ArticleNeuron2022
Metastable attractors explain the variable timing of stable behavioral action sequences.
Article in Neuron, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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47 citing papers in PubMed.
- Sharp and smooth state transitions during resting state brain dynamics.bioRxiv : the preprint server for biology · 2026Article
- Pretraining of Embodied Recurrent Networks Bridges the Gap Between Artificial and Cortical Neural Activities.Biomimetics (Basel, Switzerland) · 2026Article
- A claustro-cortical loop times state transitions for flexible behavior.Research square · 2026Article
- Decoding behavior with minimal and interpretable agent models.PLoS computational biology · 2026Article
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- Nonuniform spike count shared variability in the mouse early visual system.Journal of neurophysiology · 2026Article
- A brain-wide, trial- and time-dependent deterministic drive synergizes with within-trial noise to time self-initiated actions.bioRxiv : the preprint server for biology · 2026Article
- A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Designing Neural Dynamics: From Digital Twin Modeling to Regeneration.International journal of molecular sciences · 2025Review
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- A sticky Poisson Hidden Markov Model for solving the problem of over-segmentation and rapid state switching in cortical datasets.bioRxiv : the preprint server for biology · 2025Article
- Balanced state of networks of winner-take-all units.PLoS computational biology · 2025Article
- A non-Hebbian code for episodic memory.Science advances · 2025Article
- Deciphering neuronal variability across states reveals dynamic sensory encoding.Nature communications · 2025Article
- A sticky Poisson Hidden Markov Model for solving the problem of over-segmentation and rapid state switching in cortical datasets.PloS one · 2025Article
- Cortex-wide spatiotemporal motifs of theta oscillations are coupled to freely moving behavior.Frontiers in systems neuroscience · 2025Article
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- Hierarchical behavior control by a single class of interneurons.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Mesoscale neuronal granular trial variability in vivo illustrated by nonlinear recurrent network in silico.Nature communications · 2024Article
- Dopamine builds and reveals reward-associated latent behavioral attractors.Nature communications · 2024Article
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Abstract
The timing of self-initiated actions shows large variability even when they are executed in stable, well-learned sequences. Could this mix of reliability and stochasticity arise within the same neural circuit? We trained rats to perform a stereotyped sequence of self-initiated actions and recorded neural ensemble activity in secondary motor cortex (M2), which is known to reflect trial-by-trial action-timing fluctuations. Using hidden Markov models, we established a dictionary between activity patterns and actions. We then showed that metastable attractors, representing activity patterns with a reliable sequential structure and large transition timing variability, could be produced by reciprocally coupling a high-dimensional recurrent network and a low-dimensional feedforward one. Transitions between attractors relied on correlated variability in this mesoscale feedback loop, predicting a specific structure of low-dimensional correlations that were empirically verified in M2 recordings. Our results suggest a novel mesoscale network motif based on correlated variability supporting naturalistic animal behavior.
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