Mathematical Modeling

Experimental model of neuronal network learning in dissociated hippocampal cultures

A. S. Pimashkin^ab, A. A. Gladkov^ac, I. V. Mukhina^ab, M. S. Burtsev^de, V. A. Ilyin^d, V. B. Kazantsev<sup>ab

a</sup> Nizhny Novgorod State University, Nizhny Novgorod, 603950, Russia
^b Institute of Applied Physics of RAS, Nizhny Novgorod, 603950, Russia
^c Nizhny Novgorod State Medicine Academy, Nizhny Novgorod, 603005, Russia
^d NRC Kurchatov Institute, Moscow, 123182, Russia
^e NII of Normal Physiology of RAMS, Moscow, 125315, Russia

Abstract: Basic principles of learning in neural networks are widely studied with the experimental model of dissociated cultures of neurons on microelectrode arrays. This approach allows local stimulation and recording of neuronal activity. It was shown that neural networks developed in dissociated neural culture can be conditioned to reply via defined electrode on electrical stimulation. There are still problems with stability and reproducibility of conditioned replies in this experimental paradigm. In our work we propose new method of neuronal culture conditioning that allows higher stability and reproducibility of learned replies.

Key words: neuron, neuronal network, microelectrode array, neuroanimat, spikes.

UDC: 51-76

Received 11.10.2012, Published 18.10.2012