The Mechanics of Embodiment: A Dialogue on Embodiment and Computational Modeling

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamouring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensory-motor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialogue between two fictional characters: Ernest, the �experimenter�, and Mary, the �computational modeller�. The dialogue consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modelling

Visuomotor resonance in autism spectrum disorders

When we observe the actions performed by others, our motor system “resonates” along with that of the observed agent. Is a similar visuomotor resonant response observed in autism spectrum disorders (ASD)? Studies investigating action observation in ASD have yielded inconsistent findings. In this perspective article we examine behavioral and neuroscientific evidence in favor of visuomotor resonance in ASD, and consider the possible role of action-perception coupling in social cognition. We distinguish between different aspects of visuomotor resonance and conclude that while some aspects may be preserved in ASD, abnormalities exist in the way individuals with ASD convert visual information from observed actions into a program for motor execution. Such abnormalities, we surmise, may contribute to but also depend on the difficulties that individuals with ASD encounter during social interaction

When do Thick Venture Capital Markets Foster Innovation? An Evolutionary Analysis

In this paper we examine the trade off between different effects of the availability of venture capital on the speed of technological progress in an industry. We consider an evolutionary industry simulation model based on Nelson and Winter (1982) where R&D efforts of an incumbent firm generate technological know-how embodied in key R&D employees, who might use this know-how to found a spinoff of the incumbent. Venture capital is needed to finance a spinoff, and therefore the expected profits from founding a spinoff depend on how easily venture capital can be acquired. Accordingly, thick venture capital markets might have two opposing effects. First, incentives of firms to invest in R&D might be reduced and, second, if spinoff formation results in technological spillovers between the parent firm and the spinoffs, the generation of spinoff firms might positively influence the future efficiency of the incumbent's innovation efforts. We study how this tradeoff influences the effect of venture capital on the innovation expenditures, speed of technological change and the evolution of industry concentration in several scenarios with different industry characteristics.Venture Capital, Technological Progress, R&D Effort, Spinoff, Industry Evolution

Look What I Am Doing: Does Observational Learning Take Place in Evocative Task-Sharing Situations?

Two experiments were conducted to investigate whether physical and observational practice in task-sharing entail comparable implicit motor learning. To this end, the social-transfer-of-learning (SToL) effect was assessed when both participants performed the joint practice task (Experiment 1 \u2013 complete task-sharing), or when one participant observed the other performing half of the practice task (Experiment 2 \u2013 evocative task-sharing). Since the inversion of the spatial relations between responding agent and stimulus position has been shown to prevent SToL, in the present study we assessed it in both complete and evocative task-sharing conditions either when spatial relations were kept constant or changed from the practice to the transfer session. The same pattern of results was found for both complete and evocative task-sharing, thus suggesting that implicit motor learning in evocative task-sharing is equivalent to that obtained in complete task-sharing. We conclude that this motor learning originates from the simulation of the complementary (rather than the imitative) action

Embodied Gesture Processing: Motor-Based Integration of Perception and Action in Social Artificial Agents

A close coupling of perception and action processes is assumed to play an important role in basic capabilities of social interaction, such as guiding attention and observation of others’ behavior, coordinating the form and functions of behavior, or grounding the understanding of others’ behavior in one’s own experiences. In the attempt to endow artificial embodied agents with similar abilities, we present a probabilistic model for the integration of perception and generation of hand-arm gestures via a hierarchy of shared motor representations, allowing for combined bottom-up and top-down processing. Results from human-agent interactions are reported demonstrating the model’s performance in learning, observation, imitation, and generation of gestures

Towards a complete multiple-mechanism account of predictive language processing [Commentary on Pickering & Garrod]

Although we agree with Pickering & Garrod (P&G) that prediction-by-simulation and prediction-by-association are important mechanisms of anticipatory language processing, this commentary suggests that they: (1) overlook other potential mechanisms that might underlie prediction in language processing, (2) overestimate the importance of prediction-by-association in early childhood, and (3) underestimate the complexity and significance of several factors that might mediate prediction during language processing

An integrated theory of language production and comprehension

Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation (such as semantics, syntax, and phonology). We show (a) how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, (b) how they interweave production and comprehension processes, and (c) how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal

Action observation and execution: What is shared?

Performing an action and observing it activate the same internal representations of action. The representations are therefore shared between self and other (shared representations of action, SRA). But what exactly is shared? At what level within the hierarchical structure of the motor system do SRA occur? Understanding the content of SRA is important in order to decide what theoretical work SRA can perform. In this paper, we provide some conceptual clarification by raising three main questions: (i) are SRA semantic or pragmatic representations of action?; (ii) are SRA sensory or motor representations?; (iii) are SRA representations of the action as a global unit or as a set of elementary motor components? After outlining a model of the motor hierarchy, we conclude that the best candidate for SRA is intentions in action, defined as the motor plans of the dynamic sequence of movements. We shed new light on SRA by highlighting the causal efficacy of intentions in action. This in turn explains phenomena such as inhibition of imitation