Netoff Theoden I, Clewley Robert, Arno Scott, Keck Tara, White John A
Department of Biomedical Engineering, and Center for Memory and Brain, Boston University, Boston, Massachusetts 02215, USA.
J Neurosci. 2004 Sep 15;24(37):8075-83. doi: 10.1523/JNEUROSCI.1509-04.2004.
In hippocampal slice models of epilepsy, two behaviors are seen: short bursts of electrical activity lasting 100 msec and seizure-like electrical activity lasting seconds. The bursts originate from the CA3 region, where there is a high degree of recurrent excitatory connections. Seizures originate from the CA1, where there are fewer recurrent connections. In attempting to explain this behavior, we simulated model networks of excitatory neurons using several types of model neurons. The model neurons were connected in a ring containing predominantly local connections and some long-distance random connections, resulting in a small-world network connectivity pattern. By changing parameters such as the synaptic strengths, number of synapses per neuron, proportion of local versus long-distance connections, we induced "normal," "seizing," and "bursting" behaviors. Based on these simulations, we made a simple mathematical description of these networks under well-defined assumptions. This mathematical description explains how specific changes in the topology or synaptic strength in the model cause transitions from normal to seizing and then to bursting. These behaviors appear to be general properties of excitatory networks.
在癫痫的海马切片模型中,可观察到两种行为:持续100毫秒的短阵电活动和持续数秒的癫痫样电活动。短阵活动起源于CA3区,该区存在高度的反复兴奋性连接。癫痫发作起源于CA1区,该区的反复连接较少。为了解释这种行为,我们使用几种类型的模型神经元对兴奋性神经元的模型网络进行了模拟。模型神经元连接成一个环,主要包含局部连接和一些长距离随机连接,形成了小世界网络连接模式。通过改变诸如突触强度、每个神经元的突触数量、局部连接与长距离连接的比例等参数,我们诱导出了“正常”“癫痫发作”和“短阵活动”行为。基于这些模拟,我们在明确的假设下对这些网络进行了简单的数学描述。这种数学描述解释了模型中拓扑结构或突触强度的特定变化如何导致从正常状态转变为癫痫发作状态,进而转变为短阵活动状态。这些行为似乎是兴奋性网络的普遍特性。