Omurtag A, Knight B W, Sirovich L
Laboratory of Applied Mathematics, Mount Sinai School of Medicine, New York, NY 10029, USA.
J Comput Neurosci. 2000 Jan-Feb;8(1):51-63. doi: 10.1023/a:1008964915724.
The dynamics of large populations of interacting neurons is investigated. Redundancy present in subpopulations of cortical networks is exploited through the introduction of a probabilistic description. A derivation of the kinetic equations for such subpopulations, under general transmembrane dynamics, is presented. The particular case of integrate-and-fire membrane dynamics is considered in detail. A variety of direct simulations of neuronal populations, under varying conditions and with as many as O(10(5)) neurons, is reported. Comparison is made with analogous kinetic equations under the same conditions. Excellent agreement, down to fine detail, is obtained. It is emphasized that no free parameters enter in the comparisons that are made.
研究了大量相互作用神经元的动力学。通过引入概率描述来利用皮质网络亚群中存在的冗余。给出了在一般跨膜动力学下此类亚群动力学方程的推导。详细考虑了积分发放膜动力学的特殊情况。报告了在不同条件下对多达O(10⁵)个神经元的神经元群体进行的各种直接模拟。在相同条件下与类似的动力学方程进行了比较。在细节上都取得了极好的一致性。需要强调的是,在进行的比较中没有引入自由参数。