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      Embodied Cognition is Not What you Think it is

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          Abstract

          The most exciting hypothesis in cognitive science right now is the theory that cognition is embodied. Like all good ideas in cognitive science, however, embodiment immediately came to mean six different things. The most common definitions involve the straight-forward claim that “states of the body modify states of the mind.” However, the implications of embodiment are actually much more radical than this. If cognition can span the brain, body, and the environment, then the “states of mind” of disembodied cognitive science won’t exist to be modified. Cognition will instead be an extended system assembled from a broad array of resources. Taking embodiment seriously therefore requires both new methods and theory. Here we outline four key steps that research programs should follow in order to fully engage with the implications of embodiment. The first step is to conduct a task analysis, which characterizes from a first person perspective the specific task that a perceiving-acting cognitive agent is faced with. The second step is to identify the task-relevant resources the agent has access to in order to solve the task. These resources can span brain, body, and environment. The third step is to identify how the agent can assemble these resources into a system capable of solving the problem at hand. The last step is to test the agent’s performance to confirm that agent is actually using the solution identified in step 3. We explore these steps in more detail with reference to two useful examples (the outfielder problem and the A-not-B error), and introduce how to apply this analysis to the thorny question of language use. Embodied cognition is more than we think it is, and we have the tools we need to realize its full potential.

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          Most cited references54

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          Perceptual symbol systems.

          Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statistics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement recording systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The storage and reactivation of perceptual symbols operates at the level of perceptual components--not at the level of holistic perceptual experiences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a common frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspection (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and abstract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinatorially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a perceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal symbol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.
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            Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex.

            How natural speech is represented in the auditory cortex constitutes a major challenge for cognitive neuroscience. Although many single-unit and neuroimaging studies have yielded valuable insights about the processing of speech and matched complex sounds, the mechanisms underlying the analysis of speech dynamics in human auditory cortex remain largely unknown. Here, we show that the phase pattern of theta band (4-8 Hz) responses recorded from human auditory cortex with magnetoencephalography (MEG) reliably tracks and discriminates spoken sentences and that this discrimination ability is correlated with speech intelligibility. The findings suggest that an approximately 200 ms temporal window (period of theta oscillation) segments the incoming speech signal, resetting and sliding to track speech dynamics. This hypothesized mechanism for cortical speech analysis is based on the stimulus-induced modulation of inherent cortical rhythms and provides further evidence implicating the syllable as a computational primitive for the representation of spoken language.
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              Passive Dynamic Walking

              T McGeer (1990)
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                Author and article information

                Journal
                Front Psychol
                Front Psychol
                Front. Psychology
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                12 February 2013
                2013
                : 4
                : 58
                Affiliations
                [1] 1School of Social, Psychological and Communication Sciences, Leeds Metropolitan University Leeds, UK
                Author notes

                Edited by: Louise Connell, University of Manchester, UK

                Reviewed by: Louise Connell, University of Manchester, UK; Tad Brunye, US Army NSRDEC and Tufts University, USA; Louise Barrett, University of Lethbridge, Canada

                *Correspondence: Andrew D. Wilson, School of Social, Psychological and Communication Sciences, Leeds Metropolitan University, Civic Quarter, Calverley Street, Leeds LS1 3HE, UK. e-mail: a.d.wilson@ 123456leedsmet.ac.uk

                This article was submitted to Frontiers in Cognitive Science, a specialty of Frontiers in Psychology.

                Article
                10.3389/fpsyg.2013.00058
                3569617
                23408669
                8cabd713-298b-4970-9ef1-b09ed035c579
                Copyright © 2013 Wilson and Golonka.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 31 August 2012
                : 26 January 2013
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 87, Pages: 13, Words: 13606
                Categories
                Psychology
                Hypothesis and Theory

                Clinical Psychology & Psychiatry
                embodied cognition,dynamical systems,replacement hypothesis,robotics,outfielder problem,a-not-b error,language

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