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γ 节律的形态分析支持抑制稳定网络中的超线性抑制状态。

Shape analysis of gamma rhythm supports a superlinear inhibitory regime in an inhibition-stabilized network.

机构信息

IISc Mathematics Initiative, Department of Mathematics, Indian Institute of Science, Bangalore, India.

Centre for Neuroscience, Indian Institute of Science, Bangalore, India.

出版信息

PLoS Comput Biol. 2022 Feb 14;18(2):e1009886. doi: 10.1371/journal.pcbi.1009886. eCollection 2022 Feb.

Abstract

Visual inspection of stimulus-induced gamma oscillations (30-70 Hz) often reveals a non-sinusoidal shape. Such distortions are a hallmark of non-linear systems and are also observed in mean-field models of gamma oscillations. A thorough characterization of the shape of the gamma cycle can therefore provide additional constraints on the operating regime of such models. However, the gamma waveform has not been quantitatively characterized, partially because the first harmonic of gamma, which arises because of the non-sinusoidal nature of the signal, is typically weak and gets masked due to a broadband increase in power related to spiking. To address this, we recorded local field potential (LFP) from the primary visual cortex (V1) of two awake female macaques while presenting full-field gratings or iso-luminant chromatic hues that produced huge gamma oscillations with prominent peaks at harmonic frequencies in the power spectra. We found that gamma and its first harmonic always maintained a specific phase relationship, resulting in a distinctive shape with a sharp trough and a shallow peak. Interestingly, a Wilson-Cowan (WC) model operating in an inhibition stabilized mode could replicate this shape, but only when the inhibitory population operated in the super-linear regime, as predicted recently. However, another recently developed model of gamma that operates in a linear regime driven by stochastic noise failed to produce salient harmonics or the observed shape. Our results impose additional constraints on models that generate gamma oscillations and their operating regimes.

摘要

视觉检查刺激诱导的伽马振荡(30-70 Hz)通常呈现出非正弦形状。这种失真是非线性系统的标志,也在伽马振荡的平均场模型中观察到。因此,对伽马周期形状的彻底表征可以为这些模型的工作模式提供额外的约束。然而,伽马波形尚未得到定量描述,部分原因是由于信号的非正弦性质而产生的伽马的第一谐波通常较弱,并且由于与尖峰相关的功率的宽带增加而被屏蔽。为了解决这个问题,我们在两只清醒的雌性猕猴的初级视觉皮层(V1)记录局部场电位(LFP),同时呈现全场光栅或等亮度彩色色调,这些刺激产生了巨大的伽马振荡,在功率谱中在谐波频率处具有明显的峰值。我们发现,伽马及其第一谐波始终保持特定的相位关系,从而形成具有明显的波谷和浅峰的独特形状。有趣的是,最近预测的威尔逊-考恩(WC)模型在抑制稳定模式下可以复制这种形状,但前提是抑制群体在超线性范围内运作。然而,另一个最近开发的线性驱动的随机噪声模型未能产生显著的谐波或观察到的形状。我们的结果对产生伽马振荡及其工作模式的模型施加了额外的约束。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db88/8880865/a492746e38c2/pcbi.1009886.g001.jpg

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