Conference devoted to the 90th anniversary of Alexei A. Lyapunov

Akademgorodok, Novosibirsk, Russia, October 8-11, 2001,
(state registration number 0320300064)

Abstracts


Cybernetics and Phisiology

Components of evoked potentials

Pokrovsky A.N.

V.I.Zubov Research Institute for Computational Mathematics and Control Processes of St-Petersburg State University (St-Petersburg)

It is well known that evoked potentials (EP) are miscellanies of components with different origins. Usual classification of the components of cortical EP as surface positive ones and surface negative ones is not valid. They cannot evaluate the latent periods of the EP components.

It is widespread opinion that main part of EP is formed by superposition of extracellular potentials of neuronal dendrits. Therefore we consider extracellular potential of single neuron? dendrites during activation of the synapses of several axons of the same kind as the elementary part of EP component Two models of the elementary part of EP component was studied using linear approximation. The second model took into consideration bifurcation of dendrites. It was a boundary problem defined on the finite graph (tree) for equations of parabolic type. Extracellular potentials was calculated as the potentials in homogenous isotropic medium with finite conductivity, the source of the potentials being charge distribution on the trees. The EP component is defined as superposition of the elementary parts.

The model of EP component was studied as a function of the space coordinates and time. It was shown that normalized space distribution of the potential change in a little only during EP. This function of the space coordinates (?profile? of component through the cortex in particular) can be used as ?adiabatic? invariant of the component.

Let us accept that sinaptic ?clouds? of the axonal systems of different origins differ each from other. Then ?profiles? of different components through the cortex are linear independent.

Times of beginnings of EP components (or latent periods) differ. It is naturally to use the latent periods as the basis of classification of the components.

Our model of EP is superposition of a number of the components with linear independent profiles and different latent periods, high-frequency noise and low-frequency background of cortex? activity. The algorithm and the programs for calculation of the latent periods of the components was worked out. The programs was verified using existing records of EP. High quality of the synchronous layer records of EP is necessary for calculation of latent periods.

The work is supported by RFBR project 99-01-00699.

Note. Abstracts are published in author's edition



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