非线性物理破解神经编码机制

信息在神经系统中以脉冲点序列的形式传输和处理，神经系统如何通过脉冲点序列对所表达的信息进行编码，一直是一个谜．人们曾普遍认为，神经可能通过发放率（单位时间发放脉冲出现的次数）对信息编码，也有人猜测，神经可通过脉冲点序列的时序编码．由于神经发放的随机性，这就使得任何编码机制都面临着被表达信息的确定性与表达该信息的信号的随机性的矛盾．通过神经非线性随机动力学模型，文章作者发现，神经点序列的发放率对点序列的时序信息传输的影响，揭示了神经点序列时序信息在神经非线性传输中的随机共振特征．由此预期，并进一步通过听觉心理物理实验观察到，在一定条件下噪声对听觉的增强作用．从而通过非线性物理揭示了听觉时序编码机制的存在以及在时序编码中随机性噪声的积极作用．

Cracking neural coding by nonlinear physics

Information in neural systems is transferred and processed in the form of spike trains, but how a spike train encodes the information it conveys is unknown. The main controversy of the neural coding mechanism is whether information is encoded in the temporal pattern or the rate of the spike train, and how does the random neural spike train express deterministic information. Through a nonlinear neural dynamic model we discover that the spike rate and the randomness of the spiking influence temporal information transfer in a way like stochastic resonance. This predicts an enhancing effect of noise on hearing, which is further confirmed by psychophysical experiments.