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Updated: Apr 24, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
The geometry and dimensionality of brain-wide activity
Zezhen Wang1, Weihao Mai2, Yuming Chai3,4
1School of Data Science, University of Science and Technology of China, Hefei, China.
None:
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, randomly sampled 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.
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