Epileptic seizures from abnormal networks: why some seizures defy predictability.
Epileptic seizures from abnormal networks: why some seizures defy predictability.
复制标题
DOI：
10.1016/j.eplepsyres.2011.11.006
复制
发表时间：
2012-05
影响因子：
2.2
通讯作者：
Franaszczuk PJ
中科院分区：
文献类型：
--
作者：
Anderson WS;Azhar F;Kudela P;Bergey GK;Franaszczuk PJ
癫痫发作的预测已被证明在临床现实环境中是困难的。有没有可能皮层放电的波动会影响癫痫发作在发作区的开始？为了测试这一点，我们现在使用了神经网络模拟在大脑皮质的计算模型中，该模型总共有65,536个神经元，其细胞间连接模式模仿组织学数据。空间分布的泊松驱动背景输入代表邻近皮质的活动，影响1%的神经元。用伽玛分布对爆间相间隔期进行拟合，对随机性进行非参数检验，并进行动力系统分析以寻找间歇期内的周期1轨道。非参数分析表明，间隔是从它们的基本联合分布中随机提取的，而动力系统分析与对爆发相产生的非确定性动力学解释是一致的。这些结果表明，在大脑皮质具有类似癫痫灶的异常连接的区域，有可能通过周围皮质区域的输入波动来启动癫痫活动。这些发现提示了一种从异常的局灶性癫痫网络中产生发作的可能性。这一机制还有助于解释在一些患者中预测部分癫痫发作的困难。
Seizure prediction has proven to be difficult in clinically realistic environments. Is it possible that fluctuations in cortical firing could influence the onset of seizures in an ictal zone? To test this, we have now used neural network simulations in a computational model of cortex having a total of 65,536 neurons with intercellular wiring patterned after histological data. A spatially distributed Poisson driven background input representing the activity of neighboring cortex affected 1% of the neurons. Gamma distributions were fit to the interbursting phase intervals, a non-parametric test for randomness was applied, and a dynamical systems analysis was performed to search for period-1 orbits in the intervals. The non-parametric analysis suggests that intervals are being drawn at random from their underlying joint distribution and the dynamical systems analysis is consistent with a nondeterministic dynamical interpretation of the generation of bursting phases. These results imply that in a region of cortex with abnormal connectivity analogous to a seizure focus, it is possible to initiate seizure activity with fluctuations of input from the surrounding cortical regions. These findings suggest one possibility for ictal generation from abnormal focal epileptic networks. This mechanism additionally could help explain the difficulty in predicting partial seizures in some patients.