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首页> 外文期刊>Journal of Computational Neuroscience >Dynamical changes in neurons during seizures determine tonic to clonic shift
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Dynamical changes in neurons during seizures determine tonic to clonic shift

机译：癫痫发作期间神经元的动态变化决定了强直向阵挛的转变

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摘要

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.
机译：强直-阵挛性癫痫发作从高频异步活动转变为低频相干振荡，但这种转变的机制仍然未知。由于蜂窝响应的变化，我们提出了网络同步的转变。在这里，我们使用来自Morris-Lecar（M-L）模型神经元的具有突触抑制的相位响应曲线（PRC），并逐渐降低网络仿真中细胞的输入电流。此方法有效地降低了触发速率，导致转换为更大的网络同步性，从而说明了过渡现象的可能机制。 PRC是从基于M-L电导的模型单元中在极限周期内输入电流范围内测得的。用由二阶统计量生成的网络拓扑模拟了一个包含3000个兴奋神经元的大型网络，该拓扑允许一定范围的种群同步。用仓本有序参数测量振荡细胞的群体同步性，这揭示了我们的模型网络表现出的从滋补相到阵挛相的转变。与EEG数据相比，用于强直-阵挛性癫痫发作转变的细胞反应转移机制可以紧密再现种群行为。

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