Abstract
Alpha-band activity is the most prominent neurobiological feature of scalp electroencephalography (EEG) signals, recent findings showed that there is more than one alpha rhythm coexisted in this 8-13 Hz band, but the generation mechanism of them was not fully understood. To address this question, we collected local field potential (LFP) in 32 brain regions of human brain with stereo-EEG (SEEG), with simultaneously recording with EEG during the process from awaked state (eyes-closed) to loss of consciousness (LOC) state with anesthesia. Our study revealed a prominent low-alpha (LA) rhythm (8-10 Hz) localized in the occipital region during the awake, eyes-closed state. As anesthetic depth increased leading to the LOC, this low-alpha rhythm gradually diminished and was replaced by a globally distributed high-alpha (HA) rhythm (10-13 Hz). This phenomenon was consistently observed at both LFP and EEG levels. Furthermore, we demonstrated that state-dependent changes of oscillatory property in alpha band were primarily driven by periodic rather than aperiodic activities, which could be also effectively explained by a simple dynamical model. This work provides the first evidence of anesthetic-induced modulation mechanisms underlying the generation and regulation of distinct alpha oscillations, offering valuable insights for future research in anesthesia, consciousness studies, and potential clinical applications.
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Data availability
The raw datasets are available upon reasonable request to the corresponding authors. The numerical source data for plots underlying graphs in the manuscript can be found in Supplementary data file (Supplementary Data 1).
Code availability
The analysis codes are available upon reasonable request to the corresponding authors.
References
Buzsáki, G. Rhythms of the Brain (Oxford University Press, 2009).
Buzsáki, G. & Vöröslakos, M. Brain rhythms have come of age. Neuron 111, 922–926 (2023).
Buzsáki, G., Logothetis, N. & Singer, W. Scaling brain size, keeping timing: evolutionary preservation of brain rhythms. Neuron. 80, 751–764 (2013).
Brunet, N., Vinck, M., Bosman, C. A., Singer, W. & Fries, P. Gamma or no gamma, that is the question. Trends Cogn. Sci. 18, 507–509 (2014).
Jensen, O., Kaiser, J. & Lachaux, J. P. Human gamma-frequency oscillations associated with attention and memory. Trends Neurosci. 30, 317–324 (2007).
Bosman, C. A., Womelsdorf, T., Desimone, R. & Fries, P. A microsaccadic rhythm modulates gamma-band synchronization and behavior. J. Neurosci. 29, 9471–9480 (2009).
Wang, J. et al. Executive function elevated by long term high-intensity physical activity and the regulation role of beta-band activity in human frontal region. Cogn. Neurodyn. 1–10 (2022) https://doi.org/10.1007/S11571-022-09905-Z/FIGURES/6.
Liu, X. et al. Neural circuit underlying individual differences in visual escape habituation. Neuron https://doi.org/10.1016/J.NEURON.2025.04.018 (2025)
Fernández-Ruiz, A. et al. Gamma rhythm communication between entorhinal cortex and dentate gyrus neuronal assemblies. Science 372, (2021).
Han, C. et al. Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex. PLoS Biol. 1–23 (2021) https://doi.org/10.1371/journal.pbio.3001466.
Samaha, J., Bauer, P., Cimaroli, S. & Postle, B.R. Top-down control of the phase of alpha-band oscillations as a mechanism for temporal prediction. Proc. Natl. Acad. Sci. USA https://doi.org/10.1073/pnas.1503686112 (2015)
Lou, B., Li, Y., Philiastides, M. G. & Sajda, P. Prestimulus alpha power predicts fidelity of sensory encoding in perceptual decision making. Neuroimage https://doi.org/10.1016/j.neuroimage.2013.10.041 (2014)
Roberts, D. M., Fedota, J. R., Buzzell, G. A., Parasuraman, R. & McDonald, C. G. Prestimulus Oscillations in the alpha band of the EEG are modulated by the difficulty of feature discrimination and predict activation of a sensory discrimination process. J. Cogn. Neurosci. https://doi.org/10.1162/jocn_a_00569 (2014)
Cardin, J. A. et al. Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459, 663–667 (2009).
Martorell, A. J. et al. Multi-sensory gamma stimulation ameliorates Alzheimer’s-associated pathology and improves cognition. Cell 177, 256–271.e22 (2019).
Han, C. et al. Neural mechanism of orientation selectivity for distinct gamma oscillations in cat V1. J. Vis. 20, 1116 (2020).
Han, C. et al. The generation and modulation of distinct gamma oscillations with local, horizontal, and feedback connections in the primary visual cortex: a model study on large-scale networks. Neural Plast. 2021, 8874516 (2021).
Han, C. et al. Enhancement of the neural response during 40 Hz auditory entrainment in closed-eye state in human prefrontal region. Cogn. Neurodyn. https://doi.org/10.1007/s11571-022-09834-x (2022) .
Mashour, G. A. Consciousness, anesthesia, and neural synchrony. Anesthesiology 119, 7–9 (2013).
Singer, W. Consciousness and the binding problem. Ann. N.Y. Acad. Sci. (2001). https://doi.org/10.1111/j.1749-6632.2001.tb05712.x.
Purdon, P. L. et al. Electroencephalogram signatures of loss and recovery of consciousness from propofol. Proc. Natl. Acad. Sci. USA 110, (2013).
Ferrarelli, F. et al. Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness. Proc. Natl. Acad. Sci. USA 107, 2681–2686 (2010).
Fiset, P. et al. Brain mechanisms of propofol-induced loss of consciousness in humans: a positron emission tomographic study. J. Neurosci. 19, 5506–5513 (1999).
Ge, D., Han, C., Liu, C. & Meng, Z. Neural oscillations in the somatosensory and motor cortex distinguish dexmedetomidine-induced anesthesia and sleep in rats. CNS Neurosci. Ther. 31, (2025).
Hight, D. & Sleigh, J. Consciousness and the outside world: is there anyone listening? Br. J. Anaesth. 128, 895–897 (2022).
Zelmann, R. et al. Differential cortical network engagement during states of un/consciousness in humans. Neuron 111, 3479–3495.e6 (2023).
Adam, E., Kwon, O., Montejo, K. A. & Brown, E. N. Modulatory dynamics mark the transition between anesthetic states of unconsciousness. https://doi.org/10.1073/pnas (2023)
Pal, D. & Mashour, G. A. General anesthesia and the cortical stranglehold on consciousness. Neuron 110, 1891–1893 (2022).
Bazanova, O. M. & Vernon, D. Interpreting EEG alpha activity. Neuroscience and Biobehavioral Reviews 44, 94–110 (2014).
Klimesch, W., Sauseng, P. & Hanslmayr, S. EEG alpha oscillations: The inhibition-timing hypothesis. Brain Res. Rev. 53, 63–88 (2007).
Hindriks, R., van Putten, M. J. A. M. & Deco, G. Intra-cortical propagation of EEG alpha oscillations. Neuroimage 103, 444–453 (2014).
Tröndle, M., Popov, T., Dziemian, S. & Langer, N. Decomposing the role of alpha oscillations during brain maturation. Elife 11, e77571 (2022).
Vijayan, S. & Kopell, N. J. Thalamic model of awake alpha oscillations and implications for stimulus processing. Proc. Natl. Acad. Sci. USA 109, 18553–18558 (2012).
Halgren, M. et al. The generation and propagation of the human alpha rhythm. Proc. Natl. Acad. Sci. USA 116, 23772–23782 (2019).
Berger, H. Über das Elektrenkephalogramm des Menschen. Arch. Psychiatr. Nervenkr https://doi.org/10.1007/BF01797193 (1929).
Babiloni, C. et al. Alpha rhythm and Alzheimer’s disease: has Hans Berger’s dream come true?. Clin. Neurophysiol. 172, 33–50 (2025).
Nestvogel, D. B. & McCormick, D. A. Visual thalamocortical mechanisms of waking state-dependent activity and alpha oscillations. Neuron 110, 120–138.e4 (2022).
Cantero, J. L., Atienza, M., Gómez, C. & Salas, R. M. Spectral structure and brain mapping of human alpha activities in different arousal states. Neuropsychobiology 39, 110–116 (1999).
Han, C., Cheung, V. C. K. & Chan, R. H. M. Aging amplifies sex differences in low alpha and low beta EEG oscillations. Neuroimage 312, 121231 (2025).
Zikereya, T. et al. Different oscillatory mechanisms of dementia-related diseases with cognitive impairment in closed-eye state. Neuroimage 304, 120945. https://doi.org/10.1016/J.NEUROIMAGE.2024.120945 (2024).
Liu, P. et al. Alterations of oscillatory activity and cognitive function after aneurysmal subarachnoid hemorrhage. Int. J. Surg. https://doi.org/10.1097/JS9.0000000000002190 (2024).
Rihs, T. A., Michel, C. M. & Thut, G. A bias for posterior alpha-band power suppression versus enhancement during shifting versus maintenance of spatial attention. Neuroimage 44, 190–199 (2009).
Jensen, O. & Mazaheri, A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front Hum. Neurosci. 4, 2008 (2010).
Lorincz, M. L., Kékesi, K. A., Juhász, G., Crunelli, V. & Hughes, S. W. Temporal framing of thalamic relay-mode firing by phasic inhibition during the alpha rhythm. Neuron 63, 683–696 (2009).
Han, C. et al. Oscillatory biomarkers of autism: evidence from the innate visual fear evoking paradigm. Cogn. Neurodyn. 6, (2022).
Lin, Y. et al. The neural oscillatory mechanism underlying human brain fingerprint recognition using a portable EEG acquisition device. Neuroimage 294, 120637. https://doi.org/10.1016/J.NEUROIMAGE.2024.120637 (2024).
Zhang, Y. et al. Shared oscillatory mechanisms of alpha-band activity in prefrontal regions in eyes open and closed state using a portable EEG acquisition device. Sci. Rep. 14, 26719 (2024).
Shi, K. et al. Distinct mechanisms of multiple alpha-band activities in frontal regions following an 8-week medium- (Yoga) and high-intensity (Pamela) exercise intervention. CNS Neurosci. Ther. 31, e70405 (2025).
Zhang, Z. & Han, C. High alpha-band activity of prefrontal cortex contributes to the significant neural alterations in the initial two-month phase of a romantic relationship. https://doi.org/10.21203/RS.3.RS-5835787/V1 (2025).
Zhao, X. et al. Distinguishing major depressive disorder from bipolar disorder using alpha-band activity in resting-state electroencephalogram. J. Affect. Disord. 376, 333–340 (2025).
Wang, B. et al. Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB). J. Affect. Disord. 355, 254–264 (2024).
Han, C. et al. Monitoring sleep quality through low α-band activity in the prefrontal cortex using a portable electroencephalogram device: longitudinal study. J. Med. Internet Res. 27, e67188 (2025).
Han, C. et al. Compensatory mechanism of attention-deficit/hyperactivity disorder recovery in resting state alpha rhythms. Front. Comput. Neurosci. 1–10 https://doi.org/10.3389/fncom.2022.883065 (2022).
Barzegaran, E., Vildavski, V. Y. & Knyazeva, M. G. Fine structure of posterior alpha rhythm in human EEG: frequency components, their cortical sources, and temporal behavior. Sci. Rep. 7, 1–12 (2017).
Jia, J., Fang, F. & Luo, H. Selective spatial attention involves two alpha-band components associated with distinct spatiotemporal and functional characteristics. Neuroimage 199, 228–236 (2019).
Vijayan, S., Ching, S. N., Purdon, P. L., Brown, E. N. & Kopell, N. J. Thalamocortical mechanisms for the anteriorization of alpha rhythms during propofol-induced unconsciousness. J. Neurosci. 33, 11070–11075 (2013).
Bell, B., Percival, D. B. & Walden, A. T. Calculating Thomson’s spectral multitapers by inverse iteration. J. Comput. Graph. Stat. 2, 119–130 (1993).
Percival, D. B. & Walden, A. T. Spectral Analysis for Physical Applications. https://doi.org/10.1017/cbo9780511622762 (Cambridge University Press, 1993).
Cao, Y. et al. Oscillatory properties of class C notifiable infectious diseases in China from 2009 to 2021. Front. Public Health 10, 903025 (2022).
Han, C., Li, M., Haihambo, N., Cao, Y. & Zhao, X. Enlightenment on oscillatory properties of 23 class B notifiable infectious diseases in the mainland of China from 2004 to 2020. PLoS One 16, e0252803 (2021).
Han, C., Li, M., Haihambo, N. & Babuna, P. Mechanisms of recurrent outbreak of COVID-19: a model-based study. Nonlinear Dyn. 106, 1169–1185 (2021).
Zhao, X. et al. Changes in temporal properties for epidemics of notifiable infectious diseases in China during the COVID-19 epidemic: population-based surveillance study. JMIR Public Health Surveill. 8, 1–12 (2022).
Zhao, X. et al. Periodic characteristics of Hepatitis virus infections From 2013 to 2020 and their association with meteorological factors in Guangdong, China: surveillance study. JMIR Public Health Surveill. 9, e45199 (2023).
Han, C., Shapley, R. & Xing, D. Gamma rhythms in the visual cortex: functions and mechanisms. Cogn. Neurodyn. https://doi.org/10.1007/s11571-021-09767-x (2021)
Donoghue, T. et al. Parameterizing neural power spectra into periodic and aperiodic components. Nat. Neurosci. 23, 1655–1665 (2020).
Barbieri, F., Mazzoni, A., Logothetis, N. K., Panzeri, S. & Brunel, N. Stimulus dependence of local field potential spectra: experiment versus theory. J. Neurosci. 34, 14589–14605 (2014).
Börgers, C., Franzesi, G., LeBeau, F. E. N., Boyden, E. S. & Kopell, N. J. Minimal size of cell assemblies coordinated by gamma oscillations. PLoS Comput. Biol. 8, (2012).
Wilson, H. R. & Cowan, J. D. Excitatory and inhibitory interactions in localized populations of model neurons. Biophys. J. 12, 1–24 (1972).
Mejias, J. F., Murray, J. D., Kennedy, H. & Wang, X. J. Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex. Sci. Adv. 2, (2016).
Ching, S., Cimenser, A., Purdon, P. L., Brown, E. N. & Kopell, N. J. Thalamocortical model for a propofol-induced α-rhythm associated with loss of consciousness. Proc. Natl. Acad. Sci. USA 107, 22665–22670 (2010).
Hughes, S. W. & Crunelli, V. Thalamic mechanisms of EEG alpha rhythms and their pathological implications. Neuroscientist 11, 357–372 (2005).
Helfrich, R. F., Huang, M., Wilson, G. & Knight, R. T. Prefrontal cortex modulates posterior alpha oscillations during top-down guided visual perception. Proc. Natl. Acad. Sci. USA. https://doi.org/10.1073/pnas.1705965114 (2017).
Jiang, J. et al. Signatures of thalamocortical alpha oscillations and synchronization with increased anesthetic depths under isoflurane. Front. Pharm. 13, 887981 (2022).
Chamadia, S. et al. Delta oscillations phase limit neural activity during sevoflurane anesthesia. Commun. Biol. 2, 1–10 (2019).
Zakaria, L., Desowska, A., Berde, C. B. & Cornelissen, L. Electroencephalographic delta and alpha oscillations reveal phase-amplitude coupling in paediatric patients undergoing sevoflurane-based general anaesthesia. Br. J. Anaesth. 130, 595–602 (2023).
Blain-Moraes, S., Lee, U. C., Ku, S. W., Noh, G. J. & Mashour, G. A. Electroencephalographic effects of ketamine on power, cross-frequency coupling, and connectivity in the alpha bandwidth. Front. Syst. Neurosci. 8, 97257 (2014).
Tsuda, N., Hayashi, K., Hagihira, S. & Sawa, T. Ketamine, an NMDA-antagonist, increases the oscillatory frequencies of alpha-peaks on the electroencephalographic power spectrum. Acta Anaesthesiol. Scand. 51, 472–481 (2007).
Huang, Y. et al. Spectral and phase-amplitude coupling signatures in human deep brain oscillations during propofol-induced anaesthesia. Br. J. Anaesth. 121, 303–313 (2018).
Baumgarten, T. J. et al. Connecting occipital alpha band peak frequency, visual temporal resolution, and occipital GABA levels in healthy participants and hepatic encephalopathy patients. Neuroimage Clin. 20, 347–356 (2018).
Lendner, J. D. et al. An electrophysiological marker of arousal level in humans. Elife 9, 1–29 (2020).
Malekmohammadi, M., Price, C. M., Hudson, A. E., DIcesare, J. A. T. & Pouratian, N. Propofol-induced loss of consciousness is associated with a decrease in thalamocortical connectivity in humans. Brain 142, 2288–2302 (2019).
Tanabe, S. et al. Altered global brain signal during physiologic, pharmacologic, and pathologic states of unconsciousness in humans and rats. Anesthesiology 132, 1392–1406 (2020).
Patel, S. R. et al. Dynamics of recovery from anaesthesia-induced unconsciousness across primate neocortex. Brain 143, 833–843 (2020).
Lewis, L. D. et al. Rapid fragmentation of neuronal networks at the onset of propofol-induced unconsciousness. Proc. Natl. Acad. Sci. USA 109, (2012).
Tian, F. et al. Characterizing brain dynamics during ketamine-induced dissociation and subsequent interactions with propofol using human intracranial neurophysiology. Nat. Commun. 14, (2023).
Weiner, V. S. et al. Propofol disrupts alpha dynamics in functionally distinct thalamocortical networks during loss of consciousness. Proc. Natl. Acad. Sci. USA 120, (2023).
Kirschfeld, K. The physical basis of alpha waves in the electroencephalogram and the origin of the ‘Berger effect’. Biol. Cybernet. 92, 177–185 (2005).
Özbek, Y., Fide, E. & Yener, G. G. Resting-state EEG alpha/theta power ratio discriminates early-onset Alzheimer’s disease from healthy controls. Clin. Neurophysiol. 132, 2019–2031 (2021).
Zhou, P. et al. Alpha peak activity in resting-state EEG is associated with depressive score. Front. Neurosci. 17, (2023).
Hopman, R. J., LoTemplio, S. B., Scott, E. E., McKinney, T. L. & Strayer, D. L. Resting-state posterior alpha power changes with prolonged exposure in a natural environment. Cogn. Res Princ. Implic. 5, 1–13 (2020).
Smit, D. J. A., Linkenkaer-Hansen, K. & de Geus, E. J. C. Long-range temporal correlations in resting-state alpha oscillations predict human timing-error dynamics. J. Neurosci. 33, 11212–11220 (2013).
Frauscher, B. et al. Atlas of the normal intracranial electroencephalogram: neurophysiological awake activity in different cortical areas. Brain 141, 1130–1144 (2018).
Han, C. Editorial: Mechanism of neural oscillations and their relationship with multiple cognitive functions and mental disorders. Front. Neurosci 18, (2025).
Han, C. et al. Distinct oscillatory mechanisms in low and high alpha-band activities for screening and potential treatment of Schizophrenia. Transl. Psychiatry 15, (2025).
Han, C. The oscillating mystery: the effects of forty-hertz entrainment in treating Alzheimer’s disease. Brain-X 1, (2023).
Coldea, A., Morand, S., Veniero, D., Harvey, M. & Thut, G. Parietal alpha tACS shows inconsistent effects on visuospatial attention. PLoS One 16, (2021).
Vossen, A., Gross, J. & Thut, G. Alpha power increase after transcranial alternating current stimulation at alpha frequency (a-tACS) reflects plastic changes rather than entrainment. Brain Stimul. 8, 499–508 (2015).
Acknowledgements
This study was supported by the National Natural Science Foundation of China (Grant No. 82530042), Science and Technology Innovation Plan of Shanghai Science and Technology Commission (21Y21900600), and the Foundation of Shanghai Municipal Science and Technology Medical Innovation Research Project (Grant No.23Y21900600).
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C.H., Y.W., J.H., R.W. and S.J. conceived and designed the study. R.W., S.J., L.L., X.C., J.H. and Q.C. contributed to data collection, C.H. and S.J. contributed to the literature search, contributed to data analysis, and interpretation of results. All authors contributed to writing the paper.
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Wang, R., Jiang, S., Cai, Q. et al. Distinct origins of human low and high alpha rhythms revealed by simultaneous EEG-SEEG. Commun Biol (2026). https://doi.org/10.1038/s42003-026-09769-7
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DOI: https://doi.org/10.1038/s42003-026-09769-7
