Suppr超能文献

揭示眶额皮质高频γ中信息编码的时空动态

Spatiotemporal dynamics of information encoding revealed in orbitofrontal high-gamma.

机构信息

Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA, 94720, USA.

Friedman Brain Institute and Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

出版信息

Nat Commun. 2017 Oct 26;8(1):1139. doi: 10.1038/s41467-017-01253-5.

Abstract

High-gamma signals mirror the tuning and temporal profiles of neurons near a recording electrode in sensory and motor areas. These frequencies appear to aggregate local neuronal activity, but it is unclear how this relationship affects information encoding in high-gamma activity (HGA) in cortical areas where neurons are heterogeneous in selectivity and temporal responses, and are not functionally clustered. Here we report that populations of neurons and HGA recorded from the orbitofrontal cortex (OFC) encode similar information, although there is little correspondence between signals recorded by the same electrode. HGA appears to aggregate heterogeneous neuron activity, such that the spiking of a single cell corresponds to only small increases in HGA. Interestingly, large-scale spatiotemporal dynamics are revealed in HGA, but less apparent in the population of single neurons. Overall, HGA is closely related to neuron activity in OFC, and provides a unique means of studying large-scale spatiotemporal dynamics of information processing.

摘要

高伽马信号反映了感觉和运动区域中记录电极附近神经元的调谐和时间分布。这些频率似乎聚集了局部神经元活动,但尚不清楚这种关系如何影响皮质区域中高伽马活动(HGA)的信息编码,在这些区域中,神经元在选择性和时间响应方面存在异质性,并且没有功能聚类。在这里,我们报告说,从眶额皮质(OFC)记录的神经元群体和 HGA 编码相似的信息,尽管同一电极记录的信号之间几乎没有对应关系。HGA 似乎聚集了异质神经元活动,使得单个细胞的尖峰只对应于 HGA 的小幅度增加。有趣的是,HGA 中揭示了大规模的时空动态,但在单个神经元的群体中则不太明显。总的来说,HGA 与 OFC 中的神经元活动密切相关,并为研究信息处理的大规模时空动态提供了一种独特的手段。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3321/5658402/c67d7dd31f8e/41467_2017_1253_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验