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Slow Cortical Dynamics and the Accumulation of Information over Long Timescales
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Making sense of the world requires us to process information over multiple timescales. We sought to identify brain regions that accumulate information over short and long timescales and to characterize the distinguishing features of their dynamics. We recorded electrocorticographic (ECoG) signals from individuals watching intact and scrambled movies. Within sensory regions, fluctuations of high-frequency (64-200 Hz) power reliably tracked instantaneous low-level properties of the intact and scrambled movies. Within higher order regions, the power fluctuations were more reliable for the intact movie than the scrambled movie, indicating that these regions accumulate information over relatively long time periods (several seconds or longer). Slow (<0.1 Hz) fluctuations of high-frequency power with time courses locked to the movies were observed throughout the cortex. Slow fluctuations were relatively larger in regions that accumulated information over longer time periods, suggesting a connection between slow neuronal population dynamics and temporally extended information processing.
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“this topography has previously been mapped either by temporally scrambling the stimulus at different timescales to see which regions’ responses are disrupted (Hasson, Yang, Vallines, Heeger, & Rubin, 2008; Honey et al., 2012; Lerner, Honey, Silbert, & Hasson, 2011) or by examining the power spectrum of intrinsic dynamics within each region (Honey et al., 2012; Murray et al., 2014; Stephens et al.,”
From Discovering Event Structure in Continuous Narrative Perception and Memory (2017) · cites this paper as Honey et al., 2012
In the citing paper
“The topographical hierarchy of processing timescales along the cortical surface (2) has been supported and replicated across methodologies, including single-unit analysis (4), electrocorticography analysis (7), fMRI analysis (5, 6, 25), magnetoencephalography analysis (1), computational models (3), and resting state functional connectivity (30, 31).”
From Amplification of local changes along the timescale processing hierarchy (2017) · cites this paper as [7]
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“Previous work has suggested that long-TRW areas have intrinsically slower neural dynamics compared with short-TRW areas, and that these slower cortical dynamics may be related to an area’s ability to accumulate information over time (7, 8).”
From Amplification of local changes along the timescale processing hierarchy (2017) · cites this paper as [7]
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Buccellato, A., Çatal, Y., Bisiacchi, P., Zang, D., Zilio, F., Wang, Z., Qi, Z.-X., Zheng, R., Xu, Z.-Y., Wu, X., et al. (2023) · Entropy · doi:10.3390/e25071086 · Cited by 3
Intrinsic Neural Timescales Relate to Event-Related Activity—Key Role for Intracolumnar Connections
Çatal, Y., Wolman, A., Buccellato, A., Keskin, K., & Northoff, G. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.0896-25.2025 · Cited by 3
Golemme, M., Tatti, E., Luft, C. D. B., Bhattacharya, J., Ruiz, M. H., & Cappelletti, M. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15486 · Cited by 4
Inference, validation and predictions about statistics and propagation of cortical spiking in vivoPreprint
Wilting, J., & Priesemann, V. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/363085 · Cited by 3
Xie, T., Cheong, J. H., Manning, J. R., Brandt, A. M., Aronson, J. P., Jobst, B. C., Bujarski, K. A., & Chang, L. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.10.443308 · Cited by 3
Nee, D. E., & D’Esposito, M. (2018) · Wiley eBooks · doi:10.1002/9781119170174.epcn112 · Cited by 3
A unifying computational account of temporal context effects in language across the human cortexPreprint
Vo, V. A., Jain, S., Beckage, N., Chien, H.-Y. S., Obinwa, C., & Huth, A. G. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.03.551886 · Cited by 5
Hoffman, S. J., Dotson, N. M., Lima, V., & Gray, C. M. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.29.577843 · Cited by 3
Strategies for motion- and respiration-robust estimation of fMRI intrinsic neural timescales
Goldberg, A., Rosario, I., Power, J. D., Horga, G., & Wengler, K. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00326 · Cited by 2
From Speech Semantics to Brain Activity—Timescales Are Key in Their Information Transfer
Kumar, S., Klar, P., Çatal, Y., Chang, H., Friedemann Pulvermüller, A., & Northoff, G. (2025) · Human Brain Mapping · doi:10.1002/hbm.70379 · Cited by 1
Miles, J. T., Weaver, K. E., Webb, S. J., & Ojemann, J. G. (2025) · Journal of Neurophysiology · doi:10.1152/jn.00435.2025 · Cited by 2
Wang, X., Lyu, B., Krieger‐Redwood, K., Souter, N. E., Shafiei, G., Lin, N., Smallwood, J., Jefferies, E., & Du, Y. (2025) · Communications Biology · doi:10.1038/s42003-025-09165-7 · Cited by 2
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Comprehensive profiling of brain dynamics during anesthesia across phylogeny
Luppi, A. I., Uhrig, L., Tasserie, J., Shafiei, G., Légaré, A., Muta, K., Hata, J., Okano, H., Golkowski, D., Ranft, A., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02460-4 · Cited by 6
Metadata
- Authors
- Honey, C. J., Thesen, T., Donner, T. H., Silbert, L. J., Carlson, C. E., Devinsky, O., Doyle, W. K., Rubin, N., Heeger, D. J., & Hasson, U.
- Affiliations
- Princeton University (US)
- New York University (US)
- University of Amsterdam (NL)
- Corresponding author
- Honey, Christopher J.
- ORCID
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2012-10
- Volume
- 76
- Issue
- 2
- Pages
- 423-434
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC3517908
- OpenAlex
- W2152009360
- Cited by
- 532
- References
- 73
- Citations by year
- 2026: 52 · 2025: 50 · 2024: 56 · 2023: 56 · 2022: 53 · 2021: 47 · 2020: 48 · 2019: 36 · 2018: 36 · 2017: 37 · 2016: 20 · 2015: 18 · 2014: 15 · 2013: 7
- FWCI
- 6.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- National Institute of Mental Health (R01MH094480)
- National Institute on Drug Abuse (R21DA024423)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- information accumulation, electrocorticography, sensory processing, higher-order visual processing, film viewing, neural population dynamics, temporal integration
- MeSH terms
- Acoustic Stimulation, Adult, Brain Mapping, Cerebral Cortex, Electrodes, Electroencephalography, Female, Humans, Male, Mental Processes, Middle Aged, Photic Stimulation, Reaction Time, Spectrum Analysis, Time Factors, Reproducibility of Results, Epilepsy, Complex Partial, Young Adult, Brain Waves
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.
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