Theories and computational models of affordance and mirror systems: An integrative reviewShow others and affiliations
2013 (English)In: Neuroscience and Biobehavioral Reviews, ISSN 0149-7634, E-ISSN 1873-7528, Vol. 37, no 3, p. 491-521Article, review/survey (Refereed) Published
Abstract [en]
Neuroscientific and psychological data suggest a close link between affordance and mirror systems in the brain. However, we still lack a full understanding of both the individual systems and their interactions. Here, we propose that the architecture and functioning of the two systems is best understood in terms of two challenges faced by complex organisms, namely: (a) the need to select among multiple affordances and possible actions dependent on context and high-level goals and (b) the exploitation of the advantages deriving from a hierarchical organisation of behaviour based on actions and action-goals. We first review and analyse the psychological and neuroscientific literature on the mechanisms and processes organisms use to deal with these challenges. We then analyse existing computational models thereof. Finally we present the design of a computational framework that integrates the reviewed knowledge. The framework can be used both as a theoretical guidance to interpret empirical data and design new experiments, and to design computational models addressing specific problems debated in the literature. © 2013 Elsevier Ltd.
Place, publisher, year, edition, pages
Elsevier, 2013. Vol. 37, no 3, p. 491-521
Keywords [en]
Affordance processing, Canonical neurons, Computational modelling, Embodied cognition, Integration, Mirror system, Neurophysiology, Neuroscience, Psychology, Bayes theorem, brain function, control system, functional magnetic resonance imaging, human, mathematical model, mirror neuron, motivation, motoneuron, motor cortex, neuroimaging, neuromodulation, neuropsychology, nonhuman, parietal cortex, prefrontal cortex, premotor cortex, priority journal, review, scientific literature, sensorimotor cortex, social environment, social interaction
National Category
Computer and Information Sciences
Research subject
Technology; Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-8080DOI: 10.1016/j.neubiorev.2013.01.012ISI: 000317548100020PubMedID: 23333761Scopus ID: 2-s2.0-84874511220OAI: oai:DiVA.org:his-8080DiVA, id: diva2:615860
Funder
EU, FP7, Seventh Framework Programme
Note
CC BY-NC-ND 3.0
This research was supported by the European Commission 7th Framework Programme (FP7/2007-2013), “Challenge 2 – Cognitive Systems, Interaction, Robotics” projects “ROSSI – Emergence ofcommunication in RObots through Sensorimotor and Social Inter-action”, contract no. FP7-STREP-216125, and “IM-CLeVeR – Intrinsically Motivated Cumulative Learning Versatile Robots”, contract no. FP7-IP-231722. We would like to thank all reviewers for their helpful and constructive comments on earlier versions of this review.
2013-04-122013-04-122023-04-12Bibliographically approved