Rhythms of the Brain
Abstract
Studies of mechanisms in the brain that allow complicated things to happen in a coordinated fashion have produced some of the most spectacular discoveries in neuroscience. This book provides support for the idea that spontaneous neuron activity, far from being mere noise, is actually the source of our cognitive abilities. It looks at the co-evolution of structure and function in the mammalian brain, illustrating how self-emerged oscillatory timing is the brains fundamental organizer of neuronal information. The small world-like connectivity of the cerebral cortex allows for global computation on multiple spatial and temporal scales. The perpetual interactions among the multiple network oscillators keep cortical systems in a highly sensitive metastable state and provide energy-efficient synchronizing mechanisms via weak links. In a sequence of cycles, this book travels from the physics of oscillations through neuronal assembly organization to complex cognitive processing and memory storage.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Sharp tuning curves and bistable activity patterns are observed across cortical regions.
“a pattern seen in the sharp tuning curves and bistable activity patterns observed across cortical regions (Buzsáki 2006; Isaacson and Scanziani 2011).”
From The myth of the Bayesian brain (2025) · cites this paper as Buzsáki 2006
The prevalence of inhibitory interneurons creates winner-take-all dynamics and competitive inhibition that force categorical rather than probabilistic representations.
“Furthermore, the prevalence of inhibitory interneurons creates winner-take-all dynamics and competitive inhibition that force categorical rather than probabilistic representations—a pattern seen in the sharp tuning curves and bistable activity patterns observed across cortical regions (Buzsáki 2006; Isaacson and Scanziani 2011).”
From The myth of the Bayesian brain (2025) · cites this paper as Buzsáki 2006
Several brain systems continually work together in an extremely flexible organization, with structurally different neural tissue involved in temporarily assembled neural circuits for a given task.
“Under normal circumstances, several brain systems are continually working together (Buzsáki, 2006), showing an extremely flexible organization with structurally different neural tissue being involved in neural circuits that are only temporarily assembled so as to enable a given task (Edelman and Gally, 2013; Van der Weel et al., 2019).”
From Handwriting but not typewriting leads to widespread brain connectivity: a high-density EEG study with implications for the classroom (2024) · cites this paper as Buzsáki, 2006
Neurobiological mechanisms and neurotransmitter systems, including dopamine, norepinephrine, serotonin, acetylcholine, the HPA axis, and neural oscillations, provide substrates for adaptability and resilience.
“Neurobiological mechanisms and neurotransmitter systems ranging from neurotransmitter regulation, like, dopamine, norepinephrine, serotonin, and acetylcholine to stress physiology related to hypothalamic-pituarity-adrenal axis or HPA axis and neural oscillations—provide the substrates for adaptability and resilience (Buzsáki, 2006; McEwen, 2007; Robbins and Arnsten, 2009).”
From Enhancement of modern defense capabilities by convergence of cognitive neuroscience and artificial intelligence (2026) · cites this paper as Buzsáki, 2006
Brain rhythms in theta, alpha, and gamma bands coordinate large-scale attention, memory, and rapid response, supporting memory encoding, attentional gating, and rapid response coordination.
“Brain rhythms in the theta, alpha, and gamma bands coordinate large-scale coordination of attention, memory, and rapid response (Buzsáki, 2006), communication, supporting functions such as memory encoding, attentional gating, and rapid response coordination.”
From Enhancement of modern defense capabilities by convergence of cognitive neuroscience and artificial intelligence (2026) · cites this paper as Buzsáki, 2006
Ripples arise from an interaction between inhibitory interneurons and pyramidal cells via synaptic (glutamatergic, GABAergic) connections and gap junctions.
“Ripples arise from an interaction between inhibitory interneurons and pyramidal cells via synaptic (glutamatergic, GABAergic) connections and gap junctions (162).”
From About Sleep's Role in Memory (2013) · cites this paper as [162]
SW-Rs occur mainly during SWS but also during nonexploratory wakefulness.
“SW-Rs occur mainly during SWS but also during nonexploratory wakefulness (e.g., drinking, grooming, and quiet wakefulness).”
From About Sleep's Role in Memory (2013) · cites this paper as [162]
Theta and gamma oscillations often co-vary and may be phase-locked in different areas of cortex.
“For example, it has been observed that theta and gamma oscillations often co-vary and may be phase-locked in different areas of cortex (Buzsáki, 2006; Klimesch, Freunberger, & Sauseng, 2010).”
From Brain oscillations, hypnosis, and hypnotizability (2015) · cites this paper as Buzsáki, 2006
Slower oscillations (delta, theta, alpha) tend to be common signals among large groups of neurons spread over larger areas of the brain, likely cortico-thalamic networks, whereas faster oscillations (beta, gamma) tend to reflect regional activity, mostly cortico-cortical, primarily due to conduction delays of axons.
“For example, slower oscillations (e.g., delta, theta, and alpha) tend to be the common signals among large groups of neurons spread out over larger areas of the brain (likely cortico-thalamic networks), whereas faster oscillations (e.g., beta and gamma) tend to reflect regional activity (mostly cortico-cortical), primarily due to the limitations associated with the conduction delays of axons (Buzs”
From Brain oscillations, hypnosis, and hypnotizability (2015) · cites this paper as Buzsáki, 2006
The most commonly identified role for theta is enhancing declarative memory coding and retrieval.
“the most commonly identified role for theta, as discussed earlier in this paper, is for enhancing declarative memory coding and retrieval (Bastiaansen & Hagoort, 2003; Buzsáki, 2006; Klimesch, 1999; Klimesch, et al., 2010; Paré, et al., 2002).”
From Brain oscillations, hypnosis, and hypnotizability (2015) · cites this paper as Buzsáki, 2006
Cited by
Sorted by citations
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820 · see citing works
The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes
Buzsáki, G., Anastassiou, C. A., & Koch, C. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3241 · Cited by 4,225 · see citing works
Self-citationDiekelmann, S., & Born, J. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2762 · Cited by 3,760 · see citing works
Shaping Functional Architecture by Oscillatory Alpha Activity: Gating by Inhibition
Jensen, O., & Mazaheri, A. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00186 · Cited by 3,237 · see citing works
Alpha-band oscillations, attention, and controlled access to stored information
Klimesch, W. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.10.007 · Cited by 3,310 · see citing works
Dynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Della Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.079 · Cited by 2,962 · see citing works
Rasch, B., & Born, J. (2013) · Physiological Reviews · doi:10.1152/physrev.00032.2012 · Cited by 2,783 · see citing works
Efficiency and Cost of Economical Brain Functional Networks
Achard, S., & Bullmore, E. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030017 · Cited by 2,553 · see citing works
On the relationship between emotion and cognition
Pessoa, L. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2317 · Cited by 2,350 · see citing works
Abnormal neural oscillations and synchrony in schizophrenia
Uhlhaas, P. J., & Singer, W. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2774 · Cited by 2,120 · see citing works
Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning
Buzsáki, G. (2015) · Hippocampus · doi:10.1002/hipo.22488 · Cited by 1,759 · see citing works
Self-citationNeuronal gamma-band synchronization as a fundamental process in cortical computation
Fries, P. (2009) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.051508.135603 · Cited by 1,713 · see citing works
Intrinsic and task-evoked network architectures of the human brain
Cole, M. W., Bassett, D. S., Power, J. D., Braver, T. S., & Petersen, S. E. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.014 · Cited by 1,564 · see citing works
The role of phase synchronization in memory processes
Fell, J., & Axmacher, N. (2011) · Nature Reviews Neuroscience · doi:10.1038/nrn2979 · Cited by 1,620 · see citing works
The theory of constructed emotion: an active inference account of interoception and categorization
Barrett, L. F. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw154 · Cited by 1,426 · see citing works
Modulation of Neuronal Interactions Through Neuronal Synchronization
Womelsdorf, T., Schoffelen, J.-M., Oostenveld, R., Singer, W., Desimone, R., Engel, A. K., & Fries, P. (2007) · Science · doi:10.1126/science.1139597 · Cited by 1,367 · see citing works
Competition between functional brain networks mediates behavioral variability
Kelly, A. M. C., Uddin, L. Q., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.008 · Cited by 1,287 · see citing works
Gamma frequency entrainment attenuates amyloid load and modifies microglia
Iaccarino, H. F., Singer, A. C., Martorell, A. J., Rudenko, A., Gao, F., Gillingham, T. Z., Mathys, H., Seo, J., Kritskiy, O., Abdurrob, F., et al. (2016) · Nature · doi:10.1038/nature20587 · Cited by 1,328 · see citing works
Neural syntax: cell assemblies, synapsembles, and readers
Buzsáki, G. (2010) · Neuron · doi:10.1016/j.neuron.2010.09.023 · Cited by 1,289 · see citing works
Self-citationEmergent complex neural dynamics
Chialvo, D. R. (2010) · Nature Physics · doi:10.1038/nphys1803 · Cited by 1,165 · see citing works
Manning, J. R., Jacobs, J., Fried, I., & Kahana, M. J. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.2041-09.2009 · Cited by 973 · see citing works
The Temporal Structures and Functional Significance of Scale-free Brain Activity
He, B. J., Zempel, J. M., Snyder, A. Z., & Raichle, M. E. (2010) · Neuron · doi:10.1016/j.neuron.2010.04.020 · Cited by 990 · see citing works
Magnetoencephalography for Brain Electrophysiology and Imaging
Baillet, S. (2017) · Nature Neuroscience · doi:10.1038/nn.4504 · Cited by 992 · see citing works
Entrainment of Neocortical Neurons and Gamma Oscillations by the Hippocampal Theta Rhythm
Sirota, A., Montgomery, S., Fujisawa, S., Isomura, Y., Zugaro, M., & Buzsáki, G. (2008) · Neuron · doi:10.1016/j.neuron.2008.09.014 · Cited by 1,015 · see citing works
Self-citationTheta-gamma coupling increases during the learning of item-context associations
Tort, A. B. L., Komorowski, R. W., Manns, J. R., Kopell, N. J., & Eichenbaum, H. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911331106 · Cited by 919 · see citing works
EEG and MEG: Relevance to Neuroscience
Lopes da Silva, F. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.017 · Cited by 900 · see citing works
The theory of constructed emotion: an active inference account of interoception and categorization
Barrett, L. F. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx060 · Cited by 950 · see citing works
“11 Notably, Buzs aki (2006) wrote that ‘Brains are foretelling devices’.”
Waking state: rapid variations modulate neural and behavioral responses
McGinley, M. J., Vinck, M., Reimer, J., Batista-Brito, R., Zagha, E., Cadwell, C. R., Tolias, A. S., Cardin, J. A., & McCormick, D. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.012 · Cited by 801 · see citing works
“Transitions from locomotion to quiescence, or from externally oriented movements (e.g. exploration) towards internally oriented movements (e.g. grooming, consuming) are associated with a rapid decrease of theta activity in the hippocampus (Buzsaki, 2006; Buzsaki et al., 2003).”
InfluentialPupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex
Reimer, J., McGinley, M. J., Liu, Y., Rodenkirch, C., Wang, Q., McCormick, D. A., & Tolias, A. S. (2016) · Nature Communications · doi:10.1038/ncomms13289 · Cited by 926 · see citing works
Mechanisms underlying selective neuronal tracking of attended speech at a “cocktail party”
Zion Golumbic, E. M., Ding, N., Bickel, S., Lakatos, P., Schevon, C. A., McKhann, G. M., Goodman, R. R., Emerson, R., Mehta, A. D., Simon, J. Z., et al. (2013) · Neuron · doi:10.1016/j.neuron.2012.12.037 · Cited by 909 · see citing works
Endogenous electric fields may guide neocortical network activity
Fröhlich, F., & McCormick, D. A. (2010) · Neuron · doi:10.1016/j.neuron.2010.06.005 · Cited by 913 · see citing works
Viewpoints: how the hippocampus contributes to memory, navigation and cognition
Lisman, J., Buzsáki, G., Eichenbaum, H., Nadel, L., Ranganath, C., & Redish, A. D. (2017) · Nature Neuroscience · doi:10.1038/nn.4661 · Cited by 851 · see citing works
Self-citationThe functional significance of delta oscillations in cognitive processing
Harmony, T. (2013) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2013.00083 · Cited by 788 · see citing works
Cross-Frequency Phase–Phase Coupling between Theta and Gamma Oscillations in the Hippocampus
Belluscio, M. A., Mizuseki, K., Schmidt, R., Kempter, R., & Buzsáki, G. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.4122-11.2012 · Cited by 784 · see citing works
Self-citationTognoli, E., & Kelso, J. A. S. (2014) · Neuron · doi:10.1016/j.neuron.2013.12.022 · Cited by 718 · see citing works
Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging
Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W.-J., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.068 · Cited by 739 · see citing works
GABAergic Hub Neurons Orchestrate Synchrony in Developing Hippocampal Networks
Bonifazi, P., Goldin, M., Picardo, M. A., Jorquera, I., Cattani, A., Bianconi, G., Represa, A., Ben-Ari, Y., & Cossart, R. (2009) · Science · doi:10.1126/science.1175509 · Cited by 695 · see citing works
Mizuseki, K., Sirota, A., Pastalkova, E., & Buzsáki, G. (2009) · Neuron · doi:10.1016/j.neuron.2009.08.037 · Cited by 718 · see citing works
Self-citationRevealing neuronal function through microelectrode array recordings
Obien, M. E. J., Deligkaris, K., Bullmann, T., Bakkum, D. J., & Frey, U. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00423 · Cited by 705 · see citing works
Promises and limitations of human intracranial electroencephalography
Parvizi, J., & Kastner, S. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0108-2 · Cited by 631 · see citing works
The contribution of sleep to hippocampus-dependent memory consolidation
Marshall, L., & Born, J. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.09.001 · Cited by 667 · see citing works
Theta lingua franca: A common mid‐frontal substrate for action monitoring processes
Cavanagh, J. F., Zambrano‐Vazquez, L., & Allen, J. J. B. (2012) · Psychophysiology · doi:10.1111/j.1469-8986.2011.01293.x · Cited by 651 · see citing works
Craig, A. D. (. (2010) · Brain Structure and Function · doi:10.1007/s00429-010-0248-y · Cited by 600 · see citing works
Mechanisms and functions of theta rhythms
Colgin, L. L. (2013) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062012-170330 · Cited by 559 · see citing works
Development of Anterior Cingulate Functional Connectivity from Late Childhood to Early Adulthood
Kelly, A. M. C., Di Martino, A., Uddin, L. Q., Shehzad, Z., Gee, D. G., Reiss, P. T., Margulies, D. S., Castellanos, F. X., & Milham, M. P. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn117 · Cited by 572 · see citing works
The default-mode, ego-functions and free-energy: a neurobiological account of Freudian ideas
Carhart-Harris, R. L., & Friston, K. J. (2010) · Brain · doi:10.1093/brain/awq010 · Cited by 574 · see citing works
Buzsáki, G., & Watson, B. O. (2012) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2012.14.4/gbuzsaki · Cited by 579 · see citing works
Self-citationFrontal-midline theta from the perspective of hippocampal “theta”
Mitchell, D. J., McNaughton, N., Flanagan, D., & Kirk, I. J. (2008) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2008.09.005 · Cited by 549 · see citing works
A New Unifying Account of the Roles of Neuronal Entrainment
Lakatos, P., Gross, J., & Thut, G. (2019) · Current Biology · doi:10.1016/j.cub.2019.07.075 · Cited by 508 · see citing works
Space in the brain: How the hippocampal formation supports spatial cognition
Hartley, T., Lever, C., Burgess, N., & O'Keefe, J. (2014) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2012.0510 · Cited by 495 · see citing works
Theta power as a marker for cognitive interference
Nigbur, R., Ivanova, G., & Stürmer, B. (2011) · Clinical Neurophysiology · doi:10.1016/j.clinph.2011.03.030 · Cited by 482 · see citing works
Space and Time: The Hippocampus as a Sequence Generator
Buzsáki, G., & Tingley, D. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.07.006 · Cited by 461 · see citing works
Self-citationDefining Agency: Individuality, Normativity, Asymmetry, and Spatio-temporality in Action
Barandiaran, X. E., Di Paolo, E., & Rohde, M. (2009) · Adaptive Behavior · doi:10.1177/1059712309343819 · Cited by 497 · see citing works
Neuronal Mechanisms and Attentional Modulation of Corticothalamic Alpha Oscillations
Bollimunta, A., Mo, J., Schroeder, C. E., & Ding, M. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.5580-10.2011 · Cited by 441 · see citing works
Brain reward circuitry beyond the mesolimbic dopamine system: a neurobiological theory
Ikemoto, S. (2010) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2010.02.001 · Cited by 454 · see citing works
Measuring consciousness: relating behavioural and neurophysiological approaches
Seth, A. K., Dienes, Z., Cleeremans, A., Overgaard, M., & Pessoa, L. (2008) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2008.04.008 · Cited by 458 · see citing works
Cognitive effort drives workspace configuration of human brain functional networks
Kitzbichler, M. G., Henson, R. N. A., Smith, M. L., Nathan, P. J., & Bullmore, E. T. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.0440-11.2011 · Cited by 427 · see citing works
Converging Intracranial Markers of Conscious Access
Gaillard, R., Dehaene, S., Adam, C., Clémenceau, S., Hasboun, D., Baulac, M., Cohen, L., & Naccache, L. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000061 · Cited by 440 · see citing works
The phi complex as a neuromarker of human social coordination
Tognoli, E., Lagarde, J., DeGuzman, G. C., & Kelso, J. A. S. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0611453104 · Cited by 437 · see citing works
Neuronal Mechanisms of Cortical Alpha Oscillations in Awake-Behaving Macaques
Bollimunta, A., Chen, Y., Schroeder, C. E., & Ding, M. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.2699-08.2008 · Cited by 434 · see citing works
BCILAB: a platform for brain–computer interface development
Kothe, C. A., & Makeig, S. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/5/056014 · Cited by 412 · see citing works
D'Angelo, E., & Casali, S. (2013) · Frontiers in Neural Circuits · doi:10.3389/fncir.2012.00116 · Cited by 407 · see citing works
Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing
Jensen, O., Gips, B., Bergmann, T. O., & Bonnefond, M. (2014) · Trends in Neurosciences · doi:10.1016/j.tins.2014.04.001 · Cited by 389 · see citing works
Exploring the network dynamics underlying brain activity during rest
Cabral, J., Kringelbach, M. L., & Deco, G. (2014) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2013.12.005 · Cited by 351 · see citing works
Respiration-Entrained Brain Rhythms Are Global but Often Overlooked
Tort, A. B. L., Brankačk, J., & Draguhn, A. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.01.007 · Cited by 335 · see citing works
Layer-Specific Entrainment of Gamma-Band Neural Activity by the Alpha Rhythm in Monkey Visual Cortex
Spaak, E., Bonnefond, M., Maier, A., Leopold, D. A., & Jensen, O. (2012) · Current Biology · doi:10.1016/j.cub.2012.10.020 · Cited by 385 · see citing works
Role of myelin plasticity in oscillations and synchrony of neuronal activity
Pajevic, S., Basser, P. J., & Fields, R. D. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2013.11.007 · Cited by 378 · see citing works
Neuromodulation 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
Sadaghiani, S., Hesselmann, G., & Kleinschmidt, A. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.2592-09.2009 · Cited by 325 · see citing works
Mölle, M., Eschenko, O., Gais, S., Sara, S. J., & Born, J. (2009) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2009.06654.x · Cited by 322 · see citing works
Sleep benefits subsequent hippocampal functioning
Van Der Werf, Y. D., Altena, E., Schoonheim, M. M., Sanz-Arigita, E. J., Vis, J. C., De Rijke, W., & Van Someren, E. J. W. (2009) · Nature Neuroscience · doi:10.1038/nn.2253 · Cited by 313 · see citing works
Using network science to evaluate exercise-associated brain changes in older adults.
Burdette (2010) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2010.00023 · Cited by 320 · see citing works
Kann, O., Papageorgiou, I. E., & Draguhn, A. (2014) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2014.104 · Cited by 295 · see citing works
Neural correlates of the DMT experience assessed with multivariate EEG
Timmermann, C., Roseman, L., Schartner, M., Milliere, R., Williams, L. T. J., Erritzoe, D., Muthukumaraswamy, S., Ashton, M., Bendrioua, A., Kaur, O., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-51974-4 · Cited by 315 · see citing works
The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging
Ritter, P., Schirner, M., McIntosh, A. R., & Jirsa, V. K. (2013) · Brain Connectivity · doi:10.1089/brain.2012.0120 · Cited by 268 · see citing works
Should a Few Null Findings Falsify Prefrontal Theories of Conscious Perception?
Odegaard, B., Knight, R. T., & Lau, H. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3217-16.2017 · Cited by 316 · see citing works
Ito, J., Roy, S., Liu, Y., Cao, Y., Fletcher, M., Lu, L., Boughter, J. D., Grün, S., & Heck, D. H. (2014) · Nature Communications · doi:10.1038/ncomms4572 · Cited by 252 · see citing works
Hyder, F., Rothman, D. L., & Bennett, M. R. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1214912110 · Cited by 271 · see citing works
Interaction between neocortical and hippocampal networks via slow oscillations
Sirota, A., & Buzsáki, G. (2005) · Thalamus and Related Systems · doi:10.1017/s1472928807000258 · Cited by 270 · see citing works
Self-citationCowey, A. (2010) · Experimental Brain Research · doi:10.1007/s00221-009-1914-2 · Cited by 279 · see citing works
Gandal, M. J., Edgar, J. C., Klook, K., & Siegel, S. J. (2012) · Neuropharmacology · doi:10.1016/j.neuropharm.2011.02.007 · Cited by 269 · see citing works
Early Gamma Oscillations Synchronize Developing Thalamus and Cortex
Minlebaev, M., Colonnese, M., Tsintsadze, T., Sirota, A., & Khazipov, R. (2011) · Science · doi:10.1126/science.1210574 · Cited by 257 · see citing works
Postnatal Differentiation of Basket Cells from Slow to Fast Signaling Devices
Doischer, D., Aurel Hosp, J., Yanagawa, Y., Obata, K., Jonas, P., Vida, I., & Bartos, M. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.2890-08.2008 · Cited by 248 · see citing works
Motor cortex feedback influences sensory processing by modulating network state
Zagha, E., Casale, A. E., Sachdev, R. N. S., McGinley, M. J., & McCormick, D. A. (2013) · Neuron · doi:10.1016/j.neuron.2013.06.008 · Cited by 268 · see citing works
Common medial frontal mechanisms of adaptive control in humans and rodents
Narayanan, N. S., Cavanagh, J. F., Frank, M. J., & Laubach, M. (2013) · Nature Neuroscience · doi:10.1038/nn.3549 · Cited by 267 · see citing works
Ekstrom, A. D., Arnold, A. E. G. F., & Iaria, G. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00803 · Cited by 263 · see citing works
GABAergic interneurons targeting dendrites of pyramidal cells in the CA1 area of the hippocampus
Klausberger, T. (2009) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2009.06913.x · Cited by 260 · see citing works
Dynamic Stimulation of Visual Cortex Produces Form Vision in Sighted and Blind Humans
Beauchamp, M. S., Oswalt, D., Sun, P., Foster, B. L., Magnotti, J. F., Niketeghad, S., Pouratian, N., Bosking, W. H., & Yoshor, D. (2020) · Cell · doi:10.1016/j.cell.2020.04.033 · Cited by 257 · see citing works
Uhlhaas, P. J., & Singer, W. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.11.019 · Cited by 243 · see citing works
Glial Biology in Learning and Cognition
Fields, R. D., Araque, A., Johansen-Berg, H., Lim, S.-S., Lynch, G., Nave, K.-A., Nedergaard, M., Perez, R., Sejnowski, T., & Wake, H. (2014) · The Neuroscientist · doi:10.1177/1073858413504465 · Cited by 232 · see citing works
From Creation to Consolidation: A Novel Framework for Memory Processing
Robertson, E. M. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000019 · Cited by 236 · see citing works
Tasks for inhibitory interneurons in intact brain circuits
Roux, L., & Buzsáki, G. (2015) · Neuropharmacology · doi:10.1016/j.neuropharm.2014.09.011 · Cited by 218 · see citing works
Self-citationElastocapillary self-assembled neurotassels for stable neural activity recordings
Guan, S., Wang, J., Gu, X., Zhao, Y., Hou, R., Fan, H., Zou, L., Gao, L., Du, M., Li, C., et al. (2019) · Science Advances · doi:10.1126/sciadv.aav2842 · Cited by 222 · see citing works
Practical Measures of Integrated Information for Time-Series Data
Barrett, A. B., & Seth, A. K. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001052 · Cited by 225 · see citing works
Sharp edge artifacts and spurious coupling in EEG frequency comodulation measures
Kramer, M. A., Tort, A. B. L., & Kopell, N. J. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.01.020 · Cited by 195 · see citing works
Plasticity of local GABAergic interneurons drives olfactory habituation
Das, S., Sadanandappa, M. K., Dervan, A., Larkin, A., Lee, J. A., Sudhakaran, I. P., Priya, R., Heidari, R., Holohan, E. E., Pimentel, A., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1106411108 · Cited by 219 · see citing works
Fine‐tuned coupling between human parahippocampal ripples and sleep spindles
Clemens, Z., Mölle, M., Erőss, L., Jakus, R., Rásonyi, G., Halász, P., & Born, J. (2011) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2010.07505.x · Cited by 214 · see citing works
Genetically encoded optical indicators for the analysis of neuronal circuits
Knöpfel, T. (2012) · Nature reviews. Neuroscience · doi:10.1038/nrn3293 · Cited by 205 · see citing works
Axmacher, N., Schmitz, D. P., Wagner, T., Elger, C. E., & Fell, J. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.1778-08.2008 · Cited by 204 · see citing works
Gamma-phase shifting in awake monkey visual cortex
Vinck, M., Lima, B., Womelsdorf, T., Oostenveld, R., Singer, W., Neuenschwander, S., & Fries, P. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.1623-09.2010 · Cited by 189 · see citing works
- Authors
- Buzsáki, G.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- Corresponding author
- Buzsáki, György
- ORCID
- Buzsáki, György
- Venue
- Oxford University Press eBooks
- Publisher
- Oxford University Press
- Published
- 2006-10-26
- OpenAlex
- W2127389037
- Cited by
- 4,873
- References
- 0
- Citations by year
- 2026: 203 · 2025: 261 · 2024: 194 · 2023: 204 · 2022: 247 · 2021: 325 · 2020: 276 · 2019: 297 · 2018: 291 · 2017: 267 · 2016: 281 · 2015: 297 · 2014: 305 · 2013: 309 · 2012: 259
- FWCI
- 36.35
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Computer Science › Computer Networks and Communications › Nonlinear Dynamics and Pattern Formation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- spontaneous neuronal activity, neural oscillations, cerebral cortex, metastability, weak links, energy efficiency, cell assemblies, memory storage, cognitive processes
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
