Spontaneous Infra-slow Brain Activity Has Unique Spatiotemporal Dynamics and Laminar Structure
Open accessAbstract
Systems-level organization in spontaneous infra-slow (<0.1Hz) brain activity, measured using blood oxygen signals in fMRI and optical imaging, has become a major theme in the study of neural function in both humans and animal models. Yet the neurophysiological basis of infra-slow activity (ISA) remains unresolved. In particular, is ISA a distinct physiological process, or is it a low-frequency analog of faster neural activity? Here, using whole-cortex calcium/hemoglobin imaging in mice, we show that ISA in each of these modalities travels through the cortex along stereotypical spatiotemporal trajectories that are state dependent (wake versus anesthesia) and distinct from trajectories in delta (1-4 Hz) activity. Moreover, mouse laminar electrophysiology reveals that ISA travels through specific cortical layers and is organized into unique cross-laminar temporal dynamics that are different from higher frequency local field potential activity. These findings suggest that ISA is a distinct neurophysiological process that is reflected in fMRI blood oxygen signals.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Large-scale anterior-to-posterior propagation patterns were observed upon REM sleep onset.
“Large-scale anterior to posterior propagation patterns were observed upon REM sleep onset, and related propagation dynamics have also been reported under anesthesia50, suggesting that such activity may reflect a general organizing principle of large-scale brain dynamics across states.”
From Energy paradox in REM sleep: balancing supply and consumption in brain metabolism (2026) · cites this paper as [50]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812 · see citing works
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700 · see citing works
Self-citationPredicting human resting-state functional connectivity from structural connectivity
Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meuli, R., & Hagmann, P. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811168106 · Cited by 3,307 · see citing works
High Gamma Power Is Phase-Locked to Theta Oscillations in Human Neocortex
Canolty, R. T., Edwards, E., Dalal, S. S., Soltani, M., Nagarajan, S. S., Kirsch, H. E., Berger, M. S., Barbaro, N. M., & Knight, R. T. (2006) · Science · doi:10.1126/science.1128115 · Cited by 2,650 · see citing works
Steriade, M., Nunez, A., & Amzica, F. (1993) · The Journal of Neuroscience · doi:10.1523/jneurosci.13-08-03252.1993 · Cited by 1,903 · see citing works
Boosting slow oscillations during sleep potentiates memory
Marshall, L., Helgadóttir, H., Mölle, M., & Born, J. (2006) · Nature · doi:10.1038/nature05278 · Cited by 1,792 · see citing works
Dynamic models of large-scale brain activity
Breakspear, M. (2017) · Nature Neuroscience · doi:10.1038/nn.4497 · Cited by 1,239 · see citing works
The sleep slow oscillation as a traveling wave
Massimini, M., Huber, R., Ferrarelli, F., Hill, S., & Tononi, G. (2004) · The Journal of Neuroscience · doi:10.1523/jneurosci.1318-04.2004 · Cited by 1,221 · see citing works
Resting-state functional connectivity in neuropsychiatric disorders
Greicius, M. (2008) · Current Opinion in Neurology · doi:10.1097/wco.0b013e328306f2c5 · Cited by 1,180 · see citing works
The MVGC multivariate Granger causality toolbox: A new approach to Granger-causal inference
Barnett, L., & Seth, A. K. (2013) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2013.10.018 · Cited by 1,046 · see citing works
Spontaneously emerging cortical representations of visual attributes
Kenet, T., Bibitchkov, D., Tsodyks, M., Grinvald, A., & Arieli, A. (2003) · Nature · doi:10.1038/nature02078 · Cited by 924 · see citing works
van Kerkoerle, T., Self, M. W., Dagnino, B., Gariel-Mathis, M.-A., Poort, J., van der Togt, C., & Roelfsema, P. R. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1402773111 · Cited by 918 · see citing works
Neuromodulation of neuronal circuits: back to the future
Marder, E. (2012) · Neuron · doi:10.1016/j.neuron.2012.09.010 · Cited by 904 · see citing works
Nelson, L. E., Lu, J., Guo, T., Saper, C. B., Franks, N. P., & Maze, M. (2003) · Anesthesiology · doi:10.1097/00000542-200302000-00024 · Cited by 854 · see citing works
Very Slow Activity Fluctuations in Monkey Visual Cortex: Implications for Functional Brain Imaging
Leopold, D. A. (2003) · Cerebral Cortex · doi:10.1093/cercor/13.4.422 · Cited by 675 · see citing works
Electrophysiological correlates of the brain's intrinsic large-scale functional architecture
He, B. J., Snyder, A. Z., Zempel, J. M., Smyth, M. D., & Raichle, M. E. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0807010105 · Cited by 670 · see citing works
Self-citationLaminar Structure of Spontaneous and Sensory-Evoked Population Activity in Auditory Cortex
Sakata, S., & Harris, K. D. (2009) · Neuron · doi:10.1016/j.neuron.2009.09.020 · Cited by 581 · see citing works
The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core
Deco, G., Kringelbach, M. L., Jirsa, V., & Ritter, P. (2017) · Scientific Reports · doi:10.1038/s41598-017-03073-5 · Cited by 534 · see citing works
Monto, S., Palva, S., Voipio, J., & Palva, J. M. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.1910-08.2008 · Cited by 453 · see citing works
Ma, Y., Shaik, M. A., Kozberg, M. G., Kim, S. H., Portes, J., Timerman, D., & Hillman, E. M. C. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1525369113 · Cited by 308 · see citing works
Interpreting temporal fluctuations in resting-state functional connectivity MRI
Liégeois, R., Laumann, T. O., Snyder, A. Z., Zhou, J. H., & Yeo, B. T. T. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.012 · Cited by 256 · see citing works
Self-citationImaging of Functional Connectivity in the Mouse Brain
White, B. R., Bauer, A. Q., Snyder, A. Z., Schlaggar, B. L., Lee, J.-M., & Culver, J. P. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016322 · Cited by 253 · see citing works
Self-citationMaking Waves: Initiation and Propagation of Corticothalamic Ca2+ Waves In Vivo
Stroh, A., Adelsberger, H., Groh, A., Rühlmann, C., Fischer, S., Schierloh, A., Deisseroth, K. A., & Konnerth, A. (2013) · Neuron · doi:10.1016/j.neuron.2013.01.031 · Cited by 249 · see citing works
Infraslow LFP correlates to resting-state fMRI BOLD signals
Pan, W.-J., Thompson, G. J., Magnuson, M. E., Jaeger, D., & Keilholz, S. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.035 · Cited by 231 · see citing works
General anesthesia and the neural correlates of consciousness
Alkire, M. T., & Miller, J. (2005) · Progress in brain research · doi:10.1016/s0079-6123(05)50017-7 · Cited by 219 · see citing works
Astrocytic regulation of cortical UP states
Poskanzer, K. E., & Yuste, R. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1112378108 · Cited by 207 · see citing works
Intact skull chronic windows for mesoscopic wide-field imaging in awake mice
Silasi, G., Xiao, D., Vanni, M. P., Chen, A. C. N., & Murphy, T. H. (2016) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2016.04.012 · Cited by 205 · see citing works
Lag threads organize the brain’s intrinsic activity
Mitra, A., Snyder, A. Z., Blazey, T., & Raichle, M. E. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1503960112 · Cited by 186 · see citing works
Self-citationLag structure in resting-state fMRI
Mitra, A., Snyder, A. Z., Hacker, C. D., & Raichle, M. E. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00804.2013 · Cited by 185 · see citing works
Self-citationMatsui, T., Murakami, T., & Ohki, K. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1521299113 · Cited by 181 · see citing works
Berger, T. K., Borgdorff, A. J., Crochet, S., Neubauer, F. B., Lefort, S., Fauvet, B., Férézou, I., Carleton, A., Lüscher, H., & Petersen, C. C. H. (2007) · Journal of Neurophysiology · doi:10.1152/jn.01178.2006 · Cited by 178 · see citing works
Infra-Slow Rhythmic Oscillations of The Steady Potential of the Cerebral Cortex
ALADJALOVA, N. A. (1957) · Nature · doi:10.1038/179957a0 · Cited by 168 · see citing works
Global Intracellular Slow-Wave Dynamics of the Thalamocortical System
Sheroziya, M., & Timofeev, I. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4460-13.2014 · Cited by 142 · see citing works
Human cortical–hippocampal dialogue in wake and slow-wave sleep
Mitra, A., Snyder, A. Z., Hacker, C. D., Pahwa, M., Tagliazucchi, E., Laufs, H., Leuthardt, E. C., & Raichle, M. E. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1607289113 · Cited by 139 · see citing works
Self-citationMapping cortical mesoscopic networks of single spiking cortical or sub-cortical neurons
Xiao, D., Vanni, M. P., Mitelut, C., Chan, A. W., LeDue, J. M., Xie, Y., Chen, A. C. N., Swindale, N. V., & Murphy, T. H. (2017) · eLife · doi:10.7554/elife.19976 · Cited by 127 · see citing works
Temporal dynamics of the BOLD fMRI impulse response
de Zwart, J. A., Silva, A. C., van Gelderen, P., Kellman, P., Fukunaga, M., Chu, R., Koretsky, A. P., Frank, J. A., & Duyn, J. H. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.09.013 · Cited by 123 · see citing works
Propagated infra-slow intrinsic brain activity reorganizes across wake and slow wave sleep
Mitra, A., Snyder, A. Z., Tagliazucchi, E., Laufs, H., & Raichle, M. E. (2015) · eLife · doi:10.7554/elife.10781 · Cited by 117 · see citing works
Self-citationSpontaneous Neurotransmission: An Independent Pathway for Neuronal Signaling?
Kavalali, E. T., Chung, C., Khvotchev, M., Leitz, J., Nosyreva, E., Raingo, J., & Ramirez, D. M. O. (2011) · Physiology · doi:10.1152/physiol.00040.2010 · Cited by 104 · see citing works
Chan, A. W., Mohajerani, M. H., LeDue, J. M., Wang, Y. T., & Murphy, T. H. (2015) · Nature Communications · doi:10.1038/ncomms8738 · Cited by 81 · see citing works
State-Dependent Modulation of Slow Wave Motifs towards Awakening
Shimaoka, D., Song, C., & Knöpfel, T. (2017) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2017.00108 · Cited by 26 · see citing works
Huang, L., Liu, Y., Li, M., & Hu, D. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.07.061 · Cited by 16 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Hierarchical dynamics as a macroscopic organizing principle of the human brain
Raut, R. V., Snyder, A. Z., & Raichle, M. E. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2003383117 · Cited by 296 · see citing works
Self-citationNeuromodulation of brain state and behavior
McCormick, D. A., Nestvogel, D. B., & He, B. J. (2020) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-100219-105424 · Cited by 303 · see citing works
Spatial and Temporal Organization of the Individual Human Cerebellum
Marek, S. A., Siegel, J. S., Gordon, E. M., Raut, R. V., Gratton, C., Newbold, D. J., Ortega, M., Laumann, T. O., Adeyemo, B., Miller, D. B., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.010 · Cited by 291 · see citing works
Self-citationThe Default Mode Network’s Role in Discrete Emotion
Satpute, A. B., & Lindquist, K. A. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.07.003 · Cited by 262 · see citing works
Global waves synchronize the brain’s functional systems with fluctuating arousal
Raut, R. V., Snyder, A. Z., Mitra, A., Yellin, D., Fujii, N., Malach, R., & Raichle, M. E. (2021) · Science Advances · doi:10.1126/sciadv.abf2709 · Cited by 261 · see citing works
Self-citationHigh-resolution mapping of infraslow cortical brain activity enabled by graphene microtransistors
Masvidal‐Codina, E., Illa, X., Dasilva, M., Calia, A. B., Dragojević, T., Vidal-Rosas, E. E., Prats‐Alfonso, E., Martínez-Aguilar, J., de la Cruz, J. M., Garcia‐Cortadella, R., et al. (2018) · Nature Materials · doi:10.1038/s41563-018-0249-4 · Cited by 174 · see citing works
Default-mode network streams for coupling to language and control systems
Gordon, E. M., Laumann, T. O., Marek, S. A., Raut, R. V., Gratton, C., Newbold, D. J., Greene, D. J., Coalson, R. S., Snyder, A. Z., Schlaggar, B. L., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2005238117 · Cited by 170 · see citing works
Self-citationThe brain’s action-mode network
Dosenbach, N. U. F., Raichle, M. E., & Gordon, E. M. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-024-00895-x · Cited by 204 · see citing works
Self-citationThe secret life of predictive brains: what’s spontaneous activity for?
Pezzulo, G., Zorzi, M., & Corbetta, M. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2021.05.007 · Cited by 164 · see citing works
Movement and Performance Explain Widespread Cortical Activity in a Visual Detection Task
Salkoff, D. B., Zagha, E., McCarthy, E., & McCormick, D. A. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz206 · Cited by 153 · see citing works
Why is everyone talking about brain state?
Greene, A. S., Horien, C. L., Barson, D. G., Scheinost, D., & Constable, R. T. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.04.001 · Cited by 148 · see citing works
Beyond Trial-Based Paradigms: Continuous Behavior, Ongoing Neural Activity, and Natural Stimuli
Huk, A. C., Bonnen, K., & He, B. J. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1920-17.2018 · Cited by 138 · see citing works
Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry
Sylvester, C. M., Yu, Q., Srivastava, A. B., Marek, S., Zheng, A., Alexopoulos, D., Smyser, C. D., Shimony, J. S., Ortega, M., Dierker, D. L., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1910842117 · Cited by 139 · see citing works
Self-citationIncreased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex
Rocchi, F., Canella, C., Noei, S., Gutierrez‐Barragan, D., Coletta, L., Galbusera, A., Stuefer, A., Vassanelli, S., Pasqualetti, M., Iurilli, G., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28591-3 · Cited by 114 · see citing works
Coupling of activity, metabolism and behaviour across the Drosophila brain
Mann, K. J., Deny, S., Ganguli, S., & Clandinin, T. R. (2021) · Nature · doi:10.1038/s41586-021-03497-0 · Cited by 103 · see citing works
Brain Activity Fluctuations Propagate as Waves Traversing the Cortical Hierarchy
Gu, Y., Sainburg, L. E., Kuang, S., Han, F., Williams, J. W., Liu, Y., Zhang, N., Zhang, X., Leopold, D. A., & Liu, X. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab064 · Cited by 101 · see citing works
Separation of hemodynamic signals from GCaMP fluorescence measured with wide-field imaging
Valley, M. T., Moore, M. G., Zhuang, J., Mesa, N., Castelli, D., Sullivan, D., Reimers, M., & Waters, J. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00304.2019 · Cited by 99 · see citing works
Spatial Embedding Imposes Constraints on Neuronal Network Architectures
Stiso, J., & Bassett, D. S. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.09.007 · Cited by 95 · see citing works
Functional Connectivity of the Brain Across Rodents and Humans
Xu, N., LaGrow, T. J., Anumba, N., Lee, A., Zhang, X., Yousefi, B., Bassil, Y., Clavijo, P. G., Sharghi, V. K., Maltbie, E. A., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.816331 · Cited by 91 · see citing works
Low-Dimensional Spatiotemporal Dynamics Underlie Cortex-wide Neural Activity
MacDowell, C. J., & Buschman, T. J. (2020) · Current Biology · doi:10.1016/j.cub.2020.04.090 · Cited by 94 · see citing works
Garcia‐Cortadella, R., Schwesig, G., Jeschke, C., Illa, X., Gray, A. L., Savage, S., Stamatidou, E., Schießl, I., Masvidal‐Codina, E., Kostarelos, K., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20546-w · Cited by 94 · see citing works
Organization of Propagated Intrinsic Brain Activity in Individual Humans
Raut, R. V., Mitra, A., Marek, S. A., Ortega, M., Snyder, A. Z., Tanenbaum, A., Laumann, T. O., Dosenbach, N. U. F., & Raichle, M. E. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz198 · Cited by 78 · see citing works
Self-citationSharoh, D., van Mourik, T., Bains, L. J., Segaert, K., Weber, K., Peter Hagoort, A., & Norris, D. G. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1907858116 · Cited by 77 · see citing works
Elucidating relations between fMRI, ECoG, and EEG through a common natural stimulus
Haufe, S., DeGuzman, P., Henin, S. E., Arcaro, M. J., Honey, C. J., Hasson, U., & Parra, L. C. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2018.06.016 · Cited by 77 · see citing works
The history and future of resting-state functional magnetic resonance imaging
Biswal, B. B., & Uddin, L. Q. (2025) · Nature · doi:10.1038/s41586-025-08953-9 · Cited by 76 · see citing works
Bourdillon, P., Hermann, B., Guénot, M., Bastuji, H., Isnard, J., King, J.-R., Sitt, J. D., & Naccache, L. (2020) · Scientific Reports · doi:10.1038/s41598-020-70447-7 · Cited by 73 · see citing works
Brændholt, M., Kluger, D. S., Varga, S., Heck, D. H., Groß, J., & Allen, M. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105262 · Cited by 79 · see citing works
Subcortical-cortical dynamical states of the human brain and their breakdown in stroke
Favaretto, C., Allegra, M., Deco, G., Metcalf, N. V., Griffis, J. C., Shulman, G. L., Brovelli, A., & Corbetta, M. (2022) · Nature Communications · doi:10.1038/s41467-022-32304-1 · Cited by 72 · see citing works
Arousal as a universal embedding for spatiotemporal brain dynamics
Raut, R. V., Rosenthal, Z. P., Wang, X., Miao, H., Zhang, Z., Lee, J., Raichle, M. E., Bauer, A. Q., Brunton, S. L., Brunton, B. W., et al. (2025) · Nature · doi:10.1038/s41586-025-09544-4 · Cited by 67 · see citing works
Self-citationAstrocytes regulate ultra-slow arteriole oscillations via stretch-mediated TRPV4-COX-1 feedback
Haidey, J. N., Peringod, G., Institóris, Á., Gorzo, K. A., Nicola, W., Vandal, M., Ito, K., Liu, S., Fielding, C., Visser, F., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109405 · Cited by 66 · see citing works
Model-based whole-brain effective connectivity to study distributed cognition in health and disease
Gilson, M., Zamora‐López, G., Pallarés, V., Adhikari, M. H., Senden, M., Campo, A. T., Mantini, D., Corbetta, M., Deco, G., & Insabato, A. (2019) · Network Neuroscience · doi:10.1162/netn_a_00117 · Cited by 59 · see citing works
Targeted neurostimulation reverses a spatiotemporal biomarker of treatment-resistant depression
Mitra, A., Raichle, M. E., Geoly, A. D., Kratter, I. H., & Williams, N. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2218958120 · Cited by 58 · see citing works
Self-citationA Hierarchy of Autonomous Systems for Vocal Production
Zhang, Y. S., & Ghazanfar, A. A. (2020) · Trends in Neurosciences · doi:10.1016/j.tins.2019.12.006 · Cited by 53 · see citing works
Sources of widefield fluorescence from the brain
Waters, J. (2020) · eLife · doi:10.7554/elife.59841 · Cited by 57 · see citing works
On time delay estimation and sampling error in resting-state fMRI
Raut, R. V., Mitra, A., Snyder, A. Z., & Raichle, M. E. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.03.020 · Cited by 56 · see citing works
Self-citationMechanisms of Action of TMS in the Treatment of Depression
Downar, J. H., Siddiqi, S., Mitra, A., Williams, N., & Liston, C. M. (2024) · Current topics in behavioral neurosciences · doi:10.1007/7854_2024_483 · Cited by 55 · see citing works
Self-citationDistinct Structure of Cortical Population Activity on Fast and Infraslow Timescales
Okun, M., Steinmetz, N. A., Lak, A., Dervinis, M., & Harris, K. D. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz023 · Cited by 55 · see citing works
New perspectives on dimensionality and variability from large-scale cortical dynamics
Engel, T. A., & Steinmetz, N. A. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.09.003 · Cited by 53 · see citing works
Cortex-Wide Dynamics of Intrinsic Electrical Activities: Propagating Waves and Their Interactions
Liang, Y., Song, C., Liu, M., Gong, P., Zhou, C., & Knöpfel, T. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0623-20.2021 · Cited by 53 · see citing works
Shahsavarani, S., Thibodeaux, D. N., Xu, W., Kim, S. H., Lodgher, F., Nwokeabia, C., Cambareri, M. K., Yagielski, A. J., Zhao, H., Handwerker, D. A., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112527 · Cited by 50 · see citing works
Estimation and validation of individualized dynamic brain models with resting state fMRI
Singh, M. F., Braver, T. S., Cole, M. W., & Ching, S. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117046 · Cited by 47 · see citing works
Genetically defined cellular correlates of the baseline brain MRI signal
Wen, J., Goyal, M. S., Astafiev, S. V., Raichle, M. E., & Yablonskiy, D. A. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1808121115 · Cited by 48 · see citing works
Self-citationBrain states govern the spatio-temporal dynamics of resting-state functional connectivity
Aedo-Jury, F., Schwalm, M., Hamzehpour, L., & Stroh, A. (2020) · eLife · doi:10.7554/elife.53186 · Cited by 43 · see citing works
Neurophotonic tools for microscopic measurements and manipulation: status report
Abdelfattah, A. S., Allu, S., Campbell, R. E., Cheng, X., Čižmár, T., Costantini, I., Emiliani, V., Fomin-Thunemann, N., Gilad, A., Fernández-Alfonso, T., et al. (2022) · Neurophotonics · doi:10.1117/1.nph.9.s1.013001 · Cited by 48 · see citing works
Brain works principle followed by neural information processing: a review of novel brain theory
Wang, R., Wang, Y., Xu, X., Li, Y., & Pan, X. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10520-5 · Cited by 43 · see citing works
Vafaii, H., Mandino, F., Desrosiers-Grégoire, G., O’Connor, D. A., Markicevic, M., Shen, X., Ge, X., Hermán, P., Hyder, F., Papademetris, X., et al. (2024) · Nature Communications · doi:10.1038/s41467-023-44363-z · Cited by 40 · see citing works
On co-activation pattern analysis and non-stationarity of resting brain activity
Matsui, T., Pham, T. Q., Jimura, K., & Chikazoe, J. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.118904 · Cited by 40 · see citing works
Development of top-down cortical propagations in youth
Pines, A. R., Keller, A. S., Larsen, B., Bertolero, M. A., Ashourvan, A., Bassett, D. S., Cieslak, M., Covitz, S. C., Yong Fan, A., Feczko, E., et al. (2023) · Neuron · doi:10.1016/j.neuron.2023.01.014 · Cited by 39 · see citing works
Murphy, T. H., Michelson, N. J., Boyd, J. D., Fong, T. L., Bolaños, L. A., Bierbrauer, D., Siu, T., Balbi, M., Bolaños, F., Vanni, M. P., et al. (2020) · eLife · doi:10.7554/elife.55964 · Cited by 39 · see citing works
MacDowell, C. J., Tafazoli, S., & Buschman, T. J. (2022) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2022.102606 · Cited by 36 · see citing works
Sleep fMRI with simultaneous electrophysiology at 9.4 T in male mice
Yu, Y., Qiu, Y., Li, G., Zhang, K., Bo, B., Pei, M., Ye, J., Thompson, G. J., Cang, J., Fang, F., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37352-9 · Cited by 36 · see citing works
Control networks of the frontal lobes
Marek, S. A., & Dosenbach, N. U. F. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-12-804281-6.00018-5 · Cited by 37 · see citing works
Spatiotemporal patterns of spontaneous brain activity: a mini-review
Meyer-Baese, L., Watters, H. N., & Keilholz, S. D. (2022) · Neurophotonics · doi:10.1117/1.nph.9.3.032209 · Cited by 34 · see citing works
Propofol Anesthesia Alters Cortical Traveling Waves
Bhattacharya, S., Donoghue, J., Mahnke, M. K., Brincat, S. L., Brown, E. N., & Miller, E. K. (2022) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01856 · Cited by 33 · see citing works
Michelson, N. J., Vanni, M. P., & Murphy, T. H. (2019) · Neurophotonics · doi:10.1117/1.nph.6.2.025014 · Cited by 32 · see citing works
Rosenthal, Z. P., Raut, R. V., Yan, P., Koko, D., Kraft, A. W., Czerniewski, L. R., Acland, B. T., Mitra, A., Snyder, L. H., Bauer, A. Q., et al. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz314 · Cited by 33 · see citing works
Self-citationSymmetry breaking organizes the brain’s resting state manifold
Fousek, J., Rabuffo, G., Gudibanda, K., Sheheitli, H., Petkoski, S., & Jirsa, V. (2024) · Scientific Reports · doi:10.1038/s41598-024-83542-w · Cited by 31 · see citing works
Bueno-Júnior, L. S., Ruckstuhl, M., Lim, M. M., & Watson, B. O. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2213438120 · Cited by 31 · see citing works
Brain states as wave-like motifs
Foster, M. L., & Scheinost, D. (2024) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2024.03.004 · Cited by 29 · see citing works
Archila-Meléndez, M. E., Sorg, C., & Preibisch, C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116871 · Cited by 29 · see citing works
Tong, C., Dai, J., Chen, Y., Zhang, K., Feng, Y., & Liang, Z. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.07.006 · Cited by 28 · see citing works
Matsui, T., & Yamashita, K.-I. (2022) · Brain Connectivity · doi:10.1089/brain.2022.0044 · Cited by 27 · see citing works
Neural oscillations in human auditory cortex revealed by fast fMRI during auditory perception
Frühholz, S., Trost, W. J., Grandjean, D., & Belin, P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116401 · Cited by 30 · see citing works
Yu, M. (2020) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0018826 · Cited by 26 · see citing works
Precision functional mapping of the subcortex and cerebellum
Marek, S., & Greene, D. J. (2021) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2020.12.011 · Cited by 25 · see citing works
Albertson, A. J., Landsness, E., Tang, M. J., Yan, P., Miao, H.-Y., Rosenthal, Z., Kim, B., Culver, J. C., Bauer, A. Q., & Lee, J.-M. (2021) · bioRxiv · doi:10.1016/j.neuroimage.2022.119287 · Cited by 25 · see citing works
Self-citationSynchronization lag in post stroke: relation to motor function and structural connectivity
Wang, X., Seguin, C., Zalesky, A., Wong, W.-W., Chu, C. W., & Tong, R. K. (2019) · Network Neuroscience · doi:10.1162/netn_a_00105 · Cited by 23 · see citing works
Chen, W., Park, K., Pan, Y., Koretsky, A. P., & Du, C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116554 · Cited by 23 · see citing works
Origins of 1/f-like tissue oxygenation fluctuations in the murine cortex
Zhang, Q., Gheres, K. W., & Drew, P. J. (2021) · PLoS Biology · doi:10.1371/journal.pbio.3001298 · Cited by 22 · see citing works
Electroconvulsive therapy generates a postictal wave of spreading depolarization in mice and humans
Rosenthal, Z. P., Majeski, J. B., Somarowthu, A., Quinn, D. K., Lindquist, B. E., Putt, M. E., Karaj, A., Favilla, C. G., Baker, W. B., Hosseini, G., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59900-1 · Cited by 21 · see citing works
Self-citationStieger, J., Pinheiro‐Chagas, P., Fang, Y., Li, J., Lusk, Z., Perry, C., Girn, M., Contreras, D., Chen, Q., Huguenard, J. R., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2316021121 · Cited by 21 · see citing works
Palanisamy, A., Giri, T. K., Jiang, J., Bice, A. R., Quirk, J. D., Conyers, S. B., Maloney, S. E., Raghuraman, N., Bauer, A. Q., Garbow, J. R., et al. (2020) · JCI Insight · doi:10.1172/jci.insight.133172 · Cited by 20 · see citing works
Self-citationThe enigma of infra-slow fluctuations in the human EEG
Kropotov, J. D. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.928410 · Cited by 19 · see citing works
Wang, X., Padawer-Curry, J. A., Bice, A. R., Kim, B., Rosenthal, Z. P., Lee, J., Goyal, M. S., Macauley, S. L., & Bauer, A. Q. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114723 · Cited by 21 · see citing works
Self-citationMapping Structure-Function Relationships in the Brain
Snyder, A. Z., & Bauer, A. Q. (2018) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.10.005 · Cited by 19 · see citing works
Self-citationWhole-brain electrophysiological functional connectivity dynamics in resting-state EEG
Shou, G., Yuan, H., Li, C., Chen, Y., Chen, Y., & Ding, L. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab7ad3 · Cited by 17 · see citing works
Kahali, S., Raichle, M. E., & Yablonskiy, D. A. (2021) · Brain Sciences · doi:10.3390/brainsci11121565 · Cited by 16 · see citing works
Self-citationAstrocyte strategies in the energy-efficient brain
Fernández-González, I., & Galea, E. (2022) · Essays in Biochemistry · doi:10.1042/ebc20220077 · Cited by 16 · see citing works
Low Frequency Phase-locking of Brain Signals Contribute to Efficient Face Recognition
Wang, Y., Huang, X., Yang, X., Yang, Q., Wang, X., Northoff, G., Pang, Y., Wang, C., Cui, Q., & Chen, H. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.10.024 · Cited by 16 · see citing works
Cortical propagation tracks functional recovery after stroke
Cecchini, G., Scaglione, A., Mascaro, A. L. A., Checcucci, C., Conti, E., Adam, I., Fanelli, D., Livi, R., Pavone, F. S., & Kreuz, T. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008963 · Cited by 15 · see citing works
Hindriks, R., Mantini, D., Gravel, N., & Deco, G. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.06.007 · Cited by 15 · see citing works
Rosenthal, Z. P., Raut, R. V., Bowen, R. M., Snyder, A. Z., Culver, J. P., Raichle, M. E., & Lee, J. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2021252118 · Cited by 15 · see citing works
Self-citationActive neural coordination of motor behaviors with internal states
Zhang, Y. S., Takahashi, D. Y., Hady, A. E., Liao, D. A., & Ghazanfar, A. A. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2201194119 · Cited by 13 · see citing works
Bjerkan, J., Lancaster, G., Meglič, B., Kobal, J., Crawford, T. J., McClintock, P. V. E., & Stefanovska, A. (2023) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2023.110704 · Cited by 14 · see citing works
Järvelä, M., Raatikainen, V., Kotila, A., Kananen, J., Korhonen, V. O., Uddin, L. Q., Ansakorpi, H., & Kiviniemi, V. J. (2020) · Cerebral Cortex Communications · doi:10.1093/texcom/tgaa073 · Cited by 13 · see citing works
Possible links between the lag structure in visual cortex and visual streams using fMRI
Park, B., Shim, W. M., James, O., & Park, H. (2019) · Scientific Reports · doi:10.1038/s41598-019-40728-x · Cited by 13 · see citing works
The secret life of predictive brains: what's spontaneous activity for?Preprint
Pezzulo, G., Zorzi, M., & Corbetta, M. (2020) · doi:10.31234/osf.io/qus3h · Cited by 17 · see citing works
Zhang, S., Gao, G., Shi, W., Li, B., Lin, Q., Shu, H., & Shao, Y. (2021) · BMC Ophthalmology · doi:10.1186/s12886-021-02015-0 · Cited by 12 · see citing works
Xu, N., Smith, D. M., Jeno, G., Seeburger, D. T., Schumacher, E. H., & Keilholz, S. D. (2023) · Imaging Neuroscience · doi:10.1162/imag_a_00002 · Cited by 12 · see citing works
The Interplay Between Information Flux and Temporal Dynamics in Infraslow FrequenciesPreprint
Golesorkhi, M., Tumati, S., Gómez‐Pilar, J., Stamatakis, E. A., & Northoff, G. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.11.106476 · Cited by 12 · see citing works
Han, Z., Liu, T., Shi, Z., Zhang, J., Suo, D., Wang, L., Chen, D., Wu, J., & Yan, T. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgad276 · Cited by 11 · see citing works
Cancino-Fuentes, N., Manasanch, A., Covelo, J., Suarez-Perez, A., Fernandez, E., Matsoukis, S., Guger, C., Illa, X., Guimerà‐Brunet, A., & Sanchez-Vives, M. V. (2023) · Nanoscale · doi:10.1039/d3nr03842d · Cited by 11 · see citing works
Rudas, J., Martínez, D., Castellanos, G., Athena Demertzi, A., Martial, C., Carrière, M., Aubinet, C., Soddu, A., Laureys, S., & Gómez, F. A. (2020) · Brain Connectivity · doi:10.1089/brain.2019.0716 · Cited by 11 · see citing works
Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques
Celotto, M., Luca, C. D., Muratore, P., Resta, F., Mascaro, A. L. A., Pavone, F. S., Bonis, G. D., & Paolucci, P. S. (2020) · Methods and Protocols · doi:10.3390/mps3010014 · Cited by 11 · see citing works
Fei, Y., Wu, Q., Zhao, S., Song, K., Han, J., & Liu, C. (2024) · Nature Communications · doi:10.1038/s41467-024-47762-y · Cited by 9 · see citing works
Scaglione, A., Resta, F., Goretti, F., & Pavone, F. S. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1258793 · Cited by 9 · see citing works
Differences in the expression of cortex-wide neural dynamics are related to behavioral phenotype
MacDowell, C. J., Briones, B. A., Lenzi, M. J., Gustison, M. L., & Buschman, T. J. (2024) · Current Biology · doi:10.1016/j.cub.2024.02.004 · Cited by 9 · see citing works
Cao, B., Guo, Y. Q., Guo, Y., Xie, Q., Chen, L., Huang, H., Yu, R., & Huang, R. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102797 · Cited by 9 · see citing works
Propagations of spontaneous brain activity in awake rats
Liu, Y., & Zhang, N. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116176 · Cited by 9 · see citing works
Seitzman, B. A., Reynoso, F. J., Mitchell, T. J., Bice, A. R., Jarang, A., Wang, X., Mpoy, C., Strong, L., Rogers, B. E., Yuede, C. M., et al. (2023) · GeroScience · doi:10.1007/s11357-023-00944-w · Cited by 8 · see citing works
Self-citation
- Authors
- Mitra, A., Kraft, A., Wright, P., Acland, B., Snyder, A. Z., Rosenthal, Z., Czerniewski, L., Bauer, A., Snyder, L., Culver, J., Lee, J.-M., & Raichle, M. E.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Mitra, Anish
- ORCID
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 98
- Issue
- 2
- Pages
- 297-305.e6
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC5910292
- OpenAlex
- W2794779684
- Cited by
- 193
- References
- 41
- Citations by year
- 2026: 17 · 2025: 14 · 2024: 22 · 2023: 18 · 2022: 21 · 2021: 18 · 2020: 30 · 2019: 32 · 2018: 20 · 2017: 1
- FWCI
- 14.86
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (F30MH106253, NS080675, R01NS084028, R01NS085419, R01NS094692, F31NS089135, MH102471, R01 NS099429, R01 NS078223)
- McDonnell Center for Systems Neuroscience
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- spontaneous neuronal activity, spatiotemporal dynamics, delta oscillations, local field potentials, blood oxygenation, calcium imaging, wakefulness, mouse cortex
- MeSH terms
- Anesthesia, Animals, Brain, Brain Mapping, Magnetic Resonance Imaging, Mice, Inbred C57BL, Mice, Transgenic, Time Factors, Wakefulness, Mice, 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.
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 ›
Are you an author, or do you see a problem with this page? Request a review