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A Neural Network Model of Propagation of Burst Activity

Piotr J. Franaszczuk1,3, Pawel Kudela1,3,4, Gregory K. Bergey 1,2,3

Departments of 1Neurology and 2Physiology, 3Maryland Epilepsy Center, University of Maryland School of Medicine, Baltimore, Maryland U.S.A. and 4 Laboratory of Medical Physics, Warsaw University, Warsaw, Poland.

Patterns of propagation of epileptiform activity are important in the classification and diagnosis of different seizures. In recent years detailed models of generation and propagation of epileptiform activity in mesial temporal structures have been developed. These models simulate the generation and propagation of bursts in highly organized neuronal circuits. Cultures of dissociated spinal cord neurons exhibit spread of synchronous activity in neural networks without specific circuits. Epileptic seizures originating in mesial structures propagate to other brain structures. Measurements of the velocities of propagation of epileptiform activity in neocortical tissue indicate that propagation is significantly slower than the axon propagation speed and slower than in hippocampal slices. This suggests that this process may be a cooperative phenomenon involving a large number of sparsely connected cells. This type of connectivity can be modeled as a two-dimensional array of locally connected neurons. Our model consists of a square array of locally connected neurons (up to 150 by 150 neurons). The modified Av-Ron - Rinzel model was used to simulate single neurons. Each neuron is synaptically connected with randomly chosen neurons from its immediate neighborhood. We determined the values of model parameters needed to produce bursting activity in such a set of neurons. Repetitive firing activity in the network was triggered by one cell at the beginning of the simulation (i.e. the selected cell received a input current strong enough to evoke a burst of action potentials). Membrane potentials for selected cells and histograms of generated action potentials for all cells were recorded for different strengths and patterns of connectivity. The results of simulations show that patterns of spread of synchronous bursting activity and the velocity of spread is dependent on strength and number of synaptic connections, but relatively independent of exact patterns of connections. For a certain range of parameters, the velocity of burst propagation is in agreement with measurements of the propagation of epileptiform activity in neocortical tissue.

Supported by NIH grant NS 33732-01 to GKB and PJF and KBN grant 8T11B 02013 to PK.


Proceedings of the 1998 Workshop on Neural Modeling of Brain and Cognitive Disorders, University of Maryland, College Park, MD,1998, p39.

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