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Neuromodulation of Brain State and Behavior
Open accessAbstract
Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.
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“Sleep is a brain state that is characterized by a large-scale organization of neuronal activity that captures virtually all brain regions”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [8]
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InfluentialSleep’s contribution to memory formation
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“Neuromodulators have strong effects on behaviors, and within an animal shifts in neuromodulators are a driver of trial to trial variability (McCormick et al., 2020).”
BackgroundA dynamical systems view of neuroethology: Uncovering stateful computation in natural behaviors
Robson, D. N., & Li, J. (2022) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2022.01.002 · Cited by 25
Deciphering neuronal variability across states reveals dynamic sensory encoding
Akella, S., Ledochowitsch, P., Siegle, J. H., Belski, H., Denman, D. J., Buice, M. A., Durand, S., Koch, C., Olsen, S. R., & Jia, X. (2025) · Nature Communications · doi:10.1038/s41467-025-56733-w · Cited by 31
“Brain state variations often exhibit strong correlations with the animal’s behavioral context (Mccormick et al. 2020; Zagha and McCormick 2014).”
InfluentialWalking humans and running mice: perception and neural encoding of optic flow during self-motion
Horrocks, E. A. B., Mareschal, I., & Saleem, A. B. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2021.0450 · Cited by 29
Memory Consolidation during Ultra-short Offline States
Wamsley, E. J., Arora, M., Gibson, H., Powell, P., & Collins, M. B. (2023) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02035 · Cited by 25
Time, space, memory and brain–body rhythms
Buzsáki, G. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-025-00987-2 · Cited by 32
“In humans, an ~1 min rhythm generated by these cells phase-modulates the power of the cortical alpha rhythm in the right anterior interoceptive insular cortex 158 .”
Goc, G. L., Lafaye, J., Karpenko, S., Bormuth, V., Candelier, R., & Debrégeas, G. (2021) · BMC Biology · doi:10.1186/s12915-021-01126-w · Cited by 18
“patterns of persistent neural activity [5, 6].”
The Neuromodulatory Basis of Aggression: Lessons From the Humble Fruit Fly
Palavicino‐Maggio, C. B., & Sengupta, S. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.836666 · Cited by 18
Spiking activity in the visual thalamus is coupled to pupil dynamics across temporal scales
Crombie, D., Spacek, M. A., Leibold, C., & Busse, L. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002614 · Cited by 24
“More generally, a substantial fraction of shared variability present in large populations of neurons in visual cortex can be explained by high-dimensional sets of behaviors [19], indicating that the state of sensory systems at any given moment results from a combination of multiple processes [3].”
BackgroundLin, Z.-J., Gu, X., Gong, W., Wang, M., Wu, Y., Wang, Q., Wu, X., Zhao, X.-Y., Zhu, M. X., Wang, L., et al. (2024) · Journal of Clinical Investigation · doi:10.1172/jci181095 · Cited by 19
Look-up and look-down neurons in the mouse visual thalamus during freely moving exploration
Orlowska‐Feuer, P., Ebrahimi, A. S., Zippo, A. G., Petersen, R. S., Lucas, R. J., & Storchi, R. (2022) · Current Biology · doi:10.1016/j.cub.2022.07.049 · Cited by 20
In Situ Synthesis and Assembly of Functional Materials and Devices in Living Systems
Wang, W., Sessler, C. D., Wang, X., & Jia Liu, B. (2024) · Accounts of Chemical Research · doi:10.1021/acs.accounts.4c00049 · Cited by 19
Links between the brain and body during sleep: implications for memory processing
Whitehurst, L. N., Subramoniam, A., Krystal, A. D., & Prather, A. A. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2021.12.007 · Cited by 21
“Now, feedback networks between the hippocampus and neocortex become critical for replay and transfer [84 – 87].”
BackgroundBrain Infraslow Activity Correlates With Arousal Levels
Sihn, D., & Kim, S.-P. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.765585 · Cited by 20
Andrews, L., Keller, S. S., Osman‐Farah, J., & Macerollo, A. (2023) · Brain Communications · doi:10.1093/braincomms/fcad171 · Cited by 17
“Given that neuromodulatory effects have been shown to be sensitive to changes in brain state, 122,123 it would make sense that the structural architecture of the brain—in terms of grey and white matter integrity —would instantiate a mediating factor for therapeutic efficacy.”
Locus Coeruleus firing patterns selectively modulate brain activity and dynamicsPreprint
Grimm, C., Duss, S. N., Privitera, M., Munn, B., Frässle, S., Chernysheva, M., Patriarchi, T., Razansky, D., Wenderoth, N., Shine, J. M., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.29.505672 · Cited by 18
Acetylcholine engages distinct amygdala microcircuits to gate internal theta rhythm
Bratsch-Prince, J. X., Warren, J., Jones, G. C., McDonald, A. J., & Mott, D. D. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.1568-23.2024 · Cited by 16
A thalamocortical pathway controlling impulsive behavior
Guzulaitis, R., & Palmer, L. M. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.09.001 · Cited by 26
A time window for memory consolidation during NREM sleep revealed by cAMP oscillation
Deng, Z., Fei, X., Zhang, S., & Xu, M. (2025) · Neuron · doi:10.1016/j.neuron.2025.03.020 · Cited by 19
Neural circuit underlying individual differences in visual escape habituation
Liu, X., Lai, J., Han, C., Zhong, H., Huang, K., Liu, Y., Zhu, X., Wei, P., Tan, L., Xu, F., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.04.018 · Cited by 15
Averna, A., Marceglia, S. R. F., Priori, A., & Foffani, G. (2022) · npj Parkinson s Disease · doi:10.1038/s41531-022-00399-4 · Cited by 16
“(1) and (2) respectively) by varying either the amplitude or the frequency of a sinusoidal carrier signal fc with a modulating signal of lower frequency fm (Lathi and Ding, 2010):”
BackgroundNeurobiological reduction: From cellular explanations of behavior to interventions
Parker, D. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.987101 · Cited by 18
Toward a computational role for locus coeruleus/norepinephrine arousal systems
Nassar, M. R. (2024) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2024.101407 · Cited by 18
Papadopoulos, L., Jo, S., Zumwalt, K., Wehr, M., Jaramillo, S., McCormick, D. A., & Mazzucato, L. (2025) · Neuron · doi:10.1016/j.neuron.2025.11.011 · Cited by 16
Self-citationDissociable Components of Information Encoding in Human Perception
Vidaurre, D., Cichy, R. M., & Woolrich, M. W. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab189 · Cited by 15
“modulate neural responses (Podvalny et al. 2019; McCormick et al. 2020), it is clear that part of the large variability observed in the neural responses could be explained by the ongoing, largescale network activity and concurrent phase trajectories, and that accounting by these factors could arguably improve the capa…”
BackgroundYin, C., Melin, M. D., Rojas-Bowe, G., Sun, X. R., Couto, J., Gluf, S., Kostiuk, A., Musall, S., & Churchland, A. K. (2025) · Neuron · doi:10.1016/j.neuron.2025.06.001 · Cited by 23
Midbrain encodes sound detection behavior without auditory cortexPreprint
Lee, T.-Y., Weissenberger, Y., King, A. J., & Dahmen, J. C. (2023) · eLife · doi:10.7554/elife.89950 · Cited by 12
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Recurrent network interactions explain tectal response variability and experience-dependent behavior
Zylbertal, A., & Bianco, I. H. (2023) · eLife · doi:10.7554/elife.78381 · Cited by 11
Contribution of membrane-associated oscillators to biological timing at different timescales
Stengl, M., & Schneider, A. C. (2024) · Frontiers in Physiology · doi:10.3389/fphys.2023.1243455 · Cited by 15
“As foundation of robust, autonomous neuronal functions multiple mechanisms of homeostatic plasticity at the level of single neurons as well as at the level of neuronal ensembles maintain a speci fi c dynamic setpoint measurable as stable spike frequency (McCormick et al., 2020).”
BackgroundInfluentialSimola, J., Siebenhühner, F., Myrov, V. O., Kantojärvi, K., Paunio, T., Palva, J. M., Brattico, E., & Palva, S. (2022) · iScience · doi:10.1016/j.isci.2022.104985 · Cited by 11
“, 2014; Mostame and Sadaghiani, 2020) and neuromodulation (McCormick et al., 2020; Pfeffer et al., 2021; van den Brink et al., 2018; van den Brink et al., 2019).”
BackgroundInput-Independent Homeostasis of Developing Thalamocortical Activity
Riyahi, P., Phillips, M. A., & Colonnese, M. T. (2021) · eNeuro · doi:10.1523/eneuro.0184-21.2021 · Cited by 11
Ngomba, R. T., Lüttjohann, A., Dexter, A., Ray, S., & van Luijtelaar, G. (2023) · Cells · doi:10.3390/cells12131761 · Cited by 10
“Different brain regions, including the neocortex, hippocampus, thalamus, and brainstem, are involved in the neuronal activities during the various sleep states [14].”
BackgroundBrain network dynamics predict moments of surprise across contexts
Zhang, Z., & Rosenberg, M. D. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-02017-0 · Cited by 10
“This approach offers new perspectives for analysing data from existing cognitive paradigms and possibilities for identifying signatures of cognitive states fluctuations from large-scale brain networks 69–71 .”
Excite the unexcitable: engineering cells and redox signaling for targeted bioelectronic control
Wang, S., Aljirafi, F. O., Payne, G. F., & Bentley, W. E. (2023) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2023.103052 · Cited by 10
Metadata
- Authors
- McCormick, D. A., Nestvogel, D. B., & He, B. J.
- Affiliations
- University of Oregon (US)
- NYU Langone Health (US)
- Corresponding author
- McCormick, David A.
- Venue
- Annual Review of Neuroscience
- Publisher
- Annual Reviews
- Published
- 2020-07-08
- Volume
- 43
- Issue
- 1
- Pages
- 391-415
- ISSN
- 0147-006X (ISSN-L)
- 1545-4126
- PMC
- PMC12237593
- OpenAlex
- W3014163957
- Cited by
- 303
- References
- 167
- Citations by year
- 2026: 40 · 2025: 60 · 2024: 72 · 2023: 48 · 2022: 41 · 2021: 36 · 2020: 6
- FWCI
- 4.43
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annual Review of Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- National Institute on Deafness and Other Communication Disorders (R01DC015803)
- National Institute of Neurological Disorders and Stroke (R35NS097287)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- brain states, neural state transitions, behavioral state transitions, neuromodulation, cortico-cortical pathways, neural variability, cognitive states
- MeSH terms
- Animals, Behavior, Brain, Cerebral Cortex, Humans, Nerve Net, Neural Pathways, Neurons
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