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首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >Neuronal integration mechanisms have little effect on spike auto-correlations of cortical neurons.
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Neuronal integration mechanisms have little effect on spike auto-correlations of cortical neurons.

机译:神经元整合机制对皮层神经元的尖峰自相关影响很小。

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摘要

Cortical neurons of behaving animals generate irregular spike sequences, but the sequences generally differ from an entirely random sequence (Poisson process), and they have temporal correlations (spike auto-correlations). Temporally correlated spike sequences can be brought about because of incoming synaptic inputs to the neuron, or because of the neuronal integration mechanism. In this paper, we attempt to determine which is the origin of spike auto-correlations observed in the spiking data recorded from neurons in the prefrontal cortex of a monkey preserving a cue information in the delay response task experiment. Each incoming input is assumed to be independent from its own spike events, and the temporal integration in the neuron is assumed to be reset by every spike event. So, the process to spike is assumed to be divided into two processes: the process independent from its own spikes, which drives the process reset by its own spikes. Under these assumptions, it is found that the spike-independent process needs to have temporal correlations, through examinations of two kinds of correlation coefficient of consecutive inter-spike intervals. It is also found that the spike-reset process has little effect on the spike auto-correlations and the interval distributions. This suggests that the spike auto-correlation does originate in the temporal correlation of incoming synaptic inputs and the neuronal integration mechanism has little effect on the spike auto-correlation.
机译:行为动物的皮质神经元产生不规则的刺突序列,但是该序列通常不同于完全随机的序列(泊松过程),并且它们具有时间相关性(刺突自相关)。暂时相关的尖峰序列可能是由于传入神经元的突触输入或神经元整合机制引起的。在本文中,我们试图确定在延迟响应任务实验中保留线索信息的猴子前额叶皮层神经元记录的峰值数据中观察到的峰值自相关的起源。假定每个传入输入均独立于其自身的尖峰事件,并且假定每个尖峰事件都会重置神经元中的时间积分。因此,假设尖峰过程分为两个过程:独立于其自身尖峰的过程,该过程通过自身尖峰来驱动进程重置。在这些假设下,通过检查连续的峰值间间隔的两种相关系数,发现峰值独立过程需要具有时间相关性。还发现尖峰重置过程对尖峰自相关和间隔分布几乎没有影响。这表明尖峰自相关确实起源于传入突触输入的时间相关性,并且神经元整合机制对尖峰自相关影响很小。

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