英国伦敦大学R. Angus Silver团队取得一项新成果。经过不懈努力，他们的研究发现小脑颗粒细胞(GrC)轴突支持高维表征。2021年6月24日出版的《自然-神经科学》杂志发表了这项成果。
为了从下游浦肯野细胞“解码器”的角度描绘感觉运动表征，研究人员使用三维双光子激光显微镜记录数百个GrC轴突。
研究发现GrC轴突细胞群活动是高维的，并且在自发行为期间几乎没有精细的空间结构分布。并且沿神经元活动空间中的正交维度表示不同的行为状态。
这些结果表明小脑皮层支持高维表征并将行为状态相关的计算分离到正交子空间中，如新皮层。该发现与小脑模式分离理论的预测相符合，并表明尽管小脑和新皮层的回路结构截然不同但都使用具有共同特征的通用解码。
据介绍，经典的小脑皮层理论认为高维感觉运动表征用于分离神经元活动模式，从而改善联想学习和运动性能。最近的实验研究表明小脑颗粒细胞群调控低维表征。
附：英文原文
Title: Cerebellar granule cell axons support high-dimensional representations
Author: Frederic Lanore, N. Alex Cayco-Gajic, Harsha Gurnani, Diccon Coyle, R. Angus Silver
Issue&Volume: 2021-06-24
Abstract: In classical theories of cerebellar cortex, high-dimensional sensorimotor representations are used to separate neuronal activity patterns, improving associative learning and motor performance. Recent experimental studies suggest that cerebellar granule cell (GrC) population activity is low-dimensional. To examine sensorimotor representations from the point of view of downstream Purkinje cell ‘decoders’, we used three-dimensional acousto-optic lens two-photon microscopy to record from hundreds of GrC axons. Here we show that GrC axon population activity is high dimensional and distributed with little fine-scale spatial structure during spontaneous behaviors. Moreover, distinct behavioral states are represented along orthogonal dimensions in neuronal activity space. These results suggest that the cerebellar cortex supports high-dimensional representations and segregates behavioral state-dependent computations into orthogonal subspaces, as reported in the neocortex. Our findings match the predictions of cerebellar pattern separation theories and suggest that the cerebellum and neocortex use population codes with common features, despite their vastly different circuit structures.
DOI: 10.1038/s41593-021-00873-x
Source: https://www.nature.com/articles/s41593-021-00873-x
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
本期文章：《自然—神经科学》：Online/在线发表
