Identification of synaptic connections in neural ensembles by graphical models
Identification of synaptic connections in neural ensembles by graphical models
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DOI：
10.1016/s0165-0270(97)00100-3
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发表时间：
1997-11-07
影响因子：
3
通讯作者：
Sandkuhler, J
中科院分区：
文献类型：
--
作者：
Dahlhaus, R;Eichler, M;Sandkuhler, J
提出了一种在较大的神经网络中识别直接突触连接的方法。它基于多元点过程的条件相关图。考虑到所有其他神经元，这些连接是通过两个神经元的部分光谱相干性来识别的。显示了如何通过谱密度矩阵的求逆来计算这些相干性。在 GENESIS 的模拟中，我们讨论了识别不同神经元的方法的相关性，包括兴奋性反馈环和具有侧抑制的网络。 (C) 1997 Elsevier Science B.V.
A method for the identification of direct synaptic connections in a larger neural net is presented. It is based on a conditional correlation graph for multivariate point processes. The connections are identified via the partial spectral coherence of two neurons, given all others. It is shown how these coherences can be calculated by inversion of the spectral density matrix. In simulations with GENESIS, we discuss the relevance of the method for identifying different neural ensembles including an excitatory feedback loop and networks with lateral inhibitions. (C) 1997 Elsevier Science B.V.