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Synfire Chains and Cortical Songs: Temporal Modules of Cortical Activity
Abstract
How can neural activity propagate through cortical networks built with weak, stochastic synapses? We find precise repetitions of spontaneous patterns of synaptic inputs in neocortical neurons in vivo and in vitro. These patterns repeat after minutes, maintaining millisecond accuracy. Calcium imaging of slices reveals reactivation of sequences of cells during the occurrence of repeated intracellular synaptic patterns. The spontaneous activity drifts with time, engaging different cells. Sequences of active neurons have distinct spatial structures and are repeated in the same order over tens of seconds, revealing modular temporal dynamics. Higher order sequences are replayed with compressed timing.
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“Repeated spontaneous activation of neuron assemblies does occur106,107”
From The right time to learn: Mechanisms and optimization of spaced learning (2016) · cites this paper as [106]
Citations
Cites
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
Maass, W., Natschläger, T., & Markram, H. (2002) · Neural Computation · doi:10.1162/089976602760407955 · Cited by 4,025
Cellular basis of working memory
Goldman-Rakic, P. S. (1995) · Neuron · doi:10.1016/0896-6273(95)90304-6 · Cited by 2,663
Llinás, R. R. (1988) · Science · doi:10.1126/science.3059497 · Cited by 2,285
Synaptic depression and cortical gain control
Abbott, L. F., Varela, J. A., Sen, K., & Nelson, S. B. (1997) · Science · doi:10.1126/science.275.5297.221 · Cited by 1,690
Abeles, M. (1991) · Cambridge University Press eBooks · doi:10.1017/cbo9780511574566 · Cited by 1,341
Replay of neuronal firing sequences in rat hippocampus during sleep following spatial experience
Skaggs, W. E., & McNaughton, B. L. (1996) · Science · doi:10.1126/science.271.5257.1870 · Cited by 1,173
Temporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep
Louie, K., & Wilson, M. A. (2001) · Neuron · doi:10.1016/s0896-6273(01)00186-6 · Cited by 1,148
Synaptic reverberation underlying mnemonic persistent activity
Wang, X.-J. (2001) · Trends in Neurosciences · doi:10.1016/s0166-2236(00)01868-3 · Cited by 1,059
Turning on and off recurrent balanced cortical activity
Shu, Y., Hasenstaub, A., & McCormick, D. A. (2003) · Nature · doi:10.1038/nature01616 · Cited by 1,054
Flagged first, then by citations
1 of the 34 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- L. F. Abbottet al., Science275, 220 (1997).
- W. Maass, T. Natschlager, H. Markram, Neural Comput.14, 2531 (2003).
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Metadata
- Authors
- Ikegaya, Y., Aaron, G., Cossart, R., Aronov, D., Lampl, I., Ferster, D., & Yuste, R.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Ikegaya, Yuji
- Aaron, Gloster
- Yuste, Rafael
- Venue
- Science
- Published
- 2004-04-23
- Volume
- 304
- Issue
- 5670
- Pages
- 559-564
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2064869244
- Cited by
- 838
- References
- 34
- Citations by year
- 2026: 11 · 2025: 17 · 2024: 20 · 2023: 33 · 2022: 26 · 2021: 26 · 2020: 24 · 2019: 49 · 2018: 21 · 2017: 24 · 2016: 42 · 2015: 43 · 2014: 39 · 2013: 50 · 2012: 41
- FWCI
- 27.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- synfire chains, spontaneous neuronal activity, neocortical neurons, calcium imaging, temporal dynamics, stochastic synapses
- MeSH terms
- Action Potentials, Animals, Benzazepines, Calcium, Cats, Mice, Inbred C57BL, Nerve Net, Synaptic Transmission, Neurons, Synapses, Time Factors, Visual Cortex, 2,3,4,5-Tetrahydro-7,8-dihydroxy-1-phenyl-1H-3-benzazepine, 2-Amino-5-phosphonovalerate, Receptors, N-Methyl-D-Aspartate, Prefrontal Cortex, Receptors, Dopamine D1, Pyramidal Cells, Patch-Clamp Techniques, Microscopy, Confocal, Excitatory Postsynaptic Potentials, Mice, In Vitro Techniques
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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