ReviewAnnual review of neuroscience2020
Computation Through Neural Population Dynamics.
Review in Annual review of neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 356 papers.
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Who cites it
356 citing papers in PubMed.
- Learning to infer transitively on a mental line in premotor cortex.Science advances · 2026Article
- Article
- Review
- Locus coeruleus activation transforms cortical taste representations.Cell reports · 2026Article
- Simulated field potentials capture multiple simultaneous processes underlying human temporal attention.bioRxiv : the preprint server for biology · 2026Article
- Flexible reorientation of conserved neural dynamics underlies grasp control.bioRxiv : the preprint server for biology · 2026Article
- Preparatory encoding of intended movement in the human motor cortex and implications for brain-computer interfaces.Current biology : CB · 2026Article
- Embedding of low-dimensional sensory dynamics in recurrent networks: Implications for the geometry of neural representation.Journal of computational neuroscience · 2026Article
- The compositionality continuum as a principle for studying the neural basis of intelligence.Nature neuroscience · 2026Review
- Task-Parametrized dynamics: Representation of time and decisions in recurrent neural networks.Journal of computational neuroscience · 2026Article
- Low-dimensional factorized neural computations underlie risk-adaptive choices.Research square · 2026Article
- Pretraining of Embodied Recurrent Networks Bridges the Gap Between Artificial and Cortical Neural Activities.Biomimetics (Basel, Switzerland) · 2026Article
- Shared neural geometries for bilingual semantic representations in human hippocampal neurons.Cell · 2026Article
- Feasible cognition requires latent state.Biological cybernetics · 2026Article
- Manifold-constrained plasticity enables stable learning in recurrent neural circuits.PLoS computational biology · 2026Article
- Decoding behavior with minimal and interpretable agent models.PLoS computational biology · 2026Article
- Review
- Data-driven reduced modeling of neural dynamics.Nature communications · 2026Article
- Signatures of Covert Neuron Loss in the Local Field Potential of Motor Cortex.Journal of the American Heart Association · 2026Article
- Entropy, Inhibition and Memory in Balanced Spiking Reservoirs.Entropy (Basel, Switzerland) · 2026Article
296 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
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Abstract
Significant experimental, computational, and theoretical work has identified rich structure within the coordinated activity of interconnected neural populations. An emerging challenge now is to uncover the nature of the associated computations, how they are implemented, and what role they play in driving behavior. We term this computation through neural population dynamics. If successful, this framework will reveal general motifs of neural population activity and quantitatively describe how neural population dynamics implement computations necessary for driving goal-directed behavior. Here, we start with a mathematical primer on dynamical systems theory and analytical tools necessary to apply this perspective to experimental data. Next, we highlight some recent discoveries resulting from successful application of dynamical systems. We focus on studies spanning motor control, timing, decision-making, and working memory. Finally, we briefly discuss promising recent lines of investigation and future directions for the computation through neural population dynamics framework.
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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.