ArticleiScience2024
Topological structure of population activity in mouse visual cortex encodes densely sampled stimulus rotations.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- How 'Neural' is a Neural Foundation Model?ArXiv · 2026Article
- Designing Neural Dynamics: From Digital Twin Modeling to Regeneration.International journal of molecular sciences · 2025Review
- Relationships between the degrees of freedom in the affine Gaussian derivative model for visual receptive fields and 2-D affine image transformations with application to covariance properties of simple cells in the primary visual cortex.Biological cybernetics · 2025Article
- Coherently remapping toroidal cells but not Grid cells are responsible for path integration in virtual agents.iScience · 2023Article
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Authors and funding
4 authors.
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Abstract
The primary visual cortex is one of the most well understood regions supporting the processing involved in sensory computation. Following the popularization of high-density neural recordings, it has been observed that the activity of large neural populations is often constrained to low dimensional manifolds. In this work, we quantify the structure of such neural manifolds in the visual cortex. We do this by analyzing publicly available two-photon optical recordings of mouse primary visual cortex in response to visual stimuli with a densely sampled rotation angle. Using a geodesic metric along with persistent homology, we discover that population activity in response to such stimuli generates a circular manifold, encoding the angle of rotation. Furthermore, we observe that this circular manifold is expressed differently in subpopulations of neurons with differing orientation and direction selectivity. Finally, we discuss some of the obstacles to reliably retrieving the truthful topology generated by a neural population.
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