Modeling the functional connectivity in embodied in vitro neuronal network
© Novellino et al; licensee BioMed Central Ltd. 2009
Published: 13 July 2009
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 [1, 2]. We describe the investigation of the effect of the stimulus-induced distributed plasticity and functional connectivity on the information processing capabilities of the neuronal network. The results evidence a modification at functional connectivity level that can be described in terms of a Hebbian learning rule.
The hypothetical configuration for the obstacle avoidance achievement requires the cross-connection weights to be weaker than the direct ones. The achieve modulation is close to the theoretical achievement thus confirming the possibility to describe the embodied neuro-robotic paradigm in terms of Hebbian rules.
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