ArticleJournal of neurophysiology2020
Frequency-separated principal component analysis of cortical population activity.
Article in Journal of neurophysiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Disentangling Stimulus & Population Dynamics in Mouse V1: Orthogonal Subspace Decomposition for Neural Representation.bioRxiv : the preprint server for biology · 2025Article
- A deep generative adversarial network capturing complex spiral waves in disinhibited circuits of the cerebral cortex.BMC neuroscience · 2023Article
- Estimating null and potent modes of feedforward communication in a computational model of cortical activity.Scientific reports · 2022Article
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Abstract
A hallmark of neocortical activity is the presence of low-dimensional fluctuations in firing rate that are coordinated across neurons. However, the impact of these fluctuations on sensory processing remains unclear. Here, we examined fluctuations in populations of orientation-selective neurons from anesthetized macaque primary visual cortex (V1) during stimulus viewing as well as spontaneous activity. We introduce a novel approach termed frequency-separated principal component analysis (FS-PCA) to characterize these fluctuations. This method unveiled a distribution of components with a broad range of frequencies whose eigenvalues and variance followed an approximate power law. During stimulus viewing, subpopulations of V1 neurons correlated either positively or negatively with low-dimensional fluctuations. These two subpopulations displayed distinct activation properties and noise correlations in response to sensory input. Together, results suggest that slow, low-dimensional fluctuations in V1 population activity shape the response of individual neurons to oriented stimuli and may impact the transmission of sensory information to downstream regions of the primary visual system.
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