Wang Zezhen, Mai Weihao, Chai Yuming, Qi Kexin, Ren Hongtai, Shen Chen, Zhang Shiwu, Tan Guodong, Hu Yu, Wen Quan
School of Data Science, University of Science and Technology of China, Hefei, China.
Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, China.
Elife. 2025 Jun 23;14:RP100666. doi: 10.7554/eLife.100666.
Understanding neural activity organization is vital for deciphering brain function. By recording whole-brain calcium activity in larval zebrafish during hunting and spontaneous behaviors, we find that the shape of the neural activity space, described by the neural covariance spectrum, is scale-invariant: a smaller, cell assembly resembles the entire brain. This phenomenon can be explained by Euclidean Random Matrix theory, where neurons are reorganized from anatomical to functional positions based on their correlations. Three factors contribute to the observed scale invariance: slow neural correlation decay, higher functional space dimension, and neural activity heterogeneity. In addition to matching data from zebrafish and mice, our theory and analysis demonstrate how the geometry of neural activity space evolves with population sizes and sampling methods, thus revealing an organizing principle of brain-wide activity.
理解神经活动组织对于解读脑功能至关重要。通过记录幼体斑马鱼在捕食和自发行为期间的全脑钙活动,我们发现由神经协方差谱描述的神经活动空间的形状是尺度不变的:一个较小的细胞集合类似于整个大脑。这种现象可以用欧几里得随机矩阵理论来解释,其中神经元根据它们的相关性从解剖位置重新组织到功能位置。三个因素促成了观察到的尺度不变性:缓慢的神经相关性衰减、更高的功能空间维度和神经活动异质性。除了与来自斑马鱼和小鼠的数据相匹配外,我们的理论和分析还展示了神经活动空间的几何结构如何随着群体规模和采样方法而演变,从而揭示了全脑活动的组织原则。