A tonic-clonic seizure transitions from high frequency asynchronous activity to low frequency coherent oscillations, yet the mechanism of transition remains unknown. We propose a shift in network synchrony due to changes in cellular response. Here we use phase-response curves (PRC) from Morris-Lecar (M-L) model neurons with synaptic depression and gradually decrease input current to cells within a network simulation. This method effectively decreases firing rates resulting in a shift to greater network synchrony illustrating a possible mechanism of the transition phenomenon. PRCs are measured from the M-L conductance based model cell with a range of input currents within the limit cycle. A large network of 3000 excitatory neurons is simulated with a network topology generated from second-order statistics which allows a range of population synchrony. The population synchrony of the oscillating cells is measured with the Kuramoto order parameter, which reveals a transition from tonic to clonic phase exhibited by our model network. The cellular response shift mechanism for the tonic-clonic seizure transition reproduces the population behavior closely when compared to EEG data.
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Thanks to Bard Ermentrout and Chris Warren for helpful discussions. Funding for this work provided by UMN Grant-In-Aid and NSF CAREER award.
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Beverlin, B., Kakalios, J., Nykamp, D. et al. Dynamical changes in neurons during seizures determine tonic to clonic shift. J Comput Neurosci 33, 41–51 (2012). https://doi.org/10.1007/s10827-011-0373-5
- Seizure model
- Tonic clonic