Theories and computational models of affordance and mirror systems : An integrative review

• 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.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Keyword

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

Technology

Teknik

Interaction Lab (ILAB)

Interaction Lab (ILAB)

Publication and Content Type

ref (subject category)

for (subject category)