ArticleNature computational science2022
Disentangling the flow of signals between populations of neurons.
Article in Nature computational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 43 citations in OpenAlex.
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- Input-dependent directionality of interactions between cortical areas.bioRxiv : the preprint server for biology · 2026Article
- Decomposing the modulation of interactions between neuronal populations.bioRxiv : the preprint server for biology · 2026Article
- Interactions across hemispheres in prefrontal cortex reflect global cognitive processing.Nature communications · 2026Article
- Shared somatosensory-motor neural population dynamics track motor recovery after stroke.bioRxiv : the preprint server for biology · 2026Article
- Cross-population amplitude coupling in high-dimensional oscillatory neural time series.Frontiers in computational neuroscience · 2026Article
- When predict can also explain: Few-shot prediction to select better neural latents.PLoS computational biology · 2025Article
- Interactions between motor cortical forelimb regions and their influence on muscles reorganize across behaviors.Nature communications · 2025Article
- Disentangling Stimulus & Population Dynamics in Mouse V1: Orthogonal Subspace Decomposition for Neural Representation.bioRxiv : the preprint server for biology · 2025Article
- No Central Executive? Decision Formation Through Multi-Area Population Dynamics.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Review
- Inpainting the Neural Picture: Inferring Unrecorded Brain Area Dynamics from Multi-Animal Datasets.ArXiv · 2025Article
- Accurate Identification of Communication Between Multiple Interacting Neural Populations.ArXiv · 2025Article
- Global and local origins of trial-to-trial spike count variability in visual cortex.bioRxiv : the preprint server for biology · 2025Article
- Prioritized learning of cross-population neural dynamics.Journal of neural engineering · 2025Article
- Fast Multigroup Gaussian Process Factor Models.Neural computation · 2025Article
- Measuring Stimulus Information Transfer Between Neural Populations Through the Communication Subspace.Neural computation · 2025Article
- Accurate Identification of Communication Between Multiple Interacting Neural Populations.Proceedings of machine learning research · 2025Article
- Interactions across hemispheres in prefrontal cortex reflect global cognitive processing.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
Technological advances now allow us to record from large populations of neurons across multiple brain areas. These recordings may illuminate how communication between areas contributes to brain function, yet a substantial barrier remains: how do we disentangle the concurrent, bidirectional flow of signals between populations of neurons? We propose here a dimensionality reduction framework, delayed latents across groups (DLAG), that disentangles signals relayed in each direction, identifies how these signals are represented by each population and characterizes how they evolve within and across trials. We demonstrate that DLAG performs well on synthetic datasets similar in scale to current neurophysiological recordings. Then we study simultaneously recorded populations in primate visual areas V1 and V2, where DLAG reveals signatures of bidirectional yet selective communication. Our framework lays a foundation for dissecting the intricate flow of signals across populations of neurons, and how this signalling contributes to cortical computation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.