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Geometry of spiking patterns in early visual cortex: a topological data analytic approach
- Source :
- Journal of the Royal Society Interface, Journal of the Royal Society Interface, 2022, 19 (196), ⟨10.1098/rsif.2022.0677⟩
- Publication Year :
- 2023
-
Abstract
- In the brain, spiking patterns live in a high-dimensional space of neurons and time. Thus, determining the intrinsic structure of this space presents a theoretical and experimental challenge. To address this challenge, we introduce a new framework for applying topological data analysis (TDA) to spike train data and use it to determine the geometry of spiking patterns in the visual cortex. Key to our approach is a parametrized family of distances based on the timing of spikes that quantifies the dissimilarity between neuronal responses. We applied TDA to visually driven single-unit and multiple single-unit spiking activity in macaque V1 and V2. TDA across timescales reveals a common geometry for spiking patterns in V1 and V2 which, among simple models, is most similar to that of a low-dimensional space endowed with Euclidean or hyperbolic geometry with modest curvature. Remarkably, the inferred geometry depends on timescale and is clearest for the timescales that are important for encoding contrast, orientation and spatial correlations.<br />NIH grants number EY09314 and EY07977 from the National Eye Institute of the NIH. NIH grants no. EY034150 from the National Eye Institute and NS111019 from the National Institute of Neurological Disorders and Stroke. Ikerbasque. Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation. Inria Associated Team "NeuroTransSF".
- Subjects :
- Neurons
Quantitative Biology::Neurons and Cognition
[SCCO.NEUR]Cognitive science/Neuroscience
[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS]
Data Science
Biomedical Engineering
Biophysics
Action Potentials
Bioengineering
Biochemistry
persistent homology
Biomaterials
topological data analysis
spike metric
Animals
Macaca
Photic Stimulation
Biotechnology
Visual Cortex
Subjects
Details
- ISSN :
- 17425662 and 17425689
- Volume :
- 19
- Issue :
- 196
- Database :
- OpenAIRE
- Journal :
- Journal of the Royal Society, Interface
- Accession number :
- edsair.doi.dedup.....ed63856d9d59945a145b734d0c3803ce