ArticleNeuron2023
Learning shapes cortical dynamics to enhance integration of relevant sensory input.
Article in Neuron, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Data-driven reduced modeling of neural dynamics.Nature communications · 2026Article
- Task learning increases information redundancy of neural responses in macaque visual cortex.Science (New York, N.Y.) · 2026Article
- Article
- Short-term memory errors are strongly associated with a drift in neural activity in the posterior parietal cortex.PLoS biology · 2025Article
- Coordinated multi-level adaptations across neocortical areas during task learning.Nature communications · 2025Article
- Balanced state of networks of winner-take-all units.PLoS computational biology · 2025Article
- Auditory cortex learns to discriminate audiovisual cues through selective multisensory enhancement.eLife · 2025Article
- Article
- Interdigitating Modules for Visual Processing During Locomotion and Rest in Mouse V1.bioRxiv : the preprint server for biology · 2025Article
- Article
- Inferring context-dependent computations through linear approximations of prefrontal cortex dynamics.Science advances · 2024Article
- Flexible neural population dynamics govern the speed and stability of sensory encoding in mouse visual cortex.Nature communications · 2024Article
- Orthogonality of sensory and contextual categorical dynamics embedded in a continuum of responses from the second somatosensory cortex.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Dimensionality reduction beyond neural subspaces with slice tensor component analysis.Nature neuroscience · 2024Article
- Optimal information loading into working memory explains dynamic coding in the prefrontal cortex.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Adaptive sensory behavior is thought to depend on processing in recurrent cortical circuits, but how dynamics in these circuits shapes the integration and transmission of sensory information is not well understood. Here, we study neural coding in recurrently connected networks of neurons driven by sensory input. We show analytically how information available in the network output varies with the alignment between feedforward input and the integrating modes of the circuit dynamics. In light of this theory, we analyzed neural population activity in the visual cortex of mice that learned to discriminate visual features. We found that over learning, slow patterns of network dynamics realigned to better integrate input relevant to the discrimination task. This realignment of network dynamics could be explained by changes in excitatory-inhibitory connectivity among neurons tuned to relevant features. These results suggest that learning tunes the temporal dynamics of cortical circuits to optimally integrate relevant sensory input.
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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.