{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:18:28Z","timestamp":1772173108631,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1010012","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T00:00:00Z","timestamp":1651017600000}}],"reference-count":104,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2022,4,15]],"date-time":"2022-04-15T00:00:00Z","timestamp":1649980800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Swinburne Postgraduate Research Award"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>\n                    The dynamical and physiological basis of alpha band activity and 1\/\n                    <jats:italic>f<\/jats:italic>\n                    <jats:sup>\n                      <jats:italic>\u03b2<\/jats:italic>\n                    <\/jats:sup>\n                    noise in the EEG are the subject of continued speculation. Here we conjecture, on the basis of empirical data analysis, that both of these features may be economically accounted for through a single process if the resting EEG is conceived of being the sum of multiple stochastically perturbed alpha band damped linear oscillators with a distribution of dampings (relaxation rates). The modulation of alpha-band and 1\/\n                    <jats:italic>f<\/jats:italic>\n                    <jats:sup>\n                      <jats:italic>\u03b2<\/jats:italic>\n                    <\/jats:sup>\n                    noise activity by changes in damping is explored in eyes closed (EC) and eyes open (EO) resting state EEG. We aim to estimate the distribution of dampings by solving an inverse problem applied to EEG power spectra. The characteristics of the damping distribution are examined across subjects, sensors and recording condition (EC\/EO). We find that there are robust changes in the damping distribution between EC and EO recording conditions across participants. The estimated damping distributions are found to be predominantly bimodal, with the number and position of the modes related to the sharpness of the alpha resonance and the scaling (\n                    <jats:italic>\u03b2<\/jats:italic>\n                    ) of the power spectrum (1\/\n                    <jats:italic>f<\/jats:italic>\n                    <jats:sup>\n                      <jats:italic>\u03b2<\/jats:italic>\n                    <\/jats:sup>\n                    ). The results suggest that there exists an intimate relationship between resting state alpha activity and 1\/\n                    <jats:italic>f<\/jats:italic>\n                    <jats:sup>\n                      <jats:italic>\u03b2<\/jats:italic>\n                    <\/jats:sup>\n                    noise with changes in both governed by changes to the damping of the underlying alpha oscillatory processes. In particular, alpha-blocking is observed to be the result of the most weakly damped distribution mode becoming more heavily damped. The results suggest a novel way of characterizing resting EEG power spectra and provides new insight into the central role that damped alpha-band activity may play in characterising the spatio-temporal features of resting state EEG.\n                  <\/jats:p>","DOI":"10.1371\/journal.pcbi.1010012","type":"journal-article","created":{"date-parts":[[2022,4,15]],"date-time":"2022-04-15T13:35:37Z","timestamp":1650029737000},"page":"e1010012","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":29,"title":["Alpha blocking and 1\/f\u03b2 spectral scaling in resting EEG can be accounted for by a sum of damped alpha band oscillatory processes"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0377-8673","authenticated-orcid":true,"given":"Rick","family":"Evertz","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8322-9983","authenticated-orcid":true,"given":"Damien G.","family":"Hicks","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5383-3511","authenticated-orcid":true,"given":"David T. J.","family":"Liley","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2022,4,15]]},"reference":[{"key":"pcbi.1010012.ref001","doi-asserted-by":"crossref","DOI":"10.1093\/acprof:oso\/9780195050387.001.0001","volume-title":"Electric fields of the brain: the neurophysics of EEG","author":"PL Nunez","year":"2006"},{"issue":"4","key":"pcbi.1010012.ref002","first-page":"149","article-title":"The normal EEG of the waking adult","volume":"20","author":"E Niedermeyer","year":"1999","journal-title":"Electroencephalography: basic principles, clinical applications and related fields"},{"issue":"19","key":"pcbi.1010012.ref003","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1212\/WNL.0000000000006473","article-title":"Clinical correlates of quantitative EEG in Parkinson disease: A systematic review","volume":"91","author":"VJ Geraedts","year":"2018","journal-title":"Neurology"},{"issue":"1","key":"pcbi.1010012.ref004","first-page":"527","article-title":"\u00dcber das elektrenkephalogramm des menschen","volume":"87","author":"H Berger","year":"1929","journal-title":"European archives of psychiatry and clinical neuroscience"},{"key":"pcbi.1010012.ref005","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.neuroimage.2014.01.049","article-title":"Inter-and intra-individual variability in alpha peak frequency","volume":"92","author":"S Haegens","year":"2014","journal-title":"Neuroimage"},{"key":"pcbi.1010012.ref006","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.neubiorev.2013.05.007","article-title":"Interpreting EEG alpha activity","volume":"44","author":"O Bazanova","year":"2014","journal-title":"Neuroscience & Biobehavioral Reviews"},{"key":"pcbi.1010012.ref007","doi-asserted-by":"crossref","first-page":"116408","DOI":"10.1016\/j.neuroimage.2019.116408","article-title":"Evidence that alpha blocking is due to increases in system-level oscillatory damping not neuronal population desynchronisation","volume":"208","author":"DT Liley","year":"2020","journal-title":"NeuroImage"},{"key":"pcbi.1010012.ref008","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.jneumeth.2015.06.002","article-title":"Physiologically based arousal state estimation and dynamics","volume":"253","author":"R Abeysuriya","year":"2015","journal-title":"Journal of Neuroscience Methods"},{"key":"pcbi.1010012.ref009","doi-asserted-by":"crossref","first-page":"23","DOI":"10.3389\/fncom.2018.00023","article-title":"On the physiological modulation and potential mechanisms underlying parieto-occipital alpha oscillations","volume":"12","author":"D Lozano-Soldevilla","year":"2018","journal-title":"Frontiers in computational neuroscience"},{"key":"pcbi.1010012.ref010","volume-title":"Physiological basis of the alpha rhythm","author":"P Andersen","year":"1968"},{"issue":"1","key":"pcbi.1010012.ref011","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1080\/net.13.1.67.113","article-title":"A spatially continuous mean field theory of electrocortical activity","volume":"13","author":"DT Liley","year":"2002","journal-title":"Network: Computation in Neural Systems"},{"key":"pcbi.1010012.ref012","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1016\/j.neuroimage.2018.08.063","article-title":"The frequency of alpha oscillations: task-dependent modulation and its functional significance","volume":"183","author":"IBH Samuel","year":"2018","journal-title":"Neuroimage"},{"issue":"1","key":"pcbi.1010012.ref013","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.ijpsycho.2012.07.001","article-title":"A short review of alpha activity in cognitive processes and in cognitive impairment","volume":"86","author":"E Ba\u015far","year":"2012","journal-title":"International Journal of Psychophysiology"},{"issue":"1-2","key":"pcbi.1010012.ref014","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.brainresrev.2011.04.002","article-title":"The role of alpha oscillations in temporal attention","volume":"67","author":"S Hanslmayr","year":"2011","journal-title":"Brain research reviews"},{"issue":"1-2","key":"pcbi.1010012.ref015","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/S0167-8760(96)00066-9","article-title":"Event-related synchronization (ERS) in the alpha band\u2014an electrophysiological correlate of cortical idling: a review","volume":"24","author":"G Pfurtscheller","year":"1996","journal-title":"International journal of psychophysiology"},{"key":"pcbi.1010012.ref016","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1016\/j.neuroimage.2018.06.068","article-title":"1\/f electrophysiological spectra in resting and drug-induced states can be explained by the dynamics of multiple oscillatory relaxation processes","volume":"179","author":"SD Muthukumaraswamy","year":"2018","journal-title":"NeuroImage"},{"issue":"1","key":"pcbi.1010012.ref017","first-page":"40","article-title":"The noise in natural phenomena","volume":"78","author":"BJ West","year":"1990","journal-title":"American Scientist"},{"key":"pcbi.1010012.ref018","unstructured":"Milotti E. 1\/f noise: a pedagogical review. arXiv preprint physics\/0204033. 2002."},{"key":"pcbi.1010012.ref019","doi-asserted-by":"crossref","first-page":"186","DOI":"10.3389\/fphys.2012.00186","article-title":"Scale-free and multifractal properties of fmri signals during rest and task","volume":"3","author":"P Ciuciu","year":"2012","journal-title":"Frontiers in physiology"},{"issue":"9","key":"pcbi.1010012.ref020","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1016\/j.tics.2014.04.003","article-title":"Scale-free brain activity: past, present, and future","volume":"18","author":"BJ He","year":"2014","journal-title":"Trends in cognitive sciences"},{"issue":"3","key":"pcbi.1010012.ref021","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s10827-010-0263-2","article-title":"Comparative power spectral analysis of simultaneous elecroencephalographic and magnetoencephalographic recordings in humans suggests non-resistive extracellular media","volume":"29","author":"N Dehghani","year":"2010","journal-title":"Journal of computational neuroscience"},{"issue":"39","key":"pcbi.1010012.ref022","doi-asserted-by":"crossref","first-page":"13786","DOI":"10.1523\/JNEUROSCI.2111-11.2011","article-title":"Scale-free properties of the functional magnetic resonance imaging signal during rest and task","volume":"31","author":"BJ He","year":"2011","journal-title":"Journal of Neuroscience"},{"key":"pcbi.1010012.ref023","doi-asserted-by":"crossref","DOI":"10.1093\/acprof:oso\/9780195301069.001.0001","volume-title":"Rhythms of the Brain","author":"G Buzsaki","year":"2006"},{"issue":"3","key":"pcbi.1010012.ref024","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/j.neuron.2010.04.020","article-title":"The temporal structures and functional significance of scale-free brain activity","volume":"66","author":"BJ He","year":"2010","journal-title":"Neuron"},{"issue":"3","key":"pcbi.1010012.ref025","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.pscychresns.2013.09.008","article-title":"Identifying major depressive disorder using Hurst exponent of resting-state brain networks","volume":"214","author":"M Wei","year":"2013","journal-title":"Psychiatry Research: Neuroimaging"},{"issue":"38","key":"pcbi.1010012.ref026","doi-asserted-by":"crossref","first-page":"13257","DOI":"10.1523\/JNEUROSCI.2332-14.2015","article-title":"Age-related changes in 1\/f neural electrophysiological noise","volume":"35","author":"B Voytek","year":"2015","journal-title":"Journal of Neuroscience"},{"issue":"3-4","key":"pcbi.1010012.ref027","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/0025-5564(69)90044-3","article-title":"Estimation of parameters for a linear difference equation with application to EEG analysis","volume":"5","author":"LH Zetterberg","year":"1969","journal-title":"Mathematical Biosciences"},{"issue":"3","key":"pcbi.1010012.ref028","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/0013-4694(76)90116-4","article-title":"Visible and non-visible EEG changes demonstrated by spectral parameter analysis","volume":"41","author":"A Isaksson","year":"1976","journal-title":"Electroencephalography and clinical neurophysiology"},{"issue":"1-2","key":"pcbi.1010012.ref029","doi-asserted-by":"crossref","first-page":"89","DOI":"10.3109\/00207458808985730","article-title":"A parametric model for multichannel EEG spectra","volume":"40","author":"RD Pascual-marqui","year":"1988","journal-title":"International Journal of Neuroscience"},{"issue":"1864","key":"pcbi.1010012.ref030","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1098\/rsta.2007.2092","article-title":"The criticality hypothesis: how local cortical networks might optimize information processing","volume":"366","author":"JM Beggs","year":"2008","journal-title":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences"},{"issue":"11","key":"pcbi.1010012.ref031","doi-asserted-by":"crossref","first-page":"118102","DOI":"10.1103\/PhysRevLett.97.118102","article-title":"Does the 1\/f frequency scaling of brain signals reflect self-organized critical states?","volume":"97","author":"C Bedard","year":"2006","journal-title":"Physical review letters"},{"key":"pcbi.1010012.ref032","doi-asserted-by":"crossref","first-page":"163","DOI":"10.3389\/fphys.2012.00163","article-title":"Being critical of criticality in the brain","volume":"3","author":"JM Beggs","year":"2012","journal-title":"Frontiers in physiology"},{"issue":"3","key":"pcbi.1010012.ref033","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1007\/s10827-010-0245-4","article-title":"Intrinsic dendritic filtering gives low-pass power spectra of local field potentials","volume":"29","author":"H Lind\u00e9n","year":"2010","journal-title":"Journal of computational neuroscience"},{"key":"pcbi.1010012.ref034","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.neuroimage.2017.06.078","article-title":"Inferring synaptic excitation\/inhibition balance from field potentials","volume":"158","author":"R Gao","year":"2017","journal-title":"Neuroimage"},{"issue":"10","key":"pcbi.1010012.ref035","doi-asserted-by":"crossref","first-page":"3610","DOI":"10.1093\/cercor\/bhx233","article-title":"Random recurrent networks near criticality capture the broadband power distribution of human ECoG dynamics","volume":"28","author":"R Chaudhuri","year":"2018","journal-title":"Cerebral Cortex"},{"issue":"1","key":"pcbi.1010012.ref036","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/s10548-015-0448-0","article-title":"Separating fractal and oscillatory components in the power spectrum of neurophysiological signal","volume":"29","author":"H Wen","year":"2016","journal-title":"Brain topography"},{"issue":"12","key":"pcbi.1010012.ref037","doi-asserted-by":"crossref","first-page":"1655","DOI":"10.1038\/s41593-020-00744-x","article-title":"Parameterizing neural power spectra into periodic and aperiodic components","volume":"23","author":"T Donoghue","year":"2020","journal-title":"Nature neuroscience"},{"key":"pcbi.1010012.ref038","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-54593-1","volume-title":"Neural fields: theory and applications","author":"S Coombes","year":"2014"},{"key":"pcbi.1010012.ref039","doi-asserted-by":"crossref","DOI":"10.1007\/978-94-007-3858-4","volume-title":"Computational systems neurobiology","author":"N Le Nov\u00e8re","year":"2012"},{"issue":"3","key":"pcbi.1010012.ref040","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1016\/j.neuroimage.2010.01.045","article-title":"Large-scale neural dynamics: simple and complex","volume":"52","author":"S Coombes","year":"2010","journal-title":"NeuroImage"},{"issue":"4","key":"pcbi.1010012.ref041","doi-asserted-by":"crossref","first-page":"e1007662","DOI":"10.1371\/journal.pcbi.1007662","article-title":"Inferring a simple mechanism for alpha-blocking by fitting a neural population model to EEG spectra","volume":"16","author":"A Hartoyo","year":"2020","journal-title":"PLoS computational biology"},{"issue":"1","key":"pcbi.1010012.ref042","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/BF00355687","article-title":"Linear model of brain electrical activity\u2014EEG as a superposition of damped oscillatory modes","volume":"53","author":"PJ Franaszczuk","year":"1985","journal-title":"Biological cybernetics"},{"issue":"10","key":"pcbi.1010012.ref043","doi-asserted-by":"crossref","first-page":"1801","DOI":"10.1016\/S1388-2457(99)00099-1","article-title":"Dynamics of the human alpha rhythm: evidence for non-linearity?","volume":"110","author":"C Stam","year":"1999","journal-title":"Clinical Neurophysiology"},{"issue":"1","key":"pcbi.1010012.ref044","doi-asserted-by":"crossref","first-page":"109","DOI":"10.55782\/ane-2000-1329","article-title":"Nonlinearity in human resting, eyes-closed EEG: an in-depth case study","volume":"60","author":"W Pritchard","year":"2000","journal-title":"Acta Neurobiologiae Experimentalis"},{"issue":"4","key":"pcbi.1010012.ref045","doi-asserted-by":"crossref","first-page":"277","DOI":"10.55782\/ane-2002-1445","article-title":"Testing for non-linearity in EEG signal of healthy subjects","volume":"62","author":"RA St\u00eapie\u00f1","year":"2002","journal-title":"Acta neurobiologiae experimentalis"},{"issue":"3","key":"pcbi.1010012.ref046","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0167-8760(02)00006-5","article-title":"Non-linear EEG measures during sleep: effects of the different sleep stages and cyclic alternating pattern","volume":"43","author":"R Ferri","year":"2002","journal-title":"International Journal of Psychophysiology"},{"issue":"7","key":"pcbi.1010012.ref047","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1023\/A:1026284321451","article-title":"Does the EEG during isoflurane\/alfentanil anesthesia differ from linear random data?","volume":"17","author":"H Schwilden","year":"2002","journal-title":"Journal of clinical monitoring and computing"},{"issue":"5","key":"pcbi.1010012.ref048","doi-asserted-by":"crossref","first-page":"1365","DOI":"10.1213\/01.ANE.0000148689.35951.BA","article-title":"Electroencephalogram monitoring during anesthesia with propofol and alfentanil: the impact of second order spectral analysis","volume":"100","author":"C Jeleazcov","year":"2005","journal-title":"Anesthesia & Analgesia"},{"key":"pcbi.1010012.ref049","first-page":"227","volume-title":"International review of neurobiology","author":"R Elul","year":"1972"},{"key":"pcbi.1010012.ref050","first-page":"1","volume-title":"Nonlinear dynamics in computational neuroscience","author":"S Coombes","year":"2019"},{"key":"pcbi.1010012.ref051","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1007\/978-3-642-74557-7_15","volume-title":"Brain dynamics","author":"K Blinowska","year":"1989"},{"issue":"1","key":"pcbi.1010012.ref052","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/0013-4694(89)90015-1","article-title":"On the structure of EEG development","volume":"73","author":"AA Amador","year":"1989","journal-title":"Electroencephalography and clinical Neurophysiology"},{"issue":"2","key":"pcbi.1010012.ref053","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/BF00243291","article-title":"Non-linear and linear forecasting of the EEG time series","volume":"66","author":"KJ Blinowska","year":"1991","journal-title":"Biological cybernetics"},{"issue":"3","key":"pcbi.1010012.ref054","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1007\/BF00198095","article-title":"Autoregression models of EEG","volume":"62","author":"J Wright","year":"1990","journal-title":"Biological cybernetics"},{"key":"pcbi.1010012.ref055","unstructured":"Ghorbanian P, Ramakrishnan S, Simon AJ, Ashrafiuon H. Stochastic dynamic modeling of the human brain EEG signal. In: Dynamic Systems and Control Conference. vol. 56130. American Society of Mechanical Engineers; 2013. p. V002T22A003."},{"issue":"3","key":"pcbi.1010012.ref056","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.neulet.2005.02.037","article-title":"Intelligence related differences in EEG-bandpower","volume":"381","author":"M Doppelmayr","year":"2005","journal-title":"Neuroscience Letters"},{"issue":"4","key":"pcbi.1010012.ref057","doi-asserted-by":"crossref","first-page":"e01263","DOI":"10.1002\/brb3.1263","article-title":"The roles of alpha oscillation in working memory retention","volume":"9","author":"E Wianda","year":"2019","journal-title":"Brain and behavior"},{"issue":"6","key":"pcbi.1010012.ref058","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1093\/scan\/nsz038","article-title":"Low delta and high alpha power are associated with better conflict control and working memory in high mindfulness, low anxiety individuals","volume":"14","author":"S Jaiswal","year":"2019","journal-title":"Social cognitive and affective neuroscience"},{"issue":"2","key":"pcbi.1010012.ref059","doi-asserted-by":"crossref","first-page":"021903","DOI":"10.1103\/PhysRevE.63.021903","article-title":"Prediction of electroencephalographic spectra from neurophysiology","volume":"63","author":"P Robinson","year":"2001","journal-title":"Physical Review E"},{"issue":"4","key":"pcbi.1010012.ref060","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1007\/BF00199471","article-title":"Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns","volume":"73","author":"BH Jansen","year":"1995","journal-title":"Biological cybernetics"},{"key":"pcbi.1010012.ref061","doi-asserted-by":"crossref","first-page":"118746","DOI":"10.1016\/j.neuroimage.2021.118746","article-title":"Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability","volume":"247","author":"L Iemi","year":"2022","journal-title":"NeuroImage"},{"issue":"12","key":"pcbi.1010012.ref062","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1016\/j.tics.2012.10.007","article-title":"Alpha-band oscillations, attention, and controlled access to stored information","volume":"16","author":"W Klimesch","year":"2012","journal-title":"Trends in cognitive sciences"},{"key":"pcbi.1010012.ref063","first-page":"186","article-title":"Shaping functional architecture by oscillatory alpha activity: gating by inhibition","author":"O Jensen","year":"2010","journal-title":"Frontiers in human neuroscience"},{"issue":"1","key":"pcbi.1010012.ref064","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.brainresrev.2006.06.003","article-title":"EEG alpha oscillations: the inhibition\u2013timing hypothesis","volume":"53","author":"W Klimesch","year":"2007","journal-title":"Brain research reviews"},{"issue":"7","key":"pcbi.1010012.ref065","doi-asserted-by":"crossref","first-page":"2482","DOI":"10.1111\/ejn.13807","article-title":"Temporal coupling of field potentials and action potentials in the neocortex","volume":"48","author":"BO Watson","year":"2018","journal-title":"European Journal of Neuroscience"},{"issue":"2","key":"pcbi.1010012.ref066","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1093\/cercor\/bhv304","article-title":"Ongoing alpha activity in V1 regulates visually driven spiking responses","volume":"27","author":"K Dougherty","year":"2017","journal-title":"Cerebral Cortex"},{"issue":"13","key":"pcbi.1010012.ref067","doi-asserted-by":"crossref","first-page":"4935","DOI":"10.1523\/JNEUROSCI.5580-10.2011","article-title":"Neuronal mechanisms and attentional modulation of corticothalamic alpha oscillations","volume":"31","author":"A Bollimunta","year":"2011","journal-title":"Journal of Neuroscience"},{"issue":"40","key":"pcbi.1010012.ref068","doi-asserted-by":"crossref","first-page":"9976","DOI":"10.1523\/JNEUROSCI.2699-08.2008","article-title":"Neuronal mechanisms of cortical alpha oscillations in awake-behaving macaques","volume":"28","author":"A Bollimunta","year":"2008","journal-title":"Journal of Neuroscience"},{"issue":"48","key":"pcbi.1010012.ref069","doi-asserted-by":"crossref","first-page":"19377","DOI":"10.1073\/pnas.1117190108","article-title":"\u03b1-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking","volume":"108","author":"S Haegens","year":"2011","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1010012.ref070","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1016\/j.neuroimage.2013.08.070","article-title":"Broadband changes in the cortical surface potential track activation of functionally diverse neuronal populations","volume":"85","author":"KJ Miller","year":"2014","journal-title":"Neuroimage"},{"issue":"45","key":"pcbi.1010012.ref071","doi-asserted-by":"crossref","first-page":"11526","DOI":"10.1523\/JNEUROSCI.2848-08.2008","article-title":"Neural correlates of high-gamma oscillations (60\u2013200 Hz) in macaque local field potentials and their potential implications in electrocorticography","volume":"28","author":"S Ray","year":"2008","journal-title":"Journal of Neuroscience"},{"issue":"6","key":"pcbi.1010012.ref072","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1002\/hipo.20979","article-title":"BOSC: A better oscillation detection method, extracts both sustained and transient rhythms from rat hippocampal recordings","volume":"22","author":"AM Hughes","year":"2012","journal-title":"Hippocampus"},{"issue":"1","key":"pcbi.1010012.ref073","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/ncomms10340","article-title":"Human brain networks function in connectome-specific harmonic waves","volume":"7","author":"S Atasoy","year":"2016","journal-title":"Nature communications"},{"issue":"3","key":"pcbi.1010012.ref074","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1177\/1073858417728032","article-title":"Harmonic brain modes: a unifying framework for linking space and time in brain dynamics","volume":"24","author":"S Atasoy","year":"2018","journal-title":"The Neuroscientist"},{"key":"pcbi.1010012.ref075","first-page":"176","volume-title":"Wavelets and Sparsity XVI","author":"F Abdelnour","year":"2015"},{"key":"pcbi.1010012.ref076","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.neuroimage.2016.04.050","article-title":"Eigenmodes of brain activity: Neural field theory predictions and comparison with experiment","volume":"142","author":"PA Robinson","year":"2016","journal-title":"NeuroImage"},{"key":"pcbi.1010012.ref077","doi-asserted-by":"crossref","first-page":"118919","DOI":"10.1016\/j.neuroimage.2022.118919","article-title":"Spectral graph theory of brain oscillations\u2013revisited and improved","author":"P Verma","year":"2022","journal-title":"NeuroImage"},{"issue":"11","key":"pcbi.1010012.ref078","doi-asserted-by":"crossref","first-page":"2980","DOI":"10.1002\/hbm.24991","article-title":"Spectral graph theory of brain oscillations","volume":"41","author":"A Raj","year":"2020","journal-title":"Human brain mapping"},{"key":"pcbi.1010012.ref079","doi-asserted-by":"crossref","first-page":"728","DOI":"10.1016\/j.neuroimage.2018.02.016","article-title":"Functional brain connectivity is predictable from anatomic network\u2019s Laplacian eigen-structure","volume":"172","author":"F Abdelnour","year":"2018","journal-title":"NeuroImage"},{"issue":"6","key":"pcbi.1010012.ref080","doi-asserted-by":"crossref","first-page":"e1005550","DOI":"10.1371\/journal.pcbi.1005550","article-title":"Brain network eigenmodes provide a robust and compact representation of the structural connectome in health and disease","volume":"13","author":"MB Wang","year":"2017","journal-title":"PLoS computational biology"},{"key":"pcbi.1010012.ref081","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1007\/978-94-007-3858-4_11","volume-title":"Computational Systems Neurobiology","author":"DT Liley","year":"2012"},{"issue":"8","key":"pcbi.1010012.ref082","doi-asserted-by":"crossref","first-page":"e1000092","DOI":"10.1371\/journal.pcbi.1000092","article-title":"The dynamic brain: from spiking neurons to neural masses and cortical fields","volume":"4","author":"G Deco","year":"2008","journal-title":"PLoS computational biology"},{"key":"pcbi.1010012.ref083","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1017\/S0022112010001217","article-title":"Dynamic mode decomposition of numerical and experimental data","volume":"656","author":"PJ Schmid","year":"2010","journal-title":"Journal of fluid mechanics"},{"key":"pcbi.1010012.ref084","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jneumeth.2015.10.010","article-title":"Extracting spatial\u2013temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition","volume":"258","author":"BW Brunton","year":"2016","journal-title":"Journal of neuroscience methods"},{"key":"pcbi.1010012.ref085","first-page":"423","article-title":"Revealing neuronal function through microelectrode array recordings","volume":"8","author":"MEJ Obien","year":"2015","journal-title":"Frontiers in neuroscience"},{"issue":"6437","key":"pcbi.1010012.ref086","doi-asserted-by":"crossref","first-page":"eaav7893","DOI":"10.1126\/science.aav7893","article-title":"Spontaneous behaviors drive multidimensional, brainwide activity","volume":"364","author":"C Stringer","year":"2019","journal-title":"Science"},{"key":"pcbi.1010012.ref087","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/978-3-0346-0428-4_7","article-title":"Conscious and nonconscious processes: distinct forms of evidence accumulation?","author":"S Dehaene","year":"2011","journal-title":"Biological physics"},{"key":"pcbi.1010012.ref088","doi-asserted-by":"crossref","DOI":"10.4324\/9781410612403","volume-title":"The organization of behavior: A neuropsychological theory","author":"DO Hebb","year":"2005"},{"key":"pcbi.1010012.ref089","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1016\/j.neuroimage.2019.01.024","article-title":"The spectral exponent of the resting EEG indexes the presence of consciousness during unresponsiveness induced by propofol, xenon, and ketamine","volume":"189","author":"MA Colombo","year":"2019","journal-title":"Neuroimage"},{"key":"pcbi.1010012.ref090","doi-asserted-by":"crossref","first-page":"56","DOI":"10.3389\/fnhum.2013.00056","article-title":"Relationships between electroencephalographic spectral peaks across frequency bands","volume":"7","author":"SJ Van Albada","year":"2013","journal-title":"Frontiers in human neuroscience"},{"key":"pcbi.1010012.ref091","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1007\/978-3-642-54593-1_14","volume-title":"Neural Fields","author":"DT Liley","year":"2014"},{"key":"pcbi.1010012.ref092","doi-asserted-by":"crossref","unstructured":"Groetsch CW. Integral equations of the first kind, inverse problems and regularization: a crash course. In: Journal of Physics: Conference Series. vol. 73. IOP Publishing; 2007. p. 012001.","DOI":"10.1088\/1742-6596\/73\/1\/012001"},{"key":"pcbi.1010012.ref093","volume-title":"Parameter estimation and inverse problems","author":"RC Aster","year":"2018"},{"issue":"12","key":"pcbi.1010012.ref094","doi-asserted-by":"crossref","first-page":"3479","DOI":"10.1007\/s00213-018-5064-8","article-title":"Comparison of local spectral modulation, and temporal correlation, of simultaneously recorded EEG\/fMRI signals during ketamine and midazolam sedation","volume":"235","author":"A Forsyth","year":"2018","journal-title":"Psychopharmacology"},{"issue":"6","key":"pcbi.1010012.ref095","doi-asserted-by":"crossref","first-page":"1034","DOI":"10.1109\/TBME.2004.827072","article-title":"BCI2000: a general-purpose brain-computer interface (BCI) system","volume":"51","author":"G Schalk","year":"2004","journal-title":"IEEE Transactions on biomedical engineering"},{"issue":"4","key":"pcbi.1010012.ref096","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1300\/J184v02n04_02","article-title":"Normative EEG databases and EEG biofeedback","volume":"2","author":"RW Thatcher","year":"1998","journal-title":"Journal of Neurotherapy"},{"issue":"1-2","key":"pcbi.1010012.ref097","doi-asserted-by":"crossref","first-page":"119","DOI":"10.3109\/00207459208999796","article-title":"The brain in fractal time: 1\/f-like power spectrum scaling of the human electroencephalogram","volume":"66","author":"WS Pritchard","year":"1992","journal-title":"International Journal of Neuroscience"},{"issue":"2","key":"pcbi.1010012.ref098","doi-asserted-by":"crossref","first-page":"021901","DOI":"10.1103\/PhysRevE.66.021901","article-title":"Scaling properties of fluctuations in the human electroencephalogram","volume":"66","author":"RC Hwa","year":"2002","journal-title":"Physical Review E"},{"issue":"9","key":"pcbi.1010012.ref099","doi-asserted-by":"crossref","first-page":"2171","DOI":"10.1109\/TBME.2008.923145","article-title":"A study on the possible usefulness of detrended fluctuation analysis of the electroencephalogram background activity in Alzheimer\u2019s disease","volume":"55","author":"D Ab\u00e1solo","year":"2008","journal-title":"IEEE transactions on Biomedical Engineering"},{"issue":"3","key":"pcbi.1010012.ref100","doi-asserted-by":"crossref","first-page":"031909","DOI":"10.1103\/PhysRevE.81.031909","article-title":"Dynamics of electroencephalogram entropy and pitfalls of scaling detection","volume":"81","author":"M Ignaccolo","year":"2010","journal-title":"Physical Review E"},{"key":"pcbi.1010012.ref101","doi-asserted-by":"crossref","first-page":"e02047","DOI":"10.1002\/brb3.2047","article-title":"Separating scale-free and oscillatory components of neural activity in schizophrenia","author":"FS Racz","year":"2021","journal-title":"Brain and behavior"},{"issue":"1","key":"pcbi.1010012.ref102","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-021-81230-7","article-title":"A set of composite, non-redundant EEG measures of NREM sleep based on the power law scaling of the Fourier spectrum","volume":"11","author":"R B\u00f3dizs","year":"2021","journal-title":"Scientific reports"},{"key":"pcbi.1010012.ref103","volume-title":"Information theory and statistics","author":"S Kullback","year":"1997"},{"issue":"1","key":"pcbi.1010012.ref104","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/hbm.1058","article-title":"Nonparametric permutation tests for functional neuroimaging: a primer with examples","volume":"15","author":"TE Nichols","year":"2002","journal-title":"Human brain mapping"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1010012","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T00:00:00Z","timestamp":1651017600000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1010012","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T05:22:08Z","timestamp":1726982528000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1010012"}},"subtitle":[],"editor":[{"given":"Daniele","family":"Marinazzo","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2022,4,15]]},"references-count":104,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2022,4,15]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1010012","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.08.20.457060","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,15]]}}}