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Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent.
Moioli, Renan C; Vargas, Patricia A; Husbands, Phil.
Afiliação
  • Moioli RC; Department of Informatics, Centre for Computational Neuroscience and Robotics (CCNR), University of Sussex, Falmer, Brighton, UK. r.moioli@sussex.ac.uk
Biol Cybern ; 106(6-7): 407-27, 2012 Sep.
Article em En | MEDLINE | ID: mdl-22810898
ABSTRACT
Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain-body- environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Robótica / Cognição / Modelos Neurológicos Limite: Humans Idioma: En Revista: Biol Cybern Ano de publicação: 2012 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Robótica / Cognição / Modelos Neurológicos Limite: Humans Idioma: En Revista: Biol Cybern Ano de publicação: 2012 Tipo de documento: Article