小柯机器人

美国耶鲁大学医学院Michael J. Higley团队近期取得重要工作进展，他们研究发现，皮层网络功能连接的快速波动编码自发行为。相关研究成果2023年11月30日在线发表于《自然—神经科学》杂志上。

据介绍，跨物种的实验工作表明，自发产生的行为与大脑皮层内神经活动的变化密切相关。功能性磁共振成像数据表明，皮层网络中的时间相关性因不同的行为状态而异，从而提供了模式活动的动态重组。然而，这些数据通常缺乏时间分辨率，无法在皮层信号和清醒动物自发行为的连续变化波动之间建立联系。

研究人员使用宽场介观钙成像来监测清醒小鼠的皮层动力学，并开发了一种量化快速时变功能连接的方法。研究人员发现，自发行为表现为皮层网络活动的幅度和相关结构的快速变化。将介观成像与同时进行的细胞分辨率双光子显微镜相结合，证明了相邻神经元之间以及局部和大规模网络之间的相关性也对行为进行了编码。最后，中尺度信号的动态功能连接揭示了传统的基于解剖图谱的皮层分割所无法预测的子网络。

总之，这些结果为行为信息如何在新皮层中表达提供了新的见解，并展示了研究神经网络中时变功能连接的分析框架。

附：英文原文

Title: Rapid fluctuations in functional connectivity of cortical networks encode spontaneous behavior

Author: Benisty, Hadas, Barson, Daniel, Moberly, Andrew H., Lohani, Sweyta, Tang, Lan, Coifman, Ronald R., Crair, Michael C., Mishne, Gal, Cardin, Jessica A., Higley, Michael J.

Issue&Volume: 2023-11-30

Abstract: Experimental work across species has demonstrated that spontaneously generated behaviors are robustly coupled to variations in neural activity within the cerebral cortex. Functional magnetic resonance imaging data suggest that temporal correlations in cortical networks vary across distinct behavioral states, providing for the dynamic reorganization of patterned activity. However, these data generally lack the temporal resolution to establish links between cortical signals and the continuously varying fluctuations in spontaneous behavior observed in awake animals. Here, we used wide-field mesoscopic calcium imaging to monitor cortical dynamics in awake mice and developed an approach to quantify rapidly time-varying functional connectivity. We show that spontaneous behaviors are represented by fast changes in both the magnitude and correlational structure of cortical network activity. Combining mesoscopic imaging with simultaneous cellular-resolution two-photon microscopy demonstrated that correlations among neighboring neurons and between local and large-scale networks also encode behavior. Finally, the dynamic functional connectivity of mesoscale signals revealed subnetworks not predicted by traditional anatomical atlas-based parcellation of the cortex. These results provide new insights into how behavioral information is represented across the neocortex and demonstrate an analytical framework for investigating time-varying functional connectivity in neural networks.

DOI: 10.1038/s41593-023-01498-y

Source: https://www.nature.com/articles/s41593-023-01498-y

Nature Neuroscience：《自然—神经科学》，创刊于1998年。隶属于施普林格·自然出版集团，最新IF：28.771
官方网址：https://www.nature.com/neuro/
投稿链接：https://mts-nn.nature.com/cgi-bin/main.plex