{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:23:40Z","timestamp":1772173420221,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1012521","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T00:00:00Z","timestamp":1729555200000}}],"reference-count":80,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T00:00:00Z","timestamp":1728518400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP","award":["project MNESYS (PE0000006)"],"award-info":[{"award-number":["project MNESYS (PE0000006)"]}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>The ability to solve complex tasks relies on the adaptive changes occurring in the spatio-temporal organization of brain activity under different conditions. Altered flexibility in these dynamics can lead to impaired cognitive performance, manifesting for instance as difficulties in attention regulation, distraction inhibition, and behavioral adaptation. Such impairments result in decreased efficiency and increased effort in accomplishing goal-directed tasks. Therefore, developing quantitative measures that can directly assess the effort involved in these transitions using neural data is of paramount importance. In this study, we propose a framework to associate cognitive effort during the performance of tasks with electroencephalography (EEG) activation patterns. The methodology relies on the identification of discrete dynamical states (EEG microstates) and optimal transport theory. To validate the effectiveness of this framework, we apply it to a dataset collected during a spatial version of the Stroop task, a cognitive test in which participants respond to one aspect of a stimulus while ignoring another, often conflicting, aspect. The Stroop task is a cognitive test where participants must respond to one aspect of a stimulus while ignoring another, often conflicting, aspect. Our findings reveal an increased cost linked to cognitive effort, thus confirming the framework\u2019s effectiveness in capturing and quantifying cognitive transitions. By utilizing a fully data-driven method, this research opens up fresh perspectives for physiologically describing cognitive effort within the brain.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012521","type":"journal-article","created":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T13:38:05Z","timestamp":1728567485000},"page":"e1012521","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":6,"title":["EEG microstate transition cost correlates with task demands"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9981-1027","authenticated-orcid":true,"given":"Giacomo","family":"Barzon","sequence":"first","affiliation":[]},{"given":"Ettore","family":"Ambrosini","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4087-2845","authenticated-orcid":true,"given":"Antonino","family":"Vallesi","sequence":"additional","affiliation":[]},{"given":"Samir","family":"Suweis","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2024,10,10]]},"reference":[{"issue":"1","key":"pcbi.1012521.ref001","doi-asserted-by":"crossref","first-page":"2317","DOI":"10.1038\/s41467-019-10317-7","article-title":"Resting brain dynamics at different timescales capture distinct aspects of human behavior","volume":"10","author":"R Li\u00e9geois","year":"2019","journal-title":"Nat Commun"},{"issue":"9","key":"pcbi.1012521.ref002","doi-asserted-by":"crossref","first-page":"3095","DOI":"10.1093\/cercor\/bhx179","article-title":"Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI","volume":"28","author":"A Schaefer","year":"2018","journal-title":"Cereb Cortex"},{"issue":"2","key":"pcbi.1012521.ref003","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.neuron.2014.10.015","article-title":"The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery","volume":"84","author":"VD Calhoun","year":"2014","journal-title":"Neuron"},{"key":"pcbi.1012521.ref004","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.neuroimage.2016.12.061","article-title":"The dynamic functional connectome: state-of-the-art and perspectives","volume":"160","author":"MG Preti","year":"2017","journal-title":"Neuroimage"},{"issue":"10","key":"pcbi.1012521.ref005","doi-asserted-by":"crossref","first-page":"108128","DOI":"10.1016\/j.celrep.2020.108128","article-title":"Brain states and transitions: insights from computational neuroscience","volume":"32","author":"ML Kringelbach","year":"2020","journal-title":"Cell Rep"},{"issue":"1","key":"pcbi.1012521.ref006","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1038\/s41398-020-01160-2","article-title":"Excitatory-inhibitory balance within EEG microstates and resting-state fMRI networks: assessed via simultaneous trimodal PET-MR-EEG imaging","volume":"11","author":"R Rajkumar","year":"2021","journal-title":"Transl Psychiatry"},{"key":"pcbi.1012521.ref007","doi-asserted-by":"crossref","first-page":"118850","DOI":"10.1016\/j.neuroimage.2021.118850","article-title":"Microstates and power envelope hidden Markov modeling probe bursting brain activity at different timescales","volume":"247","author":"N Coquelet","year":"2022","journal-title":"Neuroimage"},{"key":"pcbi.1012521.ref008","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/j.neuroimage.2017.11.062","article-title":"EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: a review","volume":"180","author":"CM Michel","year":"2018","journal-title":"Neuroimage"},{"key":"pcbi.1012521.ref009","doi-asserted-by":"crossref","first-page":"70","DOI":"10.3389\/fncom.2018.00070","article-title":"EEG microstate sequences from different clustering algorithms are information-theoretically invariant","volume":"12","author":"F von Wegner","year":"2018","journal-title":"Front Comput Neurosci"},{"key":"pcbi.1012521.ref010","first-page":"1","article-title":"The functional aspects of resting EEG microstates: a systematic review","author":"P Tarailis","year":"2023","journal-title":"Brain Topogr"},{"issue":"3","key":"pcbi.1012521.ref011","doi-asserted-by":"crossref","first-page":"624","DOI":"10.1037\/0033-295X.108.3.624","article-title":"Conflict monitoring and cognitive control","volume":"108","author":"MM Botvinick","year":"2001","journal-title":"Psychol Rev"},{"issue":"2","key":"pcbi.1012521.ref012","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.tics.2011.12.010","article-title":"The variable nature of cognitive control: a dual mechanisms framework","volume":"16","author":"TS Braver","year":"2012","journal-title":"Trends Cogn Sci"},{"key":"pcbi.1012521.ref013","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.cortex.2016.04.023","article-title":"Unity and diversity of executive functions: individual differences as a window on cognitive structure","volume":"86","author":"NP Friedman","year":"2017","journal-title":"Cortex"},{"key":"pcbi.1012521.ref014","first-page":"55","volume-title":"Information Processing and Cognition: The Loyola Symposium","author":"MI Posner","year":"1975"},{"key":"pcbi.1012521.ref015","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1146\/annurev.neuro.24.1.167","article-title":"An integrative theory of prefrontal cortex function","volume":"24","author":"EK Miller","year":"2001","journal-title":"Annu Rev Neurosci"},{"key":"pcbi.1012521.ref016","doi-asserted-by":"crossref","first-page":"2164","DOI":"10.3389\/fpsyg.2019.02164","article-title":"The Stroop effect occurs at multiple points along a cascade of control: evidence from cognitive neuroscience approaches","volume":"10","author":"MT Banich","year":"2019","journal-title":"Front Psychol"},{"issue":"5","key":"pcbi.1012521.ref017","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.tics.2005.03.010","article-title":"The cognitive control of emotion","volume":"9","author":"KN Ochsner","year":"2005","journal-title":"Trends Cogn Sci"},{"key":"pcbi.1012521.ref018","doi-asserted-by":"crossref","first-page":"119489","DOI":"10.1016\/j.neuroimage.2022.119489","article-title":"Modes of cognition: evidence from metastable brain dynamics","volume":"260","author":"K Capouskova","year":"2022","journal-title":"Neuroimage"},{"issue":"36","key":"pcbi.1012521.ref019","doi-asserted-by":"crossref","first-page":"18088","DOI":"10.1073\/pnas.1905534116","article-title":"Awakening: predicting external stimulation to force transitions between different brain states","volume":"116","author":"G Deco","year":"2019","journal-title":"Proc Natl Acad Sci USA"},{"key":"pcbi.1012521.ref020","first-page":"14565","article-title":"Habit learning supported by efficiently controlled network dynamics in naive macaque monkeys","author":"KP Szymula","journal-title":"arXiv preprint arXiv:2006"},{"issue":"22","key":"pcbi.1012521.ref021","doi-asserted-by":"crossref","first-page":"8259","DOI":"10.1523\/JNEUROSCI.0440-11.2011","article-title":"Cognitive effort drives workspace configuration of human brain functional networks","volume":"31","author":"MG Kitzbichler","year":"2011","journal-title":"J Neurosci"},{"key":"pcbi.1012521.ref022","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.neuroimage.2013.05.079","article-title":"Dynamic functional connectivity: promise, issues, and interpretations","volume":"80","author":"RM Hutchison","year":"2013","journal-title":"Neuroimage"},{"key":"pcbi.1012521.ref023","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1016\/j.neuroimage.2017.08.006","article-title":"Task-based dynamic functional connectivity: recent findings and open questions","volume":"180","author":"J Gonzalez-Castillo","year":"2018","journal-title":"Neuroimage"},{"issue":"1","key":"pcbi.1012521.ref024","doi-asserted-by":"crossref","first-page":"3089","DOI":"10.1038\/s41467-020-16914-1","article-title":"EEG microstates are a candidate endophenotype for schizophrenia","volume":"11","author":"JR da Cruz","year":"2020","journal-title":"Nat Commun"},{"issue":"1","key":"pcbi.1012521.ref025","doi-asserted-by":"crossref","first-page":"5069","DOI":"10.1038\/s41467-022-32304-1","article-title":"Subcortical-cortical dynamical states of the human brain and their breakdown in stroke","volume":"13","author":"C Favaretto","year":"2022","journal-title":"Nat Commun"},{"issue":"3","key":"pcbi.1012521.ref026","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1002\/hbm.25714","article-title":"Unveiling whole-brain dynamics in normal aging through Hidden Markov Models","volume":"43","author":"M Moretto","year":"2022","journal-title":"Hum Brain Mapp"},{"issue":"19","key":"pcbi.1012521.ref027","doi-asserted-by":"crossref","first-page":"3065","DOI":"10.1016\/j.cub.2018.07.083","article-title":"Whole-brain multimodal neuroimaging model using serotonin receptor maps explains non-linear functional effects of LSD","volume":"28","author":"G Deco","year":"2018","journal-title":"Curr Biol"},{"issue":"3","key":"pcbi.1012521.ref028","doi-asserted-by":"crossref","first-page":"031003","DOI":"10.1103\/RevModPhys.90.031003","article-title":"Colloquium: Control of dynamics in brain networks","volume":"90","author":"E Tang","year":"2018","journal-title":"Rev Mod Phys"},{"issue":"5","key":"pcbi.1012521.ref029","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1038\/s42254-019-0040-8","article-title":"The physics of brain network structure, function and control","volume":"1","author":"CW Lynn","year":"2019","journal-title":"Nat Rev Phys"},{"key":"pcbi.1012521.ref030","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.neuroimage.2018.04.010","article-title":"Warnings and caveats in brain controllability","volume":"176","author":"C Tu","year":"2018","journal-title":"Neuroimage"},{"key":"pcbi.1012521.ref031","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1016\/j.neuroimage.2019.07.012","article-title":"Brain controllability: not a slam dunk yet","volume":"200","author":"S Suweis","year":"2019","journal-title":"Neuroimage"},{"issue":"5","key":"pcbi.1012521.ref032","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1177\/107385840100700510","article-title":"Book review: brain function, nonlinear coupling, and neuronal transients","volume":"7","author":"KJ Friston","year":"2001","journal-title":"Neuroscientist"},{"key":"pcbi.1012521.ref033","doi-asserted-by":"crossref","first-page":"105918","DOI":"10.1016\/j.nbd.2022.105918","article-title":"Genuine high-order interactions in brain networks and neurodegeneration","volume":"175","author":"R Herzog","year":"2022","journal-title":"Neurobiol Dis"},{"issue":"1","key":"pcbi.1012521.ref034","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.pneurobio.2009.01.006","article-title":"Stochastic dynamics as a principle of brain function","volume":"88","author":"G Deco","year":"2009","journal-title":"Prog Neurobiol"},{"issue":"7","key":"pcbi.1012521.ref035","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1002\/cpa.21975","article-title":"The Data-Driven Schr\u00f6dinger Bridge","volume":"74","author":"M Pavon","year":"2021","journal-title":"Commun Pure Appl Math"},{"issue":"2","key":"pcbi.1012521.ref036","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1137\/20M1339982","article-title":"Stochastic control liaisons: Richard Sinkhorn meets Gaspard Monge on a Schr\u00f6dinger bridge","volume":"63","author":"Y Chen","year":"2021","journal-title":"SIAM Rev"},{"key":"pcbi.1012521.ref037","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1007\/s10957-015-0803-z","article-title":"On the relation between optimal transport and Schr\u00f6dinger bridges: a stochastic control viewpoint","volume":"169","author":"Y Chen","year":"2016","journal-title":"J Optim Theory Appl"},{"issue":"5\u20136","key":"pcbi.1012521.ref038","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1561\/2200000073","article-title":"Computational optimal transport: with applications to data science","volume":"11","author":"G Peyr\u00e9","year":"2019","journal-title":"Found Trends Mach Learn"},{"issue":"1","key":"pcbi.1012521.ref039","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1162\/netn_a_00213","article-title":"Quantifying brain state transition cost via Schr\u00f6dinger bridge","volume":"6","author":"G Kawakita","year":"2022","journal-title":"Netw Neurosci"},{"issue":"7","key":"pcbi.1012521.ref040","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1177\/0956797620916786","article-title":"What is the test-retest reliability of common task-functional MRI measures? New empirical evidence and a meta-analysis","volume":"31","author":"ML Elliott","year":"2020","journal-title":"Psychol Sci"},{"issue":"6","key":"pcbi.1012521.ref041","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1037\/h0054651","article-title":"Studies of interference in serial verbal reactions","volume":"18","author":"JR Stroop","year":"1935","journal-title":"J Exp Psychol"},{"key":"pcbi.1012521.ref042","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1162\/jocn_a_01076","article-title":"Domain-general Stroop performance and hemispheric asymmetries: a resting-state EEG study","volume":"29","author":"E Ambrosini","year":"2017","journal-title":"J Cogn Neurosci"},{"key":"pcbi.1012521.ref043","first-page":"1","article-title":"The Stroop legacy: a cautionary tale on methodological issues and a proposed spatial solution","author":"G Viviani","year":"2023","journal-title":"Behav Res Methods"},{"key":"pcbi.1012521.ref044","first-page":"1","article-title":"A comparison between different variants of the spatial Stroop task: the influence of analytic flexibility on Stroop effect estimates and reliability","author":"G Viviani","year":"2023","journal-title":"Behav Res Methods"},{"issue":"2","key":"pcbi.1012521.ref045","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1037\/a0035032","article-title":"Conflict-triggered top-down control: default mode, last resort, or no such thing?","volume":"40","author":"JM Bugg","year":"2014","journal-title":"J Exp Psychol Learn Mem Cogn"},{"issue":"11","key":"pcbi.1012521.ref046","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0294957","article-title":"On the relationship between emotions and cognitive control: evidence from an observational study on emotional priming Stroop task","volume":"18","author":"A Visalli","year":"2023","journal-title":"PLoS One"},{"key":"pcbi.1012521.ref047","article-title":"Tango of control: the interplay between proactive and reactive control","author":"G Viviani","year":"2024","journal-title":"J Exp Psychol Gen"},{"key":"pcbi.1012521.ref048","doi-asserted-by":"crossref","first-page":"778","DOI":"10.3758\/s13421-016-0591-1","article-title":"Dissociating proactive and reactive control in the Stroop task","volume":"44","author":"C Gonthier","year":"2016","journal-title":"Mem Cognit"},{"issue":"10","key":"pcbi.1012521.ref049","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1089\/brain.2016.0476","article-title":"Electroencephalographic resting-state networks: source localization of microstates","volume":"7","author":"A Custo","year":"2017","journal-title":"Brain Connect"},{"key":"pcbi.1012521.ref050","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.neuroimage.2014.04.002","article-title":"EEG source imaging of brain states using spatiotemporal regression","volume":"96","author":"A Custo","year":"2014","journal-title":"Neuroimage"},{"issue":"10","key":"pcbi.1012521.ref051","doi-asserted-by":"crossref","first-page":"3047","DOI":"10.1002\/hbm.25834","article-title":"Beyond broadband: towards a spectral decomposition of electroencephalography microstates","volume":"43","author":"V F\u00e9rat","year":"2022","journal-title":"Hum Brain Mapp"},{"key":"pcbi.1012521.ref052","first-page":"1","article-title":"Electrocorticographic activation patterns of electroencephalographic microstates","author":"CA Mikutta","year":"2023","journal-title":"Brain Topogr"},{"issue":"6173","key":"pcbi.1012521.ref053","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1126\/science.1247412","article-title":"Action monitoring and medial frontal cortex: leading role of supplementary motor area","volume":"343","author":"F Bonini","year":"2014","journal-title":"Science"},{"key":"pcbi.1012521.ref054","doi-asserted-by":"crossref","first-page":"105637","DOI":"10.1016\/j.bandc.2020.105637","article-title":"A review on the electroencephalography markers of Stroop executive control processes","volume":"146","author":"K Heidlmayr","year":"2020","journal-title":"Brain Cogn"},{"issue":"32","key":"pcbi.1012521.ref055","doi-asserted-by":"crossref","first-page":"10020","DOI":"10.1073\/pnas.1500048112","article-title":"Flexible brain network reconfiguration supporting inhibitory control","volume":"112","author":"JM Spielberg","year":"2015","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"37","key":"pcbi.1012521.ref056","doi-asserted-by":"crossref","first-page":"11678","DOI":"10.1073\/pnas.1422487112","article-title":"Dynamic reconfiguration of frontal brain networks during executive cognition in humans","volume":"112","author":"U Braun","year":"2015","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"1","key":"pcbi.1012521.ref057","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.neuron.2012.09.012","article-title":"Neuromodulation of brain states","volume":"76","author":"SH Lee","year":"2012","journal-title":"Neuron"},{"key":"pcbi.1012521.ref058","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.conb.2014.09.010","article-title":"Neural control of brain state","volume":"29","author":"E Zagha","year":"2014","journal-title":"Curr Opin Neurobiol"},{"key":"pcbi.1012521.ref059","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.52443","article-title":"Reconfiguration of functional brain networks and metabolic cost converge during task performance","volume":"9","author":"A Hahn","year":"2020","journal-title":"eLife"},{"issue":"5","key":"pcbi.1012521.ref060","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1109\/18.532893","article-title":"On the relative entropy of discrete-time Markov processes with given end-point densities","volume":"42","author":"A. Beghi","year":"1996","journal-title":"IEEE Trans Inf Theory"},{"key":"pcbi.1012521.ref061","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/j.neuroimage.2017.05.067","article-title":"The energy landscape underpinning module dynamics in the human brain connectome","volume":"157","author":"A Ashourvan","year":"2017","journal-title":"Neuroimage"},{"issue":"5","key":"pcbi.1012521.ref062","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2006436118","article-title":"Time-evolving controllability of effective connectivity networks during seizure progression","volume":"118","author":"BH Scheid","year":"2021","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"1","key":"pcbi.1012521.ref063","doi-asserted-by":"crossref","first-page":"5812","DOI":"10.1038\/s41467-022-33578-1","article-title":"Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain\u2019s control energy landscape","volume":"13","author":"SP Singleton","year":"2022","journal-title":"Nat Commun"},{"issue":"2","key":"pcbi.1012521.ref064","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1523\/JNEUROSCI.1053-22.2022","article-title":"Optimal control costs of brain state transitions in linear stochastic systems","volume":"43","author":"S Kamiya","year":"2023","journal-title":"J Neurosci"},{"issue":"47","key":"pcbi.1012521.ref065","article-title":"Broken detailed balance and entropy production in the human brain","volume":"118","author":"CW Lynn","year":"2021","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"2","key":"pcbi.1012521.ref066","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1007\/s10548-023-01023-1","article-title":"Propofol reversibly attenuates short-range microstate ordering and 20 Hz microstate oscillations","volume":"37","author":"G Hermann","year":"2024","journal-title":"Brain Topogr"},{"issue":"1","key":"pcbi.1012521.ref067","doi-asserted-by":"crossref","first-page":"24277","DOI":"10.1038\/s41598-021-03577-1","article-title":"Network oscillations imply the highest cognitive workload and lowest cognitive control during idea generation in open-ended creation tasks","volume":"11","author":"W Jia","year":"2021","journal-title":"Sci Rep"},{"issue":"47","key":"pcbi.1012521.ref068","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.adj3524","article-title":"Prenatal experience with language shapes the brain","volume":"9","author":"B Mariani","year":"2023","journal-title":"Sci Adv"},{"key":"pcbi.1012521.ref069","doi-asserted-by":"crossref","first-page":"848737","DOI":"10.3389\/fnins.2022.848737","article-title":"EEG microstate-specific functional connectivity and stroke-related alterations in brain dynamics","volume":"16","author":"Z Hao","year":"2022","journal-title":"Front Neurosci"},{"key":"pcbi.1012521.ref070","first-page":"1","article-title":"EEG microstates as a signature of hemispheric lateralization in stroke","author":"M Rubega","year":"2023","journal-title":"Brain Topogr"},{"issue":"1","key":"pcbi.1012521.ref071","doi-asserted-by":"crossref","first-page":"4051","DOI":"10.1038\/s41598-021-83425-4","article-title":"Flexible brain dynamics underpins complex behaviours as observed in Parkinson\u2019s disease","volume":"11","author":"P Sorrentino","year":"2021","journal-title":"Sci Rep"},{"issue":"21","key":"pcbi.1012521.ref072","doi-asserted-by":"crossref","DOI":"10.1212\/WNL.0000000000201200","article-title":"Flexibility of fast brain dynamics and disease severity in amyotrophic lateral sclerosis","volume":"99","author":"A Polverino","year":"2022","journal-title":"Neurology"},{"issue":"5","key":"pcbi.1012521.ref073","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1016\/j.neuron.2015.02.027","article-title":"Common behavioral clusters and subcortical anatomy in stroke","volume":"85","author":"M Corbetta","year":"2015","journal-title":"Neuron"},{"key":"pcbi.1012521.ref074","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.cortex.2020.09.024","article-title":"Cognitive brakes in interference resolution: a mouse-tracking and EEG co-registration study","volume":"133","author":"A Tafuro","year":"2020","journal-title":"Cortex"},{"issue":"78","key":"pcbi.1012521.ref075","doi-asserted-by":"crossref","first-page":"4564","DOI":"10.21105\/joss.04564","article-title":"Pycrostates: a Python library to study EEG microstates","volume":"7","author":"V F\u00e9rat","year":"2022","journal-title":"J Open Source Softw"},{"issue":"4","key":"pcbi.1012521.ref076","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1007\/s10548-008-0054-5","article-title":"Topographic ERP analyses: a step-by-step tutorial review","volume":"20","author":"MM Murray","year":"2008","journal-title":"Brain Topogr"},{"key":"pcbi.1012521.ref077","first-page":"289850","article-title":"Microstate EEGlab toolbox: an introductory guide","author":"AT Poulsen","year":"2018","journal-title":"bioRxiv"},{"issue":"1","key":"pcbi.1012521.ref078","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1006\/nimg.2002.1070","article-title":"Millisecond by millisecond, year by year: normative EEG microstates and developmental stages","volume":"16","author":"T Koenig","year":"2002","journal-title":"Neuroimage"},{"key":"pcbi.1012521.ref079","article-title":"A survey of the Schr\u00f6dinger problem and some of its connections with optimal transport","author":"C. L\u00e9onard","journal-title":"arXiv preprint arXiv:1308.0215"},{"key":"pcbi.1012521.ref080","article-title":"Sinkhorn distances: lightspeed computation of optimal transport","volume":"26","author":"M. Cuturi","year":"2013","journal-title":"Adv Neural Inf Process Syst"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1012521","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T00:00:00Z","timestamp":1729555200000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1012521","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T13:41:23Z","timestamp":1729604483000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1012521"}},"subtitle":[],"editor":[{"given":"Lyle J.","family":"Graham","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2024,10,10]]},"references-count":80,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,10,10]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1012521","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2023.12.07.570625","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,10]]}}}