Suppr超能文献

尽管神经反应存在重叠,但黑质网状部中缺乏峰电位计数和峰电位时间相关性。

Lack of spike-count and spike-time correlations in the substantia nigra reticulata despite overlap of neural responses.

作者信息

Nevet Alon, Morris Genela, Saban Guy, Arkadir David, Bergman Hagai

机构信息

Department of Physiology, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.

出版信息

J Neurophysiol. 2007 Oct;98(4):2232-43. doi: 10.1152/jn.00190.2007. Epub 2007 Aug 15.

Abstract

Previous studies of single neurons in the substantia nigra reticulata (SNr) have shown that many of them respond to similar events. These results, as well as anatomical studies, suggest that SNr neurons share inputs and thus may have correlated activity. Different types of correlation can exist between pairs of neurons. These are traditionally classified as either spike-count ("signal" and "noise") or spike-timing (spike-to-spike and joint peristimulus time histograms) correlations. These measures of neuronal correlation are partially independent and have different implications. Our purpose was to probe the computational characteristics of the basal ganglia output nuclei through an analysis of these different types of correlation in the SNr. We carried out simultaneous multiple-electrode single-unit recordings in the SNr of two monkeys performing a probabilistic delayed visuomotor response task. A total of 113 neurons (yielding 355 simultaneously recorded pairs) were studied. Most SNr neurons responded to one or more task-related events, with instruction cue (69%) and reward (63%) predominating. Response-match analysis, comparing peristimulus time histograms, revealed a significant overlap between response vectors. However, no measure of average correlation differed significantly from zero. The lack of significant SNr spike-count population correlations appears to be an exceptional phenomenon in the brain, perhaps indicating unique event-related processing by basal ganglia output neurons to achieve better information transfer. The lack of spike-timing correlations suggests that the basal high-frequency discharge of SNr neurons is not driven by the common inputs and is probably intrinsic.

摘要

以往对黑质网状部(SNr)单个神经元的研究表明,其中许多神经元对相似事件有反应。这些结果以及解剖学研究表明,SNr神经元共享输入,因此可能具有相关性活动。神经元对之间可能存在不同类型的相关性。传统上,这些相关性被分类为放电计数(“信号”和“噪声”)或放电时间(峰峰相关性和联合刺激时间直方图)相关性。这些神经元相关性的测量方法部分独立且具有不同的含义。我们的目的是通过分析SNr中这些不同类型的相关性来探究基底神经节输出核的计算特征。我们在两只执行概率延迟视觉运动反应任务的猴子的SNr中进行了同步多电极单单元记录。总共研究了113个神经元(产生355对同步记录的神经元对)。大多数SNr神经元对一个或多个与任务相关的事件有反应,其中指令提示(69%)和奖励(63%)占主导。通过比较刺激时间直方图的反应匹配分析显示,反应向量之间存在显著重叠。然而,平均相关性的测量结果与零没有显著差异。SNr放电计数群体相关性缺乏显著性似乎是大脑中的一种特殊现象,这可能表明基底神经节输出神经元进行了独特的事件相关处理以实现更好的信息传递。放电时间相关性的缺乏表明,SNr神经元的高频放电不是由共同输入驱动的,可能是内在的。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验