Malleability of gamma rhythms enhances population-level correlations.

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Journal of Computational Neuroscience Pub Date : 2021-05-01 Epub Date: 2021-04-05 DOI:10.1007/s10827-021-00779-4
Sonica Saraf, Lai-Sang Young
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引用次数: 3

Abstract

An important problem in systems neuroscience is to understand how information is communicated among brain regions, and it has been proposed that communication is mediated by neuronal oscillations, such as rhythms in the gamma band. We sought to investigate this idea by using a network model with two components, a source (sending) and a target (receiving) component, both built to resemble local populations in the cerebral cortex. To measure the effectiveness of communication, we used population-level correlations in spike times between the source and target. We found that after correcting for a response time that is independent of initial conditions, spike-time correlations between the source and target are significant, due in large measure to the alignment of firing events in their gamma rhythms. But, we also found that regular oscillations cannot produce the results observed in our model simulations of cortical neurons. Surprisingly, it is the irregularity of gamma rhythms, the absence of internal clocks, together with the malleability of these rhythms and their tendency to align with external pulses - features that are known to be present in gamma rhythms in the real cortex - that produced the results observed. These findings and the mechanistic explanations we offered are our primary results. Our secondary result is a mathematical relationship between correlations and the sizes of the samples used for their calculation. As improving technology enables recording simultaneously from increasing numbers of neurons, this relationship could be useful for interpreting results from experimental recordings.

伽马节律的延展性增强了种群水平的相关性。
系统神经科学的一个重要问题是理解信息是如何在大脑区域之间传递的,并且已经提出了信息是由神经元振荡介导的,例如伽马波段的节奏。我们试图通过使用一个有两个组成部分的网络模型来研究这个想法,一个来源(发送)和一个目标(接收)组成部分,这两个组成部分都类似于大脑皮层中的局部人群。为了衡量通信的有效性,我们使用了源和目标之间高峰时间的人口水平相关性。我们发现,在校正了独立于初始条件的响应时间后,源和目标之间的峰值时间相关性是显著的,这在很大程度上是由于在它们的伽马节律中发射事件的对齐。但是,我们也发现有规律的振荡不能产生我们在皮质神经元模型模拟中观察到的结果。令人惊讶的是,正是伽马节律的不规则性,内部时钟的缺失,以及这些节律的延展性以及它们与外部脉冲一致的趋势——这些特征已知存在于真实皮层的伽马节律中——产生了观察到的结果。这些发现和我们提供的机械解释是我们的主要结果。我们的第二个结果是相关性和用于计算的样本大小之间的数学关系。随着技术的进步,可以同时记录越来越多的神经元,这种关系可能有助于解释实验记录的结果。
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来源期刊
CiteScore
2.00
自引率
8.30%
发文量
32
审稿时长
3 months
期刊介绍: The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience, including advances in neural data analysis methods yielding insights into the function of the nervous system, are also welcomed (in this case, methodological papers should include an application of the new method, exemplifying the insights that it yields).It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience.
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