Estimating Instantaneous Irregularity of Neuronal Firing
Estimating Instantaneous Irregularity of Neuronal Firing
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DOI：
10.1162/neco.2009.08-08-841
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发表时间：
2009-07
影响因子：
2.9
通讯作者：
T. Shimokawa;S. Shinomoto
中科院分区：
文献类型：
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作者：
T. Shimokawa;S. Shinomoto
体内皮质神经元被认为是泊松尖峰发生器，除了随机放电率之外不传递任何信息。最近，研究人员使用一种度量来分析峰间间隔的局部变化，发现单个神经元在生成峰时表达特定的模式，这可以象征性地称为规则的、随机的或突发的，在时间上相当不变。为了更详细地研究放电模式的动态，我们在这里提出了一种贝叶斯方法，用于同时估计给定尖峰序列的放电不规则性和放电率，并且我们实现了一种算法，该算法可以使经验贝叶斯估计对于包含大量尖峰的数据来说是可行的。将该方法应用于电生理数据揭示了个体神经元的放电不规则程度和放电率之间的微妙相关性。放电不规则性在对放电速率的低程度依赖方面并没有太大偏差，并且对于皮质区域 V1 和 MT 中的单个神经元来说几乎保持不变，而在丘脑外侧膝状核中则波动很大。这表明分别存在和不存在用于维持皮层和丘脑放电模式的自动控制机制。
Cortical neurons in vivo had been regarded as Poisson spike generators that convey no information other than the rate of random firing. Recently, using a metric for analyzing local variation of interspike intervals, researchers have found that individual neurons express specific patterns in generating spikes, which may symbolically be termed regular, random, or bursty, rather invariantly in time. In order to study the dynamics of firing patterns in greater detail, we propose here a Bayesian method for estimating firing irregularity and the firing rate simultaneously for a given spike sequence, and we implement an algorithm that may render the empirical Bayesian estimation practicable for data comprising a large number of spikes. Application of this method to electrophysiological data revealed a subtle correlation between the degree of firing irregularity and the firing rate for individual neurons. Irregularity of firing did not deviate greatly around the low degree of dependence on the firing rate and remained practically unchanged for individual neurons in the cortical areas V1 and MT, whereas it fluctuated greatly in the lateral geniculate nucleus of the thalamus. This indicates the presence and absence of autocontrolling mechanisms for maintaining patterns of firing in the cortex and thalamus, respectively.