title: A continuous-time neural model for sequential action.
abstract: Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions.
authors.affiliation: Institute for Psychological Research Leiden University, Leiden, The Netherlands Leiden Institute for Brain and Cognition, 2333 AK Leiden University, Leiden, The Netherlands george.kachergis@gmail.com.
authors.forename: George
authors.initials: G
authors.lastname: Kachergis
authors.affiliation: Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA.
authors.forename: Dean
authors.initials: D
authors.lastname: Wyatte
authors.affiliation: Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA.
authors.forename: Randall C
authors.initials: RC
authors.lastname: O'Reilly
authors.affiliation: Institute for Psychological Research Leiden University, Leiden, The Netherlands Leiden Institute for Brain and Cognition, 2333 AK Leiden University, Leiden, The Netherlands.
authors.forename: Roy
authors.initials: R
authors.lastname: de Kleijn
authors.affiliation: Institute for Psychological Research Leiden University, Leiden, The Netherlands Leiden Institute for Brain and Cognition, 2333 AK Leiden University, Leiden, The Netherlands.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Hommel
mesh_terms: D003657:Decision Making / Q000502:physiology*; D006040:Goals; D006801:Humans; D007858:Learning / Q000502:physiology*; D008959:Models, Neurological; D010465:Perception / Q000502:physiology*
keywords: everyday action; neural model; sequential action control