ArticlePLoS computational biology2019
Bayesian inference of neuronal assemblies.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- The neurobiology of functional neurological disorders characterised by impaired awareness.Frontiers in psychiatry · 2023Pooled it
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- Synergy mediates long-range correlations in the visual cortex near criticality.Frontiers in computational neuroscience · 2026Article
- Synergy mediates Long-Range Correlations in the Visual Cortex Near Criticality.bioRxiv : the preprint server for biology · 2025Article
- Topological analysis of neuronal assemblies reveals low-rank structure modulated by cholinergic activity.bioRxiv : the preprint server for biology · 2025Article
- Microscale Neuronal Activity Collectively Drives Chaotic and Inflexible Dynamics at the Macroscale in Seizures.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Recurrent network interactions explain tectal response variability and experience-dependent behavior.eLife · 2023Article
- Article
- To deconvolve, or not to deconvolve: Inferences of neuronal activities using calcium imaging data.Journal of neuroscience methods · 2022Article
- CNS Hypomyelination Disrupts Axonal Conduction and Behavior in Larval Zebrafish.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Integrated OMICs unveil the bone-marrow microenvironment in human leukemia.Cell reports · 2021Article
- Acceleration of the SPADE Method Using a Custom-Tailored FP-Growth Implementation.Frontiers in neuroinformatics · 2021Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
In many areas of the brain, both spontaneous and stimulus-evoked activity can manifest as synchronous activation of neuronal assemblies. The characterization of assembly structure and dynamics provides important insights into how brain computations are distributed across neural networks. The proliferation of experimental techniques for recording the activity of neuronal assemblies calls for a comprehensive statistical method to describe, analyze and characterize these high dimensional datasets. The performance of existing methods for defining assemblies is sensitive to noise and stochasticity in neuronal firing patterns and assembly heterogeneity. To address these problems, we introduce a generative hierarchical model of synchronous activity to describe the organization of neurons into assemblies. Unlike existing methods, our analysis provides a simultaneous estimation of assembly composition, dynamics and within-assembly statistical features, such as the levels of activity, noise and assembly synchrony. We have used our method to characterize population activity throughout the tectum of larval zebrafish, allowing us to make statistical inference on the spatiotemporal organization of tectal assemblies, their composition and the logic of their interactions. We have also applied our method to functional imaging and neuropixels recordings from the mouse, allowing us to relate the activity of identified assemblies to specific behaviours such as running or changes in pupil diameter.
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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.