ArticleeLife2017
Cell assemblies at multiple time scales with arbitrary lag constellations.
Article in eLife, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Bad habits-good goals? Meta-analysis and translation of the habit construct to alcoholism.Translational psychiatry · 2024Pooled it
- Neurons embedded in loop-like motifs act as central hubs for brain-wide integration.The Journal of physiology · 2026Article
- Direction of motion decoding in mouse V1: Neuron predictive power relates to functional connectivity organization.bioRxiv : the preprint server for biology · 2025Article
- Out of the single-neuron straitjacket: Neurons within assemblies change selectivity and their reconfiguration underlies dynamic coding.The Journal of physiology · 2025Article
- Improving data sharing and knowledge transfer via the Neuroelectrophysiology Analysis Ontology (NEAO).Scientific data · 2025Article
- Anesthesia alters complexity of spontaneous and stimulus-related neuronal firing patterns in rat visual cortex.Neuroscience · 2025Article
- Lattice physics approaches for neural networks.iScience · 2024Review
- Integration of rate and phase codes by hippocampal cell-assemblies supports flexible encoding of spatiotemporal context.Nature communications · 2024Article
- Brain orchestra under spontaneous conditions: Identifying communication modules from the functional architecture of area V1.bioRxiv : the preprint server for biology · 2024Article
- Connecting the dots in the zona incerta: A study of neural assemblies and motifs of inter-area coordination in mice.iScience · 2024Article
- Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture Models.Journal of the American Statistical Association · 2024Article
- Reconstructing computational system dynamics from neural data with recurrent neural networks.Nature reviews. Neuroscience · 2023Review
- SpikeShip: A method for fast, unsupervised discovery of high-dimensional neural spiking patterns.PLoS computational biology · 2023Article
- Third-order motifs are sufficient to fully and uniquely characterize spatiotemporal neural network activity.Scientific reports · 2023Article
- Adaptive control of synaptic plasticity integrates micro- and macroscopic network function.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023Review
- Precise Spiking Motifs in Neurobiological and Neuromorphic Data.Brain sciences · 2022Review
- From ensembles to meta-ensembles: Specific reward encoding by correlated network activity.Frontiers in behavioral neuroscience · 2022Review
- Formalizing planning and information search in naturalistic decision-making.Nature neuroscience · 2021Review
- Spontaneous activity competes with externally evoked responses in sensory cortex.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Scalable and accurate method for neuronal ensemble detection in spiking neural networks.PloS one · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hebb's idea of a cell assembly as the fundamental unit of neural information processing has dominated neuroscience like no other theoretical concept within the past 60 years. A range of different physiological phenomena, from precisely synchronized spiking to broadly simultaneous rate increases, has been subsumed under this term. Yet progress in this area is hampered by the lack of statistical tools that would enable to extract assemblies with arbitrary constellations of time lags, and at multiple temporal scales, partly due to the severe computational burden. Here we present such a unifying methodological and conceptual framework which detects assembly structure at many different time scales, levels of precision, and with arbitrary internal organization. Applying this methodology to multiple single unit recordings from various cortical areas, we find that there is no universal cortical coding scheme, but that assembly structure and precision significantly depends on the brain area recorded and ongoing task demands.
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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.