Liljenström H, Wu X B
Department of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm, Sweden.
Int J Neural Syst. 1995 Mar;6(1):19-29. doi: 10.1142/s0129065795000032.
Spontaneous neuronal activity and synaptic noise are well-known phenomena, but their biological significance has not yet been assessed. Using a computer model of the olfactory cortex we show that such activity, expressed as temporal noise in the model, can reduce recall time in associative memory tasks. We investigate both additive and multiplicative noise, and find optimal noise levels for which the recall time reaches a minimum. In addition, we demonstrate that noise can induce state transitions, such that the system is pushed from one attractor state to another. For high enough noise levels the dynamics can change dramatically and, for example, switch from an oscillatory to a chaos-like behavior. We discuss these findings in light of their significance for neural information processing.
自发神经元活动和突触噪声是众所周知的现象，但其生物学意义尚未得到评估。我们使用嗅觉皮层的计算机模型表明，这种以模型中的时间噪声表示的活动可以减少联想记忆任务中的回忆时间。我们研究了加性噪声和乘性噪声，并找到了使回忆时间达到最小值的最佳噪声水平。此外，我们证明噪声可以诱导状态转换，从而使系统从一个吸引子状态转变为另一个吸引子状态。对于足够高的噪声水平，动力学可以发生显著变化，例如，从振荡行为转变为类似混沌的行为。我们根据这些发现对神经信息处理的意义进行了讨论。
