Embodied learning of a generative neural model for biological motion perception and inference

Frontiers in Computational Neuroscience

Volumn 9, Issue JULY, 2015, Pages

  Schrodt, Fabian ^a   Layher, Georg ^b   Neumann, Heiko ^b   Butz, Martin V ^a  

^a UNIVERSITY OF TÜBINGEN   (Germany)

^b UNIVERSITY OF ULM   (Germany)

Author keywords

Active inference; Biological motion; Correspondence problem; Embodiment; Mirror neurons; Neural networks; Perspective taking; Predictive coding

Indexed keywords

ENCODING (SYMBOLS); MIRRORS; NEURONS; PARTIAL DISCHARGES;

ACTIVE INFERENCE; BIOLOGICAL MOTION; CORRESPONDENCE PROBLEMS; EMBODIMENT; MIRROR NEURONS; PERSPECTIVE TAKING; PREDICTIVE CODING;

NEURAL NETWORKS;

ACTION POTENTIAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BASKETBALL; FEEDBACK SYSTEM; INFORMATION PROCESSING; MIRROR NEURON; MOLECULAR DYNAMICS; MORPHOLOGY; MOTOR SYSTEM; MOVEMENT PERCEPTION; NEUROMODULATION; PROBABILITY; PROPRIOCEPTION; RUNNING; SPATIAL LEARNING; SPATIAL ORIENTATION; SYNAPSE; SYNAPTIC TRANSMISSION; VISUAL SYSTEM; WALKING;

EID: 84936951399     PISSN: 16625188     EISSN: 16625188     Source Type: Journal    
DOI: 10.3389/fncom.2015.00079     Document Type: Article

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