Abstracts

RATIONALE: There is growing interest in the possible application of external stimulation to terminate epileptic seizures. Investigations have shown that epileptic afterdischarges in humans can be terminated by external stimuli (Lesser et al. 2000). We have studied the potential for termination of bursting activity by external stimuli in a model neural network. METHODS: Networks of multiple neurons with both inhibitory and excitatory synaptic connections were modeled based on the Av-Ron Rinzel reduced model of a single neuron. Each neuron in the network has synaptic inputs from randomly chosen excitatory and inhibitory neurons. The number of excitatory and inhibitory connections on the input of each neuron is kept constant. The network is constantly activated by random excitatory input. The initial parameters of network activation and connectivity were chosen to simulate synchronized bursting activity. The level of noise input was then increased or, alternatively, external depolarizing current was applied to the inputs of all neurons in the network. RESULTS: Applying an external excitatory stimulus below a certain level increases bursting activity, producing constant activation of the network neurons. Increasing the amplitude of the stimulus above a certain level, however, causes cessation of bursting. This effect is observed both with constant depolarizing current and random (Poisson) excitatory input applied to all neurons in the network. CONCLUSIONS: Applying external stimuli to bursting neuronal networks can terminate the bursting activity in the networks. This effect can be produced with constant external depolarizing inputs or increased random excitatory input. These simulated neuronal networks provide models for external excitatory stimuli that can terminate bursting activity. Supported by the NIH grant NS 38958