Modeling the Functional Connectivity in Embodied in Vitro Neuronal Network

We developed a hybrid neuro-robotic bi-directional interface connecting in-vitro neuronal networks to a small mobile robot to investigate neural processes and functional modification that underlie sensorimotor learning in the nervous system. The robot sensors provide sensory-feedback signals that are coded into a spatio-temporal pattern of stimulation and the electrophysiological activity of the neuronal networks is decoded into motor commands (i.e. wheels speed). In this paper we used this embodied electrophysiology paradigm to investigate the effect of the stimulus-induced distributed plasticity and functional connectivity on the information processing capabilities of the neuronal network that is asked to achieve a reactive obstacle avoidance behavior. The results evidence a modification at functional connectivity level that can be described in terms of a Hebbian learning rule.

NOVELLINO Antonio;  CHIAPPALONE Michela;  MARTINOIA Sergio; 

2009-08-13

BIOMED CENTRAL LTD

JRC51672

1471-2202,   

http://www.biomedcentral.com/1471-2202/10/S1/P146,    https://publications.jrc.ec.europa.eu/repository/handle/JRC51672,   

10.1186/1471-2202-10-S1-P146,