Yamazaki Tadashi, Tanaka Shigeru
Laboratory for Visual Neurocomputing, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.
Neural Netw. 2007 Apr;20(3):290-7. doi: 10.1016/j.neunet.2007.04.004. Epub 2007 Apr 29.
We examined closely the cerebellar circuit model that we have proposed previously. The model granular layer generates a finite but very long sequence of active neuron populations without recurrence, which is able to represent the passage of time. For all the possible binary patterns fed into mossy fibres, the circuit generates the same number of different sequences of active neuron populations. Model Purkinje cells that receive parallel fiber inputs from neurons in the granular layer learn to stop eliciting spikes at the timing instructed by the arrival of signals from the inferior olive. These functional roles of the granular layer and Purkinje cells are regarded as a liquid state generator and readout neurons, respectively. Thus, the cerebellum that has been considered to date as a biological counterpart of a perceptron is reinterpreted to be a liquid state machine that possesses powerful information processing capability more than a perceptron.
我们仔细研究了我们之前提出的小脑回路模型。该模型的颗粒层会生成一系列有限但非常长的活跃神经元群体序列，且无递归，这能够表征时间的流逝。对于输入到苔藓纤维的所有可能的二进制模式，该回路会生成相同数量的不同活跃神经元群体序列。接收来自颗粒层神经元平行纤维输入的模型浦肯野细胞学会在来自下橄榄核的信号到达所指示的时间停止引发尖峰。颗粒层和浦肯野细胞的这些功能作用分别被视为液态发生器和读出神经元。因此，迄今为止被认为是感知机生物学对应物的小脑被重新解释为一种液态机器，它拥有比感知机更强大的信息处理能力。
