Spontaneous Fluctuations and Non-linear Ignitions: Two Dynamic Faces of Cortical Recurrent Loops
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Recent human neurophysiological recordings have uncovered two fundamental modes of cerebral cortex activity with distinct dynamics: an active mode characterized by a rapid and sustained activity ("ignition") and a spontaneous (resting-state) mode, manifesting ultra-slow fluctuations of low amplitude. We propose that both dynamics reflect two faces of the same recurrent loop mechanism: an integration device that accumulates ongoing stochastic activity and, either spontaneously or in a task-driven manner, crosses a dynamic threshold and ignites, leading to content-specific awareness. The hypothesis can explain a rich set of behavioral and neuronal phenomena, such as perceptual threshold, the high non-linearity of visual responses, the subliminal nature of spontaneous activity fluctuations, and the slow activity buildup anticipating spontaneous behavior (e.g., readiness potential). Further elaborations of this unified scheme, such as a cascade of integrators with different ignition thresholds or multi-stable states, can account for additional complexities in the repertoire of human cortical dynamics.
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Self-citationWyart, V., Dehaene, S., & Tallon-Baudry, C. (2012) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00016 · Cited by 61 · see citing works
Self-citationStimulus-free thoughts induce differential activation in the human default network
Preminger, S., Harmelech, T., & Malach, R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.036 · Cited by 59 · see citing works
Self-citationGao, Z., Goldstein, A., Harpaz, Y., Hansel, M., Golumbic, E. Z., & Shlomo Bentin, A. (2012) · Human Brain Mapping · doi:10.1002/hbm.22028 · Cited by 58 · see citing works
Aly, M., & Yonelinas, A. P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030231 · Cited by 58 · see citing works
Douglas, Z. H., Maniscalco, B., Hallett, M., Wassermann, E. M., & He, B. J. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4894-14.2015 · Cited by 51 · see citing works
Arcaro, M. J., Honey, C. J., Mruczek, R. E. B., Kästner, S., & Hasson, U. (2015) · eLife · doi:10.7554/elife.03952 · Cited by 51 · see citing works
Sekar, K., Findley, W. M., Poeppel, D., & Llinás, R. R. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1302229110 · Cited by 48 · see citing works
Targeting the functional properties of cortical neurons using fMR-adaptation
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Self-citationZhang, Z., & Sun, Q. (2011) · International review of neurobiology · doi:10.1016/b978-0-12-385198-7.00012-6 · Cited by 45 · see citing works
Temporal Integration by Stochastic Recurrent Network Dynamics With Bimodal Neurons
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Coupling between spontaneous (resting state) fMRI fluctuations and human oculo-motor activity
Ramot, M., Wilf, M., Goldberg, H., Weiss, T., Deouell, L. Y., & Malach, R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.06.015 · Cited by 35 · see citing works
Self-citationRamot, M., Fisch, L., Davidesco, I., Harel, M., Kipervasser, S., Andelman, F., Neufeld, M. Y., Kramer, U., Fried, I., & Malach, R. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.0232-13.2013 · Cited by 23 · see citing works
Self-citation
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What is consciousness, and could machines have it?
Dehaene, S., Lau, H., & Kouider, S. (2017) · Science · doi:10.1126/science.aan8871 · Cited by 855 · see citing works
Self-citationUnderstanding the Higher-Order Approach to Consciousness
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Noradrenaline Modulates Visual Perception and Late Visually Evoked Activity
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Initial-state-dependent, robust, transient neural dynamics encode conscious visual perception
Baria, A. T., Maniscalco, B., & He, B. J. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005806 · Cited by 70 · see citing works
Local neuronal relational structures underlying the contents of human conscious experience
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Self-citationApical amplification—a cellular mechanism of conscious perception?
Marvan, T., Polák, M., Bachmann, T., & Phillips, W. A. (2021) · Neuroscience of Consciousness · doi:10.1093/nc/niab036 · Cited by 45 · see citing works
Koukouli, F., Rooy, M., Changeux, J.-P., & Maskos, U. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1614417113 · Cited by 33 · see citing works
Perceptual stability reflected in neuronal pattern similarities in human visual cortex
Broday-Dvir, R., Norman, Y., Harel, M., Mehta, A. D., & Malach, R. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112614 · Cited by 28 · see citing works
Self-citationA measure centrality index for systematic empirical comparison of consciousness theories
Chis-Ciure, R., Melloni, L., & Northoff, G. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105670 · Cited by 22 · see citing works
- Authors
- Moutard, C., Dehaene, S., & Malach, R.
- Affiliations
- Université Paris-Sud (FR)
- Weizmann Institute of Science (IL)
- Corresponding author
- Malach, Rafael
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2015-10
- Volume
- 88
- Issue
- 1
- Pages
- 194-206
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W1929542974
- Cited by
- 99
- References
- 119
- Citations by year
- 2026: 5 · 2025: 5 · 2024: 12 · 2023: 8 · 2022: 7 · 2021: 13 · 2020: 8 · 2019: 10 · 2018: 10 · 2017: 12 · 2016: 9
- FWCI
- 1.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- spontaneous fluctuations, resting-state brain activity, dynamic threshold, perceptual thresholds, subliminal processing, readiness potential, cortical dynamics
- MeSH terms
- Awareness, Cerebral Cortex, Electroencephalography, Humans, Neurons, Sensory Thresholds, Nonlinear Dynamics
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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