Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation
- 1Department of Physics, University of Minnesota, Minneapolis, MN, USA
- 2Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
Seizure control using deep brain stimulation (DBS) provides an alternative therapy to patients with intractable and drug resistant epilepsy. This paper presents novel DBS stimulus protocols to disrupt seizures. Two protocols are presented: open-loop stimulation and a closed-loop feedback system utilizing measured firing rates to adjust stimulus frequency. Stimulation suppression is demonstrated in a computational model using 3000 excitatory Morris–Lecar (M–L) model neurons connected with depressing synapses. Cells are connected using second order network topology (SONET) to simulate network topologies measured in cortical networks. The network spontaneously switches from tonic to clonic as synaptic strengths and tonic input to the neurons decreases. To this model we add periodic stimulation pulses to simulate DBS. Periodic forcing can synchronize or desynchronize an oscillating population of neurons, depending on the stimulus frequency and amplitude. Therefore, it is possible to either extend or truncate the tonic or clonic phases of the seizure. Stimuli applied at the firing rate of the neuron generally synchronize the population while stimuli slightly slower than the firing rate prevent synchronization. We present an adaptive stimulation algorithm that measures the firing rate of a neuron and adjusts the stimulus to maintain a relative stimulus frequency to firing frequency and demonstrate it in a computational model of a tonic-clonic seizure. This adaptive algorithm can affect the duration of the tonic phase using much smaller stimulus amplitudes than the open-loop control.
Keywords: seizure model, deep brain stimulation, tonic-clonic, synchrony
Citation: Beverlin B II and Netoff TI (2013) Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation. Front. Neural Circuits 6:126. doi: 10.3389/fncir.2012.00126
Received: 17 October 2012; Accepted: 27 December 2012;
Published online: 06 February 2013.
Copyright © 2013 Beverlin and Netoff. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
*Correspondence: Theoden I. Netoff, Department of Biomedical Engineering, University of Minnesota, 7-105 Nis Hasselmo Hall, 312 Church St SE, Minneapolis, MN 55455, USA. e-mail: firstname.lastname@example.org