Kalitzin S, van Dijk B W, Spekreijse H, van Leeuwen W A
Graduate School of Neurosciences Amsterdam, Netherlands Ophthalmic Research Institute, Department of Visual Systems Analysis, Amsterdam, The Netherlands.
Biol Cybern. 1997 Jan;76(1):73-83. doi: 10.1007/s004220050322.
This paper studies the relation between the functional synaptic connections between two artificial neural networks and the correlation of their spiking activities. The model neurons had realistic non-oscillatory dynamic properties and the networks showed oscillatory behavior as a result of their internal synaptic connectivity. We found that both excitation and inhibition cause phase locking of the oscillating activities. When the two networks excite each other the oscillations synchronize with zero phase lag, whereas mutual inhibition between the networks resulted in an anti-phase (half period phase difference) synchronization. Correlations between the activities of the two networks can also be caused by correlated external inputs driving the systems (common input). Our analysis shows that when the networks exhibit oscillatory behavior and the rate of the common input is smaller than a characteristic network oscillator frequency, the cross-correlation functions between the activities of two systems still carry information about the mutual synaptic connectivity. This information can be retrieved with linear partialization, removing the influence of the common input. We further explored the network responses to periodic external input. We found that when the input is of a frequency smaller than a certain threshold, the network responds with bursts at the same frequency as the input. Above the threshold, the network responds with a fraction of the input frequency. This frequency threshold, characterizing the oscillatory properties of the network, is also found to determine the limit to which linear partialization works.
本文研究了两个人工神经网络之间的功能性突触连接与其尖峰活动相关性之间的关系。模型神经元具有逼真的非振荡动态特性，并且由于其内部突触连接性，网络呈现出振荡行为。我们发现，兴奋和抑制都会导致振荡活动的锁相。当两个网络相互兴奋时，振荡以零相位滞后同步，而网络之间的相互抑制则导致反相（半周期相位差）同步。两个网络活动之间的相关性也可能由驱动系统的相关外部输入（共同输入）引起。我们的分析表明，当网络呈现振荡行为且共同输入的速率小于特征网络振荡器频率时，两个系统活动之间的互相关函数仍携带有关相互突触连接性的信息。可以通过线性偏微分去除共同输入的影响来检索此信息。我们进一步探索了网络对周期性外部输入的响应。我们发现，当输入频率小于某个阈值时，网络以与输入相同的频率产生爆发响应。高于该阈值时，网络以输入频率的一部分进行响应。这个表征网络振荡特性的频率阈值也被发现决定了线性偏微分起作用的极限。
