approach. Rather than a comprehensive review of multiple extensive literatures, this article provides the interested reader with several sources or entries into those literatures.

Osteopathy and Mental Health: An Embodied, Predictive, and Interoceptive Framework

Globally, mental and musculoskeletal disorders present with high prevalence, disease burden, and comorbidity. In order to improve the quality of care for patients with persistent physical and comorbid mental health conditions, person-centered care approaches addressing psychosocial factors are currently advocated. Central to successful person-centered care is a multidisciplinary collaboration between mental health and musculoskeletal specialists underpinned by a robust therapeutic alliance. Such a collaborative approach might be found in osteopathy, which is typically utilized to treat patients with musculoskeletal disorders but may arguably also benefit mental health outcomes. However, research and practice exploring the reputed effect of osteopathy on patients with mental health problems lack a robust framework. In this hypothesis and theory article, we build upon research from embodied cognition, predictive coding, interoception, and osteopathy to propose an embodied, predictive and interoceptive framework that underpins osteopathic person-centered care for individuals with persistent physical and comorbid mental health problems. Based on the premise that, for example, chronic pain and comorbid depression are underlined by overly precise predictions or imprecise sensory information, we hypothesize that osteopathic treatment may generate strong interoceptive prediction errors that update the generative model underpinning the experience of pain and depression. Thus, physical and mental symptoms may be reduced through active and perceptual inference. We discuss how these theoretical perspectives can inform future research into osteopathy and mental health to reduce the burden of comorbid psychological factors in patients with persistent physical symptoms and support person-centered multidisciplinary care in mental health.

Distinguishing Self, Other, and Autonomy From Visual Feedback: A Combined Correlation and Acceleration Transfer Analysis

In cognitive science, Theory of Mind (ToM) is the mental faculty of assessing intentions and beliefs of others and requires, in part, to distinguish incoming sensorimotor (SM) signals and, accordingly, attribute these to either the self-model, the model of the other, or one pertaining to the external world, including inanimate objects. To gain an understanding of this mechanism, we perform a computational analysis of SM interactions in a dual-arm robotic setup. Our main contribution is that, under the common fate principle, a correlation analysis of the velocities of visual pivots is shown to be sufficient to characterize "the self" (including proximo-distal arm-joint dependencies) and to assess motor to sensory influences, and "the other" by computing clusters in the correlation dependency graph. A correlational analysis, however, is not sufficient to assess the non-symmetric/directed dependencies required to infer autonomy, the ability of entities to move by themselves. We subsequently validate 3 measures that can potentially quantify a metric for autonomy: Granger causality (GC), transfer entropy (TE), as well as a novel "Acceleration Transfer" (AT) measure, which is an instantaneous measure that computes the estimated instantaneous transfer of acceleration between visual features, from which one can compute a directed SM graph. Subsequently, autonomy is characterized by the sink nodes in this directed graph. This study results show that although TE can capture the directional dependencies, a rectified subtraction operation denoted, in this study, as AT is both sufficient and computationally cheaper.

Exocentric coding of the mapping between valence and regions of space: Implications for embodied cognition

Converging evidence has established that positive concepts presented on a computer screen are associated with upper regions of space, and negative concepts with a lower region of space. One explanation for this is that understanding positive or negative concepts requires the re-experiencing of direction, whereby “happy is up” and “sad is down.” However, it is unclear how the regions of space are encoded in these paradigms, space can be encoded in relation to oneself (egocentrically) or in object centred coordinates that are independent of oneself (exocentrically). The current study compares exocentric and egocentric coding of space, using a variation of the Meier and Robinson (2004) paradigm. Participants were asked to evaluate valenced concepts in either the upper or lower half of the screen. Spatial primes were used such that the concepts were preceded by either an upwards or a downwards eye movement. Exocentric coding of space in this paradigm was the computer screen, whilst egocentric coding was the eye movement used to access the top or bottom of the screen. It was proposed that egocentric coding of space, being coded in the body, provides evidence of a stronger relationship between the original bodily state of ‘up’ or ‘down’ and subsequent simulation. However, significant results supported an exocentric coding of space, with faster responses to positive concepts in the upper half of the screen, and to negative concepts in the lower half, irrespective of the direction of the eye movement preceding it. The implications of this for embodied cognition are discussed.

Somatosensory cortical facilitation during step preparation restored by an improved body representation in obese patients

BACKGROUND

The anticipatory postural adjustments (APA) associated with step initiation are impaired in obese patients (e.g. longer duration, greater lateral center of pressure excursion). This could arise from the known altered internal representation of the body in obese individuals as this representation is crucial for enhancing the processing of foot cutaneous inputs prior to step initiation and for setting the APA.

RESEARCH QUESTION

The purpose of the study was to examine if the processing of foot cutaneous inputs and the preparation of the APA when planning a step are impaired in obese patients due to their damaged body internal representation (BIR). We also investigated whether these sensorimotor processes will be restored after a 15-day intervention program composed of motor and cognitive activities engaging the BIR without aiming weight loss.

METHODS

We compared, prior to (D1) and after (D15) the program, the amplitude of the cortical response evoked by foot cutaneous stimulation (SEP) occurring either during quiet standing or during the planning of a step in 18 obese patients (mean body mass index, BMI: 35). The APA were analyzed by measuring the amplitude and latency of the lateral force exerted on the ground.

RESULTS AND SIGNIFICANCE

The SEP amplitude was not significantly different between the standing and stepping tasks at D1, but increased in the stepping task at D15. This enhanced sensory processing was associated with an increased activation of the posterior parietal cortex, suggesting a stronger involvement of the body representation during the planning of the stepping movement after the program. These cortical changes could have contributed to the changes in the temporal dimension of the APA observed at D15. These results suggest that programs targeting different dimensions of the BIR could be beneficial in improving the dynamic balance in obesity.

On the origin of mental representations

The symbol grounding problem raises its head in the fields of the philosophy of AI, philosophy of psychology and philosophy of cognitive sciences. The solution to the symbol grounding problem must account for the genesis of mental representations in the world. It has to offer a strategy for grounding mental representations in the objective domain. Orthodox representationalist theories do not provide a satisfactory reply to the symbol grounding problem. On the other hand, there are embodied-enactivist approaches that dissolve the problem but only at the cost of representations and internal phenomenal states. The code model of biosemiotics provides a biologically viable (i.e., mechanistic) venue for developing a new solution to the problem. For the same reason, it could reconcile representationalism to the embodied approach.

Number concepts: abstract and embodied

Numerical knowledge, including number concepts and arithmetic procedures, seems to be a clear-cut case for abstract symbol manipulation. Yet, evidence from perceptual and motor behaviour reveals that natural number knowledge and simple arithmetic also remain closely associated with modal experiences. Following a review of behavioural, animal and neuroscience studies of number processing, we propose a revised understanding of psychological number concepts as grounded in physical constraints, embodied in experience and situated through task-specific intentions. The idea that number concepts occupy a range of positions on the continuum between abstract and modal conceptual knowledge also accounts for systematic heuristics and biases in mental arithmetic, thus inviting psycho-logical approaches to the study of the mathematical mind.This article is part of the theme issue 'Varieties of abstract concepts: development, use and representation in the brain'.

Mental Number Representations in 2D Space

There is evidence both for mental number representations along a horizontal mental number line with larger numbers to the right of smaller numbers (for Western cultures) and a physically grounded, vertical representation where "more is up." Few studies have compared effects in the horizontal and vertical dimension and none so far have combined both dimensions within a single paradigm where numerical magnitude was task-irrelevant and none of the dimensions was primed by a response dimension. We now investigated number representations over both dimensions, building on findings that mental representations of numbers and space co-activate each other. In a Go/No-go experiment, participants were auditorily primed with a relatively small or large number and then visually presented with quasi-randomly distributed distractor symbols and one Arabic target number (in Go trials only). Participants pressed a central button whenever they detected the target number and elsewise refrained from responding. Responses were not more efficient when small numbers were presented to the left and large numbers to the right. However, results indicated that large numbers were associated with upper space more strongly than small numbers. This suggests that in two-dimensional space when no response dimension is given, numbers are conceptually associated with vertical, but not horizontal space.

Spiking Neurons Integrating Visual Stimuli Orientation and Direction Selectivity in a Robotic Context

Visual motion detection is essential for the survival of many species. The phenomenon includes several spatial properties, not fully understood at the level of a neural circuit. This paper proposes a computational model of a visual motion detector that integrates direction and orientation selectivity features. A recent experiment in the Drosophila model highlights that stimulus orientation influences the neural response of direction cells. However, this interaction and the significance at the behavioral level are currently unknown. As such, another objective of this article is to study the effect of merging these two visual processes when contextualized in a neuro-robotic model and an operant conditioning procedure. In this work, the learning task was solved using an artificial spiking neural network, acting as the brain controller for virtual and physical robots, showing a behavior modulation from the integration of both visual processes.

From Wide Cognition to Mechanisms: A Silent Revolution

In this paper, we argue that several recent ‘wide’ perspectives on cognition (embodied, embedded, extended, enactive, and distributed) are only partially relevant to the study of cognition. While these wide accounts override traditional methodological individualism, the study of cognition has already progressed beyond these proposed perspectives toward building integrated explanations of the mechanisms involved, including not only internal submechanisms but also interactions with others, groups, cognitive artifacts, and their environment. Wide perspectives are essentially research heuristics for building mechanistic explanations. The claim is substantiated with reference to recent developments in the study of “mindreading” and debates on emotions. We argue that the current practice in cognitive (neuro)science has undergone, in effect, a silent mechanistic revolution, and has turned from initial binary oppositions and abstract proposals toward the integration of wide perspectives with the rest of the cognitive (neuro)sciences.

Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner

Optimal decision-making is based on integrating information from several dimensions of decisional space (e.g., reward expectation, cost estimation, effort exertion). Despite considerable empirical and theoretical efforts, the computational and neural bases of such multidimensional integration have remained largely elusive. Here we propose that the current theoretical stalemate may be broken by considering the computational properties of a cortical-subcortical circuit involving the dorsal anterior cingulate cortex (dACC) and the brainstem neuromodulatory nuclei: ventral tegmental area (VTA) and locus coeruleus (LC). From this perspective, the dACC optimizes decisions about stimuli and actions, and using the same computational machinery, it also modulates cortical functions (meta-learning), via neuromodulatory control (VTA and LC). We implemented this theory in a novel neuro-computational model–the Reinforcement Meta Learner (RML). We outline how the RML captures critical empirical findings from an unprecedented range of theoretical domains, and parsimoniously integrates various previous proposals on dACC functioning.

A major challenge for all organisms is selecting optimal behaviour to obtain resources while minimizing energetic and other expenses. Evolution provided mammals with exceptional decision-making capabilities to face this challenge. Even though neuroscientists have identified a heterogeneous and distributed set of brain structures to be involved, a comprehensive theory about the biological and computational basis of such decision-making is yet to be formulated. We propose that the interaction between the medial prefrontal cortex (a part of the frontal lobes) and the subcortical nuclei releasing catecholaminergic neuromodulators will be key to such a theory. We argue that this interaction allows both the selection of optimal behaviour and, more importantly, the optimal modulation of the very brain circuits that drive such behavioral selection (i.e., meta-learning). We implemented this theory in a novel neuro-computational model, the Reinforcement Meta-Learner (RML). By means of computer simulations we showed that the RML provides a biological and computational account for a set of neuroscientific data with unprecedented scope, thereby suggesting a critical mechanism of decision-making in the mammalian brain.

The influence of communication mode on written language processing and beyond

Empirical evidence suggests a broad impact of communication mode on cognition at large, beyond language processing. Using a sign language since infancy might shape the representation of words and other linguistic stimuli - for example, incorporating in it the movements and signs used to express them. Once integrated into linguistic representations, this visuo-motor content can affect deaf signers' linguistic and cognitive processing.

Increased heart rate after exercise facilitates the processing of fearful but not disgusted faces

Embodied theories of emotion assume that emotional processing is grounded in bodily and affective processes. Accordingly, the perception of an emotion re-enacts congruent sensory and affective states; and conversely, bodily states congruent with a specific emotion facilitate emotional processing. This study tests whether the ability to process facial expressions (faces having a neutral expression, expressing fear, or disgust) can be influenced by making the participants’ body state congruent with the expressed emotion (e.g., high heart rate in the case of faces expressing fear). We designed a task requiring participants to categorize pictures of male and female faces that either had a neutral expression (neutral), or expressed emotions whose linkage with high heart rate is strong (fear) or significantly weaker or absent (disgust). Critically, participants were tested in two conditions: with experimentally induced high heart rate (Exercise) and with normal heart rate (Normal). Participants processed fearful faces (but not disgusted or neutral faces) faster when they were in the Exercise condition than in the Normal condition. These results support the idea that an emotionally congruent body state facilitates the automatic processing of emotionally-charged stimuli and this effect is emotion-specific rather than due to generic factors such as arousal.

Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex

Despite increasing evidence suggesting the cerebellum works in concert with the cortex and basal ganglia, the nature of the reciprocal interactions between these three brain regions remains unclear. This consensus paper gathers diverse recent views on a variety of important roles played by the cerebellum within the cerebello-basal ganglia-thalamo-cortical system across a range of motor and cognitive functions. The paper includes theoretical and empirical contributions, which cover the following topics: recent evidence supporting the dynamical interplay between cerebellum, basal ganglia, and cortical areas in humans and other animals; theoretical neuroscience perspectives and empirical evidence on the reciprocal influences between cerebellum, basal ganglia, and cortex in learning and control processes; and data suggesting possible roles of the cerebellum in basal ganglia movement disorders. Although starting from different backgrounds and dealing with different topics, all the contributors agree that viewing the cerebellum, basal ganglia, and cortex as an integrated system enables us to understand the function of these areas in radically different ways. In addition, there is unanimous consensus between the authors that future experimental and computational work is needed to understand the function of cerebellar-basal ganglia circuitry in both motor and non-motor functions. The paper reports the most advanced perspectives on the role of the cerebellum within the cerebello-basal ganglia-thalamo-cortical system and illustrates other elements of consensus as well as disagreements and open questions in the field.

Action perception as hypothesis testing

We present a novel computational model that describes action perception as an active inferential process that combines motor prediction (the reuse of our own motor system to predict perceived movements) and hypothesis testing (the use of eye movements to disambiguate amongst hypotheses). The system uses a generative model of how (arm and hand) actions are performed to generate hypothesis-specific visual predictions, and directs saccades to the most informative places of the visual scene to test these predictions - and underlying hypotheses. We test the model using eye movement data from a human action observation study. In both the human study and our model, saccades are proactive whenever context affords accurate action prediction; but uncertainty induces a more reactive gaze strategy, via tracking the observed movements. Our model offers a novel perspective on action observation that highlights its active nature based on prediction dynamics and hypothesis testing.

Toward a Dynamic Probabilistic Model for Vestibular Cognition

We suggest that research in vestibular cognition will benefit from the theoretical framework of probabilistic models. This will aid in developing an understanding of how interactions between high-level cognition and low-level sensory processing might occur. Many such interactions have been shown experimentally; however, to date, no attempt has been made to systematically explore vestibular cognition by using computational modeling. It is widely assumed that mental imagery and perception share at least in part neural circuitry, and it has been proposed that mental simulation is closely connected to the brain’s ability to make predictions. We claim that this connection has been disregarded in the vestibular domain, and we suggest ways in which future research may take this into consideration.

What is orgasm? A model of sexual trance and climax via rhythmic entrainment

Orgasm is one of the most intense pleasures attainable to an organism, yet its underlying mechanisms remain poorly understood. On the basis of existing literatures, this article introduces a novel mechanistic model of sexual stimulation and orgasm. In doing so, it characterizes the neurophenomenology of sexual trance and climax, describes parallels in dynamics between orgasms and seizures, speculates on possible evolutionary origins of sex differences in orgasmic responding, and proposes avenues for future experimentation. Here, a model is introduced wherein sexual stimulation induces entrainment of coupling mechanical and neuronal oscillatory systems, thus creating synchronized functional networks within which multiple positive feedback processes intersect synergistically to contribute to sexual experience. These processes generate states of deepening sensory absorption and trance, potentially culminating in climax if critical thresholds are surpassed. The centrality of rhythmic stimulation (and its modulation by salience) for surpassing these thresholds suggests ways in which differential orgasmic responding between individuals-or with different partners-may serve as a mechanism for ensuring adaptive mate choice. Because the production of rhythmic stimulation combines honest indicators of fitness with cues relating to potential for investment, differential orgasmic response may serve to influence the probability of continued sexual encounters with specific mates.

The poverty of embodied cognition

In recent years, there has been rapidly growing interest in embodied cognition, a multifaceted theoretical proposition that (1) cognitive processes are influenced by the body, (2) cognition exists in the service of action, (3) cognition is situated in the environment, and (4) cognition may occur without internal representations. Many proponents view embodied cognition as the next great paradigm shift for cognitive science. In this article, we critically examine the core ideas from embodied cognition, taking a "thought exercise" approach. We first note that the basic principles from embodiment theory are either unacceptably vague (e.g., the premise that perception is influenced by the body) or they offer nothing new (e.g., cognition evolved to optimize survival, emotions affect cognition, perception-action couplings are important). We next suggest that, for the vast majority of classic findings in cognitive science, embodied cognition offers no scientifically valuable insight. In most cases, the theory has no logical connections to the phenomena, other than some trivially true ideas. Beyond classic laboratory findings, embodiment theory is also unable to adequately address the basic experiences of cognitive life.

Resonant Dynamics of Grounded Cognition: Explanation of Behavioral and Neuroimaging Data Using the ART Neural Network

Research on grounded cognition suggests that the processing of a word or concept reactivates the perceptual representations that are associated with the referent object. The objective of this work is to demonstrate how behavioral and functional neuroimaging data on grounded cognition can be understood as different manifestations of the same cortical circuit designed to achieve stable category learning, as proposed by the adaptive resonance theory (ART). We showed that the ART neural network provides a mechanistic explanation of why reaction times in behavioral studies depend on the expectation or attentional priming created by the word meaning (Richter and Zwaan, 2009). A mismatch between top-down expectation and bottom-up sensory data activates an orienting subsystem that slows execution of the current task. Furthermore, we simulated the data from functional neuroimaging studies of color knowledge retrieval that showed anterior shift (Chao and Martin, 1999; Thompson-Schill, 2003) and an overlap effect (Simmons et al., 2007; Hsu et al., 2011) in the left fusiform gyrus. We explain the anterior effect as a result of the partial activation of different components of the same ART circuit in the condition of passive viewing. Conversely, a demanding perceptual task requires activation of the whole ART circuit. This condition is reflected in the fMRI image as an overlap between cortical activation during perceptual and conceptual processing. We conclude that the ART neural network is able to explain how the brain grounds symbols in perception via perceptual simulation.

Embodied choice: how action influences perceptual decision making

Embodied Choice considers action performance as a proper part of the decision making process rather than merely as a means to report the decision. The central statement of embodied choice is the existence of bidirectional influences between action and decisions. This implies that for a decision expressed by an action, the action dynamics and its constraints (e.g. current trajectory and kinematics) influence the decision making process. Here we use a perceptual decision making task to compare three types of model: a serial decision-then-action model, a parallel decision-and-action model, and an embodied choice model where the action feeds back into the decision making. The embodied model incorporates two key mechanisms that together are lacking in the other models: action preparation and commitment. First, action preparation strategies alleviate delays in enacting a choice but also modify decision termination. Second, action dynamics change the prospects and create a commitment effect to the initially preferred choice. Our results show that these two mechanisms make embodied choice models better suited to combine decision and action appropriately to achieve suitably fast and accurate responses, as usually required in ecologically valid situations. Moreover, embodied choice models with these mechanisms give a better account of trajectory tracking experiments during decision making. In conclusion, the embodied choice framework offers a combined theory of decision and action that gives a clear case that embodied phenomena such as the dynamics of actions can have a causal influence on central cognition.

The modern view of how we make perceptual decisions is of a process of accumulating sensory evidence until reaching a threshold level of certainty. However, this evidence accumulation model neglects the contribution of action and motor processes to the choice that is made. Recent novel studies that track the changing dynamics of actions during perceptual decisions are increasingly revealing the contribution of the actions we make to our perceptual choices. Thus, the action dynamics of our bodies causally influences our central cognition, which is a core assumption of embodied theories of mind. This paper presents an explanation of how actions, encompassing behavioral strategies such as preparation and commitment, can bias decision making processes in ways that optimize the ecological choices of animals behaving in natural environments. It thus combines two disconnected research streams, decision-making and action control in a manner consistent with theoretical and psychological arguments for embodied cognition.

Prospects for direct social perception: a multi-theoretical integration to further the science of social cognition

In this paper we suggest that differing approaches to the science of social cognition mirror the arguments between radical embodied and traditional approaches to cognition. We contrast the use in social cognition of theoretical inference and mental simulation mechanisms with approaches emphasizing a direct perception of others’ mental states. We build from a recent integrative framework unifying these divergent perspectives through the use of dual-process theory and supporting social neuroscience research. Our elaboration considers two complementary notions of direct perception: one primarily stemming from ecological psychology and the other from enactive cognition theory. We use this as the foundation from which to offer an account of the informational basis for social information and assert a set of research propositions to further the science of social cognition. In doing so, we point out how perception of the minds of others can be supported in some cases by lawful information, supporting direct perception of social affordances and perhaps, mental states, and in other cases by cues that support indirect perceptual inference. Our goal is to extend accounts of social cognition by integrating advances across disciplines to provide a multi-level and multi-theoretic description that can advance this field and offer a means through which to reconcile radical embodied and traditional approaches to cognitive neuroscience.

The why, what, where, when and how of goal-directed choice: neuronal and computational principles

The central problems that goal-directed animals must solve are: 'What do I need and Why, Where and When can this be obtained, and How do I get it?' or the H4W problem. Here, we elucidate the principles underlying the neuronal solutions to H4W using a combination of neurobiological and neurorobotic approaches. First, we analyse H4W from a system-level perspective by mapping its objectives onto the Distributed Adaptive Control embodied cognitive architecture which sees the generation of adaptive action in the real world as the primary task of the brain rather than optimally solving abstract problems. We next map this functional decomposition to the architecture of the rodent brain to test its consistency. Following this approach, we propose that the mammalian brain solves the H4W problem on the basis of multiple kinds of outcome predictions, integrating central representations of needs and drives (e.g. hypothalamus), valence (e.g. amygdala), world, self and task state spaces (e.g. neocortex, hippocampus and prefrontal cortex, respectively) combined with multi-modal selection (e.g. basal ganglia). In our analysis, goal-directed behaviour results from a well-structured architecture in which goals are bootstrapped on the basis of predefined needs, valence and multiple learning, memory and planning mechanisms rather than being generated by a singular computation.

How do you hold your mouse? Tracking the compatibility effect between hand posture and stimulus size

In keeping with the idea that observing objects activates possible motor responses, several experiments revealed compatibility effects between the hand postures used to report a choice and some characteristics of the stimuli. The real-time dynamics of such compatibility effects are currently unknown. We tracked the time course of a categorization experiment requiring subjects to categorize as natural or artifact figures of big and small objects. Participants reported their choice using either a big mouse (requiring a power grip: a hand posture compatible with the grasping of big objects) or a small mouse (requiring a precision grip: a hand posture compatible with the grasping of small objects). We found a compatibility effect between the grip required by the mouse and the grip elicited by objects, even if it was irrelevant to the task. In a following experiment with the same paradigm, lexical stimuli failed to reproduce the same effect. Nevertheless, a compatibility effect mediated by the target-word category (artificial vs. natural) was observed. We discuss the results in the context of affordance effects literature and grounded theories of cognition.

Everyday robotic action: lessons from human action control

Robots are increasingly capable of performing everyday human activities such as cooking, cleaning, and doing the laundry. This requires the real-time planning and execution of complex, temporally extended sequential actions under high degrees of uncertainty, which provides many challenges to traditional approaches to robot action control. We argue that important lessons in this respect can be learned from research on human action control. We provide a brief overview of available psychological insights into this issue and focus on four principles that we think could be particularly beneficial for robot control: the integration of symbolic and subsymbolic planning of action sequences, the integration of feedforward and feedback control, the clustering of complex actions into subcomponents, and the contextualization of action-control structures through goal representations.

Consensus paper: the cerebellum's role in movement and cognition

While the cerebellum's role in motor function is well recognized, the nature of its concurrent role in cognitive function remains considerably less clear. The current consensus paper gathers diverse views on a variety of important roles played by the cerebellum across a range of cognitive and emotional functions. This paper considers the cerebellum in relation to neurocognitive development, language function, working memory, executive function, and the development of cerebellar internal control models and reflects upon some of the ways in which better understanding the cerebellum's status as a "supervised learning machine" can enrich our ability to understand human function and adaptation. As all contributors agree that the cerebellum plays a role in cognition, there is also an agreement that this conclusion remains highly inferential. Many conclusions about the role of the cerebellum in cognition originate from applying known information about cerebellar contributions to the coordination and quality of movement. These inferences are based on the uniformity of the cerebellum's compositional infrastructure and its apparent modular organization. There is considerable support for this view, based upon observations of patients with pathology within the cerebellum.