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Spectral signs of genetically conditioned convulsibility of rats of the Krushinskiĭ-Molodkina (KM) strain were determined when studying the background electrical brain activity. These signs were: an increase of the delta-activity power in motor and visual cortical zones; considerable increase of the hippocampal potential power; weakening of the caudate nucleus potential power. Spectra of biopotentials being approximated by theoretical spectral function, model parameters simulating physiological characteristics of neural networks were estimated (an inverse problem of modelling). Spectral signs of convulsibility were shown to reflect changes in properties of the neural network. On the basis of calculations it is supposed that genetically determined convulsibility of KM rats results from weakening of inhibitory functions of the caudate nucleus as well as from increased excitability (reactivity) of hippocampal and neocortical neurons.

Rats of the Krushinskiĭ-Molodkina (KM) strain genetically predisposed to audiogenic seizures were repeatedly injected camphor for 4-5 months in gradually increasing doses (beginning from those below the seizure threshold up to those above it). As a result of "adaptation" to the convulsant action rats endured without seizures camphor doses 1.5-3 times higher than seizure threshold ones. Parallel with this "adaptation" the motor cortex of KM rats accumulated properties peculiar to the epileptic focus: spontaneous epileptiform spikes were recorded there after the camphor application. Estimation of the neural network parameters from spectra of the motor cortex biopotentials using the network model has shown a decrease of a parameter reflecting efficacy of the recurrent inhibition mechanisms. It is supposed that development of compensatory processes making rats able to avoid generalized camphor seizures are related to an increase of inhibitory functions of the caudate nucleus and weakening of the hippocampal excitability.

Desynchronous (low voltage fast activity), synchronous (high voltage slow waves) as well as convulsive brain activities were stimulated by a computer model of neuronal population. Network excitatory and inhibitory elements possessed fundamental dynamic properties of real neurones. Being independent both of the excitability of elements and of external influence efficacy, synchronous (desynchronous) network activity resulted from the increase (decrease) of the average power of "neuronal" interconnections which imitated mutual and recurrent excitation and inhibition. The inhibition efficacy being reduced as compared with excitation, synchronization of elements became intensified. As a consequence, the rhythmic activity amplitude increased and the appearance of self-sustained oscillations simulating convulsive activity was facilitated. The probable mechanism of EEG activation by virtue of the reduction of mutual and recurrent excitation and inhibition efficacy as well as the significance of inhibitory mechanism deficiency for epileptogenesis are discussed.

On the basis of neuronal network a linearized model of power spectrum of the network stable activity was calculated with the approximation of external input by "white" noise. The power spectrum function obtained was used for approximation of the power spectra of the rats motor cortex potentials by the least squares method. As a result the network parameters modelling excitatory and inhibitory cellular and synaptic mechanisms were calculated for two rat strains differing in seizure readiness. As a result of calculations genetically predisposed to seizures KM rats were assumed to differ from unpredisposed to seizures Wistar rats in the increase of efficacy of neuronal interactions (excitatory and inhibitory) as a consequence of the enhanced neuronal "reactivity".

Brain rhythmic activity model on the basis of space uniform neuronal network consisting of excitatory and inhibitory elements was examined. Network activity description by "lump approximation" was compared with simulation model computation. Lump approximation parameters dependence on the properties of neurons and synapses as well as conditions of the transition between network activity types which imitate desynchronous (low voltage fast activity) and synchronous (high voltage slow waves) brain activities were obtained.