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6 - Electrical neuroimaging in the time domain

Published online by Cambridge University Press:  15 December 2009

Christoph M. Michel
Université de Genève
Thomas Koenig
University Hospital of Psychiatry, Berne, Switzerland
Daniel Brandeis
Department of Child and Adolescent Psychiatry, University of Zurich, Switzerland and Central Institute of Mental Health, Mannheim, Grmany
Lorena R. R. Gianotti
Universität Zürich
Jiří Wackermann
Institute for Frontier Areas of Psychology and Mental Health, Freiburg im Breisgau, Germany
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Spatial analysis of the spontaneous EEG

Resting state and neurocognitive networks

A publication entitled “A default mode of brain function” initiated a new way of looking at functional imaging data. In this PET study the authors discussed the often-observed consistent decrease of brain activation in a variety of tasks as compared with the baseline. They suggested that this deactivation is due to a task-induced suspension of a default mode of brain function that is active during rest, i.e. that there exists intrinsic well-organized brain activity during rest in several distinct brain regions. This suggestion led to a large number of imaging studies on the resting state of the brain and to the conclusion that the study of this intrinsic activity is crucial for understanding how the brain works.

The fact that the brain is active during rest has been well known from a variety of EEG recordings for a very long time. Different states of the brain in the sleep–wake continuum are characterized by typical patterns of spontaneous oscillations in different frequency ranges and in different brain regions. Best studied are the evolving states during the different sleep stages, but characteristic EEG oscillation patterns have also been well described during awake periods (see Chapter 1 for details). A highly recommended comprehensive review on the brain's default state defined by oscillatory electrical brain activities is provided in the recent book by György Buzsaki, showing how these states can be measured by electrophysiological procedures at the global brain level as well as at the local cellular level.

Electrical Neuroimaging , pp. 111 - 144
Publisher: Cambridge University Press
Print publication year: 2009

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Raichle, ME, MacLeod, AM, Snyder, AZet al. A default mode of brain function. Proceedings of the National Academy of Sciences USA. 2001;98:676–682.CrossRefGoogle ScholarPubMed
Raichle, ME, Snyder, AZ. A default mode of brain function: a brief history of an evolving idea. Neuroimage 2007;37:1083–1090; discussion 1097–1089.CrossRefGoogle ScholarPubMed
Fox, MD, Raichle, ME. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience 2007;8:700–711.CrossRefGoogle ScholarPubMed
Lopes da Silva, F. Neural mechanisms underlying brain waves: from neural membranes to networks. Electroencephalography and Clinical Neurophysiology 1991;79:81–93.CrossRefGoogle ScholarPubMed
Buzsaki, G. Rhythms of the Brain. Oxford: Oxford University Press; 2006.CrossRefGoogle Scholar
Laufs, H, Krakow, K, Sterzer, Pet al. Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest. Proceedings of the National Academy of Sciences USA 2003;100:11053–11058.CrossRefGoogle ScholarPubMed
Laufs, H, Kleinschmidt, A, Beyerle, Aet al. EEG-correlated fMRI of human alpha activity. Neuroimage 2003;19:1463–1476.CrossRefGoogle ScholarPubMed
Laufs, H, Holt, JL, Elfont, Ret al. Where the BOLD signal goes when alpha EEG leaves. Neuroimage 2006;31:1408–1418.CrossRefGoogle ScholarPubMed
Bressler, SL. Large-scale cortical networks and cognition. Brain Research. Brain Research Reviews 1995;20:288–304.CrossRefGoogle ScholarPubMed
Mesulam, MM. From sensation to cognition. Brain 1998;121:1013–1052.CrossRefGoogle Scholar
Fuster, JM. The cognit: a network model of cortical representation. International Journal of Psychophysiology 2006;60:125–132.CrossRefGoogle ScholarPubMed
Baars, BJ. In the Theater of Consciousness: The Workspace of the Mind. Oxford: Oxford University Press; 1997.CrossRefGoogle Scholar
Baars, BJ. The conscious access hypothesis: origins and recent evidence. Trends in Cognitive Science 2002;6:47–52.CrossRefGoogle ScholarPubMed
Dehaene, S, Kerszberg, M, Changeux, JP. A neuronal model of a global workspace in effortful cognitive tasks. Proceedings of the National Academy of Sciences USA. 1998;95:14529–14534.CrossRefGoogle ScholarPubMed
Dehaene, S, Sergent, C, Changeux, JP. A neuronal network model linking subjective reports and objective physiological data during conscious perception. Proceedings of the National Academy of Sciences USA 2003;100:8520–8525.CrossRefGoogle ScholarPubMed
Dehaene, S, Naccache, L. Towards a cognitive neuroscience of consciousness: basic evidence and a workspace framework. Cognition 2001;79:1–37.CrossRefGoogle Scholar
Bressler, SL, Tognoli, E. Operational principles of neurocognitive networks. International Journal of Psychophysiology 2006;60:139–148.CrossRefGoogle ScholarPubMed
Grossberg, S.The complementary brain: unifying brain dynamics and modularity. Trends in Cognitive Science 2000;4:233–246.CrossRefGoogle ScholarPubMed
Fingelkurts, AA. Timing in cognition and EEG brain dynamics: discreteness versus continuity. Cognitive Processes 2006;7:135–162.CrossRefGoogle ScholarPubMed
Changeux, J-P, Michel, CM. Mechanism of neural integration at the brain-scale level. In Grillner, S, Graybiel, AM, eds. Microcircuits. Cambridge: MIT Press; 2004, pp. 347–370.Google Scholar
Lehmann, D, Ozaki, H, Pal, I. EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. Electroencephalography and Clinical Neurophysiology 1987;67:271–288.CrossRefGoogle ScholarPubMed
Koukkou, M, Lehmann, D.An information-processing perspective of psychophysiological measurements. Journal of Psychophysiology 1987;1:109–112.Google Scholar
Lehmann, D.Brain electric fields and brain functional states. In Friedrich, R, Wunderlin, A, eds. Evolution of Dynamical Structures in Complex Systems. Berlin: Springer; 1992, pp. 235–248.CrossRefGoogle Scholar
John, ER. A field theory of consciousness. Conscious Cognition 2001;10:184–213.CrossRefGoogle Scholar
Lehmann, D, Strik, WK, Henggeler, B, Koenig, T, Koukkou, M. Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts. International Journal of Psychophysiology 1998;29:1–11.CrossRefGoogle ScholarPubMed
Koenig, T, Prichep, L, Lehmann, Det al. Millisecond by millisecond, year by year: normative EEG microstates and developmental stages. Neuroimage 2002;16:41–48.CrossRefGoogle ScholarPubMed
Wackerman, J, Lehmann, D, Michel, CM, Strik, WK. Adaptive segmentation of spontaneous EEG map series into spatially defined microstates. International Journal of Psychophysiology 1993;14:269–283.CrossRefGoogle Scholar
Efron, R.The minimum duration of a perception. Neuropsychologia 1970;8:57–63.CrossRefGoogle ScholarPubMed
Libet, B.The experimental evidence of subjective referral of a sensory experience backward in time. Philosophy and Science 1981;48:182–197.CrossRefGoogle Scholar
Sergent, C, Dehaene, S. Neural processes underlying conscious perception: experimental findings and a global neuronal workspace framework. Journal of Physiology, Paris 2004;98:374–384.CrossRefGoogle Scholar
Strik, WK, Lehmann, D. Data determined window size and space-oriented segmentation of spontaneous EEG map series. Electroencephalography and Clinical Neurophysiology 1993;87:169–174.CrossRefGoogle ScholarPubMed
Kinoshita, T, Strik, WK, Michel, CMet al. Microstate segmentation of spontaneous multichannel EEG map series under diazepam and sulpiride. Pharmacopsychiatry 1995;28:51–55.CrossRefGoogle ScholarPubMed
Koenig, T, Lehmann, D, Merlo, MCet al. A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest. European Archives in Psychiatry and Clinical Neuroscience 1999;249:205–211.CrossRefGoogle ScholarPubMed
Strelets, V, Faber, PL, Golikova, Jet al. Chronic schizophrenics with positive symptomatology have shortened EEG microstate durations. Clinical Neurophysiology 2003;114:2043–2051.CrossRefGoogle ScholarPubMed
Kikuchi, M, Koenig, T, Wada, Yet al. Native EEG and treatment effects in neuroleptic-naive schizophrenic patients: time and frequency domain approaches. Schizophrenia Research 2007;97:163–172.CrossRefGoogle ScholarPubMed
Strik, WK, Dierks, T, Becker, T, Lehmann, D.Larger topographical variance and decreased duration of brain electric microstates in depression. Journal of Neural Transmission General Section 1995;99:213–222.CrossRefGoogle ScholarPubMed
Dierks, T, Jelic, V, Julin, Pet al. EEG-microstates in mild memory impairment and Alzheimer's disease: possible association with disturbed information processing. Journal of Neural Transmission 1997;104:483–495.CrossRefGoogle ScholarPubMed
Strik, WK, Chiaramonti, R, Muscas, GCet al. Decreased EEG microstate duration and anteriorisation of the brain electrical fields in mild and moderate dementia of the Alzheimer type. Psychiatry Research 1997;75:183–191.CrossRefGoogle ScholarPubMed
Kinoshita, T, Michel, CM, Yagyu, T, Lehmann, D, Saito, M. Diazepam and sulpiride effects on frequency domain EEG source localisations. Neuropsychobiology 1994;30:126–131.CrossRefGoogle Scholar
Katayama, H, Gianotti, LR, Isotani, Tet al. Classes of multichannel EEG microstates in light and deep hypnotic conditions. Brain Topography 2007;20:7–14.CrossRefGoogle ScholarPubMed
Lehmann, D, Faber, PL, Galderisi, Set al. EEG microstate duration and syntax in acute, medication-naive, first-episode schizophrenia: a multi-center study. Psychiatry Research 2005;138:141–156.CrossRefGoogle ScholarPubMed
Lehmann, D, Wackermann, J, Michel, CM, Koenig, T. Space-oriented EEG segmentation reveals changes in brain electric field maps under the influence of a nootropic drug. Psychiatry Research 1993;50:275–282.CrossRefGoogle ScholarPubMed
Pascual-Marqui, RD, Michel, CM, Lehmann, D. Segmentation of brain electrical activity into microstates: model estimation and validation. IEEE Transactions on Biomedical Engineering 1995;42:658–665.CrossRefGoogle Scholar
Murray, MM, Brunet, D, Michel, CM. Topographic ERP analyses: a step-by-step tutorial review. Brain Topography 2008;20:249–264.CrossRefGoogle ScholarPubMed
Skrandies, W.Data reduction of multichannel fields: global field power and principal component analysis. Brain Topography 1989;2:73–80.CrossRefGoogle ScholarPubMed
Spencer, KM, Dien, J, Donchin, E. Spatiotemporal analysis of the late ERP responses to deviant stimuli. Psychophysiology 2001;38:343–358.CrossRefGoogle ScholarPubMed
Pourtois, G, Deplanque, S, Michel C.M. et al. Beyond the conventional event-related brain potential (ERP): exploring the time-course of visual emotion processing using topographic and principal component analyses. Brain Topography 2008;20:265–277.CrossRefGoogle ScholarPubMed
Makeig, S, Westerfield, M, Jung, TPet al. Functionally independent components of the late positive event-related potential during visual spatial attention. Journal of Neuroscience 1999;19:2665–2680.CrossRefGoogle ScholarPubMed
Makeig, S, Debener, S, Onton, J, Delorme, A. Mining event-related brain dynamics. Trends in Cognitive Science 2004;8:204–210.CrossRefGoogle ScholarPubMed
Lehmann, D.Multichannel topography of human alpha EEG fields. Electroencephalography and Clinical Neurophysiology 1971;31:439–449.CrossRefGoogle ScholarPubMed
Regan, D. Human Brain Electrophysiology: Evoked Potentials and Evoked Magnetic Fields in Science and Medicine. Amsterdam: Elsevier; 1989.Google Scholar
Chiappa, KH, ed. Evoked Potentials in Clinical Medicine. 3rd edn. Philadelphia: Lippincott-Raven; 1997.Google Scholar
Luck, SJ. An Introduction to the Event-Related Potential Technique. Cambridge, MA: MIT Press; 2005.Google Scholar
Handy, TC. Event-Related Potentials: A Methods Handbook. Cambridge, MA: MIT Press; 2004.Google Scholar
Donchin, E, Isreal, JB. Event-related potentials and psychological theory. Progress in Brain Research 1980;54:697–715.CrossRefGoogle ScholarPubMed
Michel, CM, Murray, MM, Lantz, Get al. EEG source imaging. Clinical Neurophysiology 2004;115:2195–2222.CrossRefGoogle ScholarPubMed
McCarthy, G, Wood CC. Scalp distributions of event-related potentials: an ambiguity associated with analysis of variance models. Electroencephalography and Clinical Neurophysiology 1985;62:203–208.CrossRefGoogle ScholarPubMed
Vaughan, HGJ. The neural origins of human event-related potentials. Annals of the New York Academy of Sciences 1982;388:125–138.CrossRefGoogle ScholarPubMed
Khateb, A, Annoni, JM, Landis, Tet al. Spatio-temporal analysis of electric brain activity during semantic and phonological word processing. International Journal of Psychophysiology 1999;32:215–231.CrossRefGoogle ScholarPubMed
Michel, CM, Seeck, M, Murray, MM. The speed of visual cognition. Supplement in Clinical Neurophysiology 2004;57:617–627.CrossRefGoogle ScholarPubMed
Kutas, M, Hillyard, SA. Reading senseless sentences: brain potentials reflect semantic incongruity. Science 1980;207:203–205.CrossRefGoogle ScholarPubMed
Guthrie, D, Buchwald, JS. Significance testing of difference potentials. Psychophysiology 1991;28:240–244.CrossRefGoogle ScholarPubMed
Seeck, M, Mainwaring, N, Cosgrove, Ret al. Neurophysiologic correlates of implicit face memory in intracranial visual evoked potentials. Neurology 1997;49:1312–1316.CrossRefGoogle ScholarPubMed
Molholm, S, Ritter, W, Murray, MMet al. Multisensory auditory-visual interactions during early sensory processing in humans: a high-density electrical mapping study. Brain Research Cognitive Brain Research 2002;14:115–128.CrossRefGoogle ScholarPubMed
Rossell, SL, Price, CJ, Nobre, AC. The anatomy and time course of semantic priming investigated by fMRI and ERPs. Neuropsychologia 2003;41:550–564.CrossRefGoogle ScholarPubMed
Lehmann, D, Skrandies, W.Reference-free identification of components of checkerboard-evoked multichannel potential fields. Electroencephalography and Clinical Neurophysiology 1980;48:609–621.CrossRefGoogle ScholarPubMed
Michel, CM, Grave de Peralta, R, Lantz, Get al. Spatio-temporal EEG analysis and distributed source estimation in presurgical epilepsy evaluation. Journal of Clinical Neurophysiology 1999;16:225–238.CrossRefGoogle Scholar
Michel, CM, Thut, G, Morand, Set al. Electric source imaging of human brain functions. Brain Research. Brain Research Reviews 2001;36:108–118.CrossRefGoogle ScholarPubMed
Brandeis, D, Lehmann, D, Michel, CM, Mingrone, W. Mapping event-related brain potential microstates to sentence endings. Brain Topography 1995;8:145–159.CrossRefGoogle ScholarPubMed
Pegna, AJ, Khateb, A, Spinelli, Let al. Unravelling the cerebral dynamics of mental imagery. Human Brain Mapping 1997;5:410–421.3.0.CO;2-6>CrossRefGoogle Scholar
Michel, CM, Seeck, M, Landis, T. Spatiotemporal dynamics of human cognition. News in Physiological Science 1999;14:206–214.Google ScholarPubMed
Brandeis, D, Naylor, H, Halliday, R, Callaway, E, Yano, L. Scopolamine effects on visual information processing, attention, and event-related potential map latencies. Psychophysiology 1992;29:315–336.CrossRefGoogle ScholarPubMed
Cohen, L, Lehericy, S, Chochon, Fet al. Language-specific tuning of visual cortex? Functional properties of the Visual Word Form Area. Brain 2002;125:1054–1069.CrossRefGoogle ScholarPubMed
Salmelin, R.Clinical neurophysiology of language: the MEG approach. Clinical Neurophysiology 2007;118:237–254.CrossRefGoogle ScholarPubMed
Ortigue, S, Thut, G, Landis, T, Michel, CM. Time-resolved sex differences in language lateralization. Brain 2005;128:E28; author reply E29.CrossRefGoogle ScholarPubMed
James, CE, Britz, J, Vuilleumier, P, Hauert, CA, Michel, CM. Early neuronal responses in right limbic structures mediate harmony incongruity processing in musical experts. Neuroimage 2008;42:1597–1608.CrossRefGoogle ScholarPubMed
Bottini, G, Corcoran, R, Sterzi, Ret al. The role of the right hemisphere in the interpretation of figurative aspects of language. A positron emission tomography activation study. Brain 1994;117:1241–1253.CrossRefGoogle Scholar
Kuperberg, GR, McGuire, PK, Bullmore, ETet al. Common and distinct neural substrates for pragmatic, semantic, and syntactic processing of spoken sentences: an fMRI study. Journal of Cognitive Neuroscience 2000;12:321–341.CrossRefGoogle ScholarPubMed
St George, M, Kutas, M, Martinez, A, Sereno, MI. Semantic integration in reading: engagement of the right hemisphere during discourse processing. Brain 1999;122:1317–1325.CrossRefGoogle ScholarPubMed
Rossell, SL, Bullmore, ET, Williams, SC, David, AS. Brain activation during automatic and controlled processing of semantic relations: a priming experiment using lexical-decision. Neuropsychologia 2001;39:1167–1176.CrossRefGoogle ScholarPubMed
Schulz, E, Maurer, U, Mark, Set al. Impaired semantic processing during sentence reading in children with dyslexia: combined fMRI and ERP evidence. Neuroimage 2008;41:153–168.CrossRefGoogle ScholarPubMed
Lehmann, D, Skrandies, W. Spatial analysis of evoked potentials in man – a review. Progress in Neurobiology 1984;23:227–250.CrossRefGoogle ScholarPubMed
Skrandies, W.Global field power and topographic similarity. Brain Topography 1990;3:137–141.CrossRefGoogle ScholarPubMed
Skrandies, W. EEG/EP: new techniques. Brain Topography 1993;5:347–350.CrossRefGoogle Scholar
Brandeis, D, Lehmann D, . Event-related potentials of the brain and cognitive processes: approaches and applications. Neuropsychologia 1986;24:151–168.CrossRefGoogle ScholarPubMed
Morand, S, Thut, G, Grave de Peralta, Ret al. Electrophysiological evidence for fast visual processing through the human koniocellular pathway when stimuli move. Cerebral Cortex 2000;10:817–825.CrossRefGoogle ScholarPubMed
Ducommun, CY, Murray, MM, Thut, Get al. Segregated processing of auditory motion and auditory location: an ERP mapping study. Neuroimage 2002;16:76–88.CrossRefGoogle ScholarPubMed
Leonards, U, Palix, J, Michel, C, Ibanez, V. Comparison of early cortical networks in efficient and inefficient visual search: an event-related potential study. Journal of Cognitive Neuroscience 2003;15:1039–1051.CrossRefGoogle ScholarPubMed
Pegna, AJ, Khateb, A, Murray, MM, Landis, T, Michel, CM. Neural processing of illusory and real contours revealed by high-density ERP mapping. Neuroreport 2002;13:965–968.CrossRefGoogle ScholarPubMed
Pegna, AJ, Khateb, A, Michel, CM, Landis, T. Visual recognition of faces, objects, and words using degraded stimuli: where and when it occurs. Human Brain Mapping 2004;22:300–311.CrossRefGoogle ScholarPubMed
Murray, MM, Foxe, JJ, Higgins, BA, Javitt, DC, Schroeder, CE. Visuo-spatial neural response interactions in early cortical processing during a simple reaction time task: a high-density electrical mapping study. Neuropsychologia 2001;39:828–844.CrossRefGoogle ScholarPubMed
Murray, MM, Molholm, S, Michel, CMet al. Grabbing your ear: rapid auditory-somatosensory multisensory interactions in low-level sensory cortices are not constrained by stimulus alignment. Cerebral Cortex 2005;15:963–974.CrossRefGoogle Scholar
Murray, MM, Camen, C, Gonzalez Andino, SL, Bovet, P, Clarke, S. Rapid brain discrimination of sounds of objects. Journal of Neuroscience 2006;26:1293–1302.CrossRefGoogle Scholar
Murray, MM, Imber, ML, Javitt, DC, Foxe, JJ. Boundary completion is automatic and dissociable from shape discrimination. Journal of Neuroscience 2006;26:12043–12054.CrossRefGoogle ScholarPubMed
Santis, L, Clarke, S, Murray, MM. Automatic and intrinsic auditory “what” and “where” processing in humans revealed by electrical neuroimaging. Cerebral Cortex 2007;17:9–17.CrossRefGoogle Scholar
Santis, L, Spierer, L, Clarke, S, Murray, MM. Getting in touch: segregated somatosensory what and where pathways in humans revealed by electrical neuroimaging. Neuroimage 2007;37:890–903.CrossRefGoogle ScholarPubMed
Thut, G, Hauert, CA, Morand, S, Seeck, M, Landis, T, Michel, C. Evidence for interhemispheric motor-level transfer in a simple reaction time task: an EEG study. Experimental Brain Research 1999;128:256–261.CrossRefGoogle Scholar
Thut, G, Hauert, CA, Viviani, Pet al. Internally driven versus externally cued movement selection: a study on the timing of brain activity. Cognitive Brain Research 2000;9:261–269.CrossRefGoogle Scholar
Caldara, R, Deiber, MP, Andrey, Cet al. Actual and mental motor preparation and execution: a spatiotemporal ERP study. Experimental Brain Research 2004;159:389–399.CrossRefGoogle ScholarPubMed
Khateb, A, Michel, CM, Pegna, AJ, Landis, T, Annoni, JM. New insights into the Stroop effect: a spatio-temporal analysis of electric brain activity. Neuroreport 2000;11:1849–1855.CrossRefGoogle ScholarPubMed
Gonzalez Andino, SL, Michel, CM, Thut, G, Landis, T, Grave de Peralta, R. Prediction of response speed by anticipatory high-frequency (gamma band) oscillations in the human brain. Human Brain Mapping 2005;24:50–58.CrossRefGoogle ScholarPubMed
Schnider, A, Valenza, N, Morand, S, Michel, CM. Early cortical distinction between memories that pertain to ongoing reality and memories that don't. Cerebral Cortex 2002;12:54–61.CrossRefGoogle ScholarPubMed
Schnider, A, Mohr, C, Morand, S, Michel, CM. Early cortical response to behaviorally relevant absence of anticipated outcomes: a human event-related potential study. Neuroimage 2007;35:1348–1355.CrossRefGoogle ScholarPubMed
Murray, MM, Michel, CM, Grave de Peralta, Ret al. Rapid discrimination of visual and multisensory memories revealed by electrical neuroimaging. Neuroimage 2004;21:125–135.CrossRefGoogle ScholarPubMed
Khateb, A, Michel, CM, Pegna, AJet al. The time course of semantic category processing in the cerebral hemispheres: an electrophysiological study. Cognitive Brain Research 2001;10:251–264.CrossRefGoogle ScholarPubMed
Khateb, A, Michel, CM, Pegna, AJet al. Processing of semantic categorical and associative relations: an ERP mapping study. International Journal of Psychophysiology 2003;49:41–55.CrossRefGoogle ScholarPubMed
Khateb, A, Pegna, AJ, Landis, Tet al. Rhyme processing in the brain: an ERP mapping study. International Journal of Psychophysiology 2007;63:240–250.CrossRefGoogle ScholarPubMed
Khateb, A, Abutalebi, J, Michel, CMet al. Language selection in bilinguals: a spatio-temporal analysis of electric brain activity. International Journal of Psychophysiology 2007;65:201–213.CrossRefGoogle ScholarPubMed
Wirth, M, Horn, H, Koenig, Tet al. Sex differences in semantic processing: event-related brain potentials distinguish between lower and higher order semantic analysis during word reading. Cerebral Cortex 2007;17:1987–1997.CrossRefGoogle ScholarPubMed
Ortigue, S, Michel, CM, Murray, MMet al. Electrical neuroimaging reveals early generator modulation to emotional words. Neuroimage 2004;21:1242–1251.CrossRefGoogle ScholarPubMed
Pourtois, G, Thut, G, Grave de Peralta, R, Michel, C, Vuilleumier, P. Two electrophysiological stages of spatial orienting towards fearful faces: early temporo-parietal activation preceding gain control in extrastriate visual cortex. Neuroimage 2005;26:149–163.CrossRefGoogle ScholarPubMed
Gianotti, LR, Faber, PL, Schuler, Met al. First valence, then arousal: the temporal dynamics of brain electric activity evoked by emotional stimuli. Brain Topography 2008;20:143–156.CrossRefGoogle ScholarPubMed
Caldara, R, Thut, G, Servoir, Pet al. Face versus non-face object perception and the ‘other-race’ effect: a spatio-temporal event-related potential study. Clinical Neurophysiology 2003;114:515–528.CrossRefGoogle ScholarPubMed
Thierry, G, Martin, CD, Downing, P, Pegna, AJ. Controlling for interstimulus perceptual variance abolishes N170 face selectivity. Nature Neuroscience 2007;10:505–511.CrossRefGoogle ScholarPubMed
Petit, LS, Pegna, AJ, Harris, IM, Michel, CM. Automatic motor cortex activation for natural as compared to awkward grips of a manipulable object. Experimental Brain Research 2006;168:120–130.CrossRefGoogle ScholarPubMed
Overney, LS, Michel, CM, Harris, IM, Pegna, AJ. Cerebral processes in mental transformations of body parts: recognition prior to rotation. Brain Research. Cognitive Brain Research 2005;25:722–734.CrossRefGoogle ScholarPubMed
Blanke, O, Mohr, C, Michel, CMet al. Linking out-of-body experience and self processing to mental own-body imagery at the temporoparietal junction. Journal of Neuroscience 2005;25:550–557.CrossRefGoogle ScholarPubMed
Arzy, S, Thut, G, Mohr, C, Michel, CM, Blanke, O. Neural basis of embodiment: distinct contributions of temporoparietal junction and extrastriate body area. Journal of Neuroscience 2006;26:8074–8081.CrossRefGoogle ScholarPubMed
Seeck, M, Michel, CM, Mainwaring, Net al. Evidence for rapid face recognition from human scalp and intracranial electrodes. Neuroreport 1997;8:2749–2754.CrossRefGoogle ScholarPubMed
Koenig, T, Lehmann, D. Microstates in language-related brain potential maps show noun-verb differences. Brain and Language 1996;53:169–182.CrossRefGoogle ScholarPubMed
Tardif, E, Murray, MM, Meylan, R, Spierer, L, Clarke, S. The spatio-temporal brain dynamics of processing and integrating sound localization cues in humans. Brain Research 2006;1092:161–176.CrossRefGoogle ScholarPubMed
Thorpe, S, Fize, D, Marlot, C. Speed of processing in the human visual system. Nature 1996;381:520–522.CrossRefGoogle ScholarPubMed
Schroeder, CE, Mehta, AD, Givre, SJ. A spatiotemporal profile of visual system activation revealed by current source density analysis in the awake macaque. Cerebral Cortex 1998;8:575–592.CrossRefGoogle ScholarPubMed
Bullier, J.Integrated model of visual processing. Brain Research. Brain Research Review 2001;36:96–107.CrossRefGoogle ScholarPubMed
Arieli, A, Sterkin, A, Grinvald, A, Aertsen, A. Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses. Science 1996;273:1868–1871.CrossRefGoogle ScholarPubMed
Fries, P, Neuenschwander, S, Engel, AK, Goebel, R, Singer, W. Rapid feature selective neuronal synchronization through correlated latency shifting. Nature Neuroscience 2001;4:194–200.CrossRefGoogle ScholarPubMed
Togt, C, Spekreijse, H, Super, H. Neural responses in cat visual cortex reflect state changes in correlated activity. European Journal of Neuroscience 2005;22:465–475.CrossRefGoogle ScholarPubMed
Super, H, Togt, C, Spekreijse, H, Lamme, VA. Internal state of monkey primary visual cortex (V1) predicts figure-ground perception. Journal of Neuroscience 2003;23:3407–3414.CrossRefGoogle ScholarPubMed
Togt, C, Kalitzin, S, Spekreijse, H, Lamme, VA, Super, H. Synchrony dynamics in monkey V1 predict success in visual detection. Cerebral Cortex 2006;16:136–148.CrossRefGoogle ScholarPubMed
Womelsdorf, T, Fries, P, Mitra, PP, Desimone, R. Gamma-band synchronization in visual cortex predicts speed of change detection. Nature 2006;439:733–736.CrossRefGoogle ScholarPubMed
Ergenoglu, T, Demiralp, T, Bayraktaroglu, Zet al. Alpha rhythm of the EEG modulates visual detection performance in humans. Brain Research. Cognitive Brain Research 2004;20:376–383.CrossRefGoogle ScholarPubMed
Hanslmayr, S, Sauseng, P, Doppelmayr, M, Schabus, M, Klimesch, W. Increasing individual upper alpha power by neurofeedback improves cognitive performance in human subjects. Applied Psychophysiology and Biofeedback 2005;30:1–10.CrossRefGoogle ScholarPubMed
Babiloni, C, Vecchio, F, Bultrini, A, Luca Romani, G, Rossini, PM. Pre- and poststimulus alpha rhythms are related to conscious visual perception: a high-resolution EEG study. Cerebral Cortex 2006;16:1690–1700.CrossRefGoogle ScholarPubMed
Thut, G, Nietzel, A, Brandt, SA, Pascual-Leone, A. Alpha-band electroencephalographic activity over occipital cortex indexes visuospatial attention bias and predicts visual target detection. Journal of Neuroscience 2006;26:9494–9502.CrossRefGoogle ScholarPubMed
Rihs, TA, Michel, CM, Thut, G. Mechanisms of selective inhibition in visual spatial attention are indexed by alpha-band EEG synchronization. European Journal of Neuroscience 2007;25:603–610.CrossRefGoogle ScholarPubMed
Romei, V, Brodbeck, V, Michel, Cet al. Spontaneous fluctuations in posterior {alpha}-band EEG activity reflect variability in excitability of human visual areas. Cerebral Cortex 2008;18:2010–2018.CrossRefGoogle ScholarPubMed
Ress, D, Backus, BT, Heeger, DJ. Activity in primary visual cortex predicts performance in a visual detection task. Nature Neuroscience 2000;3:940–945.CrossRefGoogle Scholar
Fox, MD, Snyder, AZ, Zacks, JM, Raichle, ME. Coherent spontaneous activity accounts for trial-to-trial variability in human evoked brain responses. Nature Neuroscience 2006;9:23–25.CrossRefGoogle ScholarPubMed
Lehmann, D, Michel, CM, Pal, I, Pascual-Marqui, RD. Event-related potential maps depend on prestimulus brain electric microstate map. International Journal of Neuroscience 1994;74:239–248.CrossRefGoogle ScholarPubMed
Kondakor, I, Pascual-Marqui, RD, Michel, CM, Lehmann, D. Event-related potential map differences depend on the prestimulus microstates. Journal of Medical Engineering and Technology 1995;19:66–69.CrossRefGoogle ScholarPubMed
Kondakor, I, Lehmann, D, Michel, CMet al. Prestimulus EEG microstates influence visual event-related potential microstates in field maps with 47 channels. Journal of Neural Transmission 1997;104:161–173.CrossRefGoogle ScholarPubMed
Müller, TJ, Koenig, T, Wackermann, Jet al. Subsecond changes of global brain state in illusory multistable motion perception. Journal of Neural Transmission 2005;112:565–576.CrossRefGoogle Scholar
Müller, TJ, Federspiel, A, Fallgatter, AJ, Strik, WK. EEG signs of vigilance fluctuations preceding perceptual flips in multistable illusionary motion. Neuroreport 1999;10:3423–3427.CrossRefGoogle ScholarPubMed
Mohr, C, Michel, CM, Lantz, Get al. Brain state-dependent functional hemispheric specialization in men but not in women. Cerebral Cortex 2005;15:1451–1458.CrossRefGoogle Scholar
Graves, R, Landis, T, Goodglass, H. Laterality and sex differences for visual recognition of emotional and non-emotional words. Neuropsychologia 1981;19:95–102.CrossRefGoogle ScholarPubMed
Britz, J, Landis, T, Michel, CM. Right parietal brain activity precedes perceptual alternation of bistable stimuli. Cerebral Cortex 2009;19:55–65.CrossRefGoogle ScholarPubMed
Makeig, S, Westerfield, M, Jung, TPet al. Dynamic brain sources of visual evoked responses. Science 2002;295:690–694.CrossRefGoogle ScholarPubMed
Quian Quiroga, R, Garcia, H. Single-trial event-related potentials with wavelet denoising. Clinical Neurophysiology 2003;114:376–390.CrossRefGoogle ScholarPubMed
Knuth, KH, Shah, AS, Truccolo, WAet al. Differentially variable component analysis: identifying multiple evoked components using trial-to-trial variability. Journal of Neurophysiology 2006;95:3257–3276.CrossRefGoogle ScholarPubMed
Jongsma, ML, Eichele, T, Rijn, CMet al. Tracking pattern learning with single-trial event-related potentials. Clinical Neurophysiology 2006;117:1957–1973.CrossRefGoogle ScholarPubMed
Quian Quiroga, R, Luijtelaar, EL. Habituation and sensitization in rat auditory evoked potentials: a single-trial analysis with wavelet denoising. International Journal of Psychophysiology 2002;43:141–153.CrossRefGoogle ScholarPubMed
Quian Quiroga, R, Snyder, LH, Batista, AP, Cui, H, Andersen, RA. Movement intention is better predicted than attention in the posterior parietal cortex. Journal of Neuroscience 2006;26:3615–3620.CrossRefGoogle ScholarPubMed
Singer, W.Synchronization of cortical activity and its putative role in information processing and learning. Annual Review of Physiology 1993;55:349–374.CrossRefGoogle Scholar
Engel, AK, Fries, P, Singer, W. Dynamic predictions: oscillations and synchrony in top-down processing. Nature Review Neuroscience 2001;2:704–716.CrossRefGoogle ScholarPubMed
Lee, KH, Williams, LM, Breakspear, M, Gordon, E. Synchronous gamma activity: a review and contribution to an integrative neuroscience model of schizophrenia. Brain Research. Brain Research Review 2003;41:57–78.CrossRefGoogle Scholar
Bell, AJ, Sejnowski, TJ. An information-maximization approach to blind separation and blind deconvolution. Neural Comput 1995;7:1129–1159.CrossRefGoogle ScholarPubMed
Hyvarinen, A, Oja, E. A fast fixed-point algorithm for independent component analysis. Neural Computation 1997;9:1483–1492.CrossRefGoogle Scholar
Vigario, RN. Extraction of ocular artefacts from EEG using independent component analysis. Electroencephalography and Clinical Neurophysiology 1997;103:395–404.CrossRefGoogle ScholarPubMed
Barbati, G, Porcaro, C, Zappasodi, F, Rossini, PM, Tecchio, F. Optimization of an independent component analysis approach for artifact identification and removal in magnetoencephalographic signals. Clinical Neurophysiology 2004;115:1220–1232.CrossRefGoogle ScholarPubMed
Delorme, A, Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods 2004;134:9–21.CrossRefGoogle ScholarPubMed
Mantini, D, Franciotti, R, Romani, GL, Pizzella, V. Improving MEG source localizations: an automated method for complete artifact removal based on independent component analysis. Neuroimage 2008;40:160–173.CrossRefGoogle ScholarPubMed
Nakamura, W, Anami, K, Mori, Tet al. Removal of ballistocardiogram artifacts from simultaneously recorded EEG and fMRI data using independent component analysis. IEEE Transactions on Biomedical Engineering 2006;53:1294–1308.CrossRefGoogle ScholarPubMed
Mantini, D, Perrucci, MG, Cugini, Set al. Complete artifact removal for EEG recorded during continuous fMRI using independent component analysis. Neuroimage 2007;34:598–607.CrossRefGoogle ScholarPubMed
Grouiller, F, Vercueil, L, Krainik, Aet al. A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI. Neuroimage 2007;38:124–137.CrossRefGoogle ScholarPubMed
Womelsdorf, T, Schoffelen, JM, Oostenveld, Ret al. Modulation of neuronal interactions through neuronal synchronization. Science 2007;316:1609–1612.CrossRefGoogle ScholarPubMed
Onton, J, Delorme, A, Makeig, S. Frontal midline EEG dynamics during working memory. Neuroimage 2005;27:341–356.CrossRefGoogle ScholarPubMed
Onton, J, Westerfield, M, Townsend, J, Makeig, S. Imaging human EEG dynamics using independent component analysis. Neuroscience and Biobehavioral Reviews 2006;30:808–822.CrossRefGoogle ScholarPubMed
Makeig, S. Response: event-related brain dynamics – unifying brain electrophysiology. Trends in Neuroscience 2002;25:390.CrossRefGoogle ScholarPubMed
Jansen, BH, Agarwal, G, Hegde, A, Boutros, NN. Phase synchronization of the ongoing EEG and auditory EP generation. Clinical Neurophysiology 2003;114:79–85.CrossRefGoogle ScholarPubMed
Shah, AS, Bressler, SL, Knuth, KHet al. Neural dynamics and the fundamental mechanisms of event-related brain potentials. Cerebral Cortex 2004;14:476–483.CrossRefGoogle ScholarPubMed
Belouchrani, A, Abed-Merain, K, Cardoso, J-F, Moulines, E. A blind source separation technique using second-order statistics. IEEE Transactions on Signaling Processes 1997;5:434–444.CrossRefGoogle Scholar
Barbati, G, Sigismondi, R, Zappasodi, Fet al. Functional source separation from magnetoencephalographic signals. Human Brain Mapping 2006;27:925–934.CrossRefGoogle ScholarPubMed
Georgiadis, SD, Ranta-aho, PO, Tarvainen, MP, Karjalainen, PA. Single-trial dynamical estimation of event-related potentials: a Kalman filter-based approach. IEEE Transactions on Biomedical Engineering 2005;52:1397–1406.CrossRefGoogle ScholarPubMed
Wang, Z, Maier, A, Leopold, DA, Logothetis, NK, Liang, H. Single-trial evoked potential estimation using wavelets. Computers in Biology and Medicine 2007;37:463–473.CrossRefGoogle ScholarPubMed
Bai, O, Lin, P, Vorbach, Set al. Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG. Clinical Neurophysiology 2007;118:2637–2655.CrossRefGoogle ScholarPubMed
Muller, KR, Tangermann, M, Dornhege, Get al. Machine learning for real-time single-trial EEG-analysis: from brain-computer interfacing to mental state monitoring. Journal of Neuroscientific Methods 2008;167:82–90.CrossRefGoogle ScholarPubMed
Lucia, M, Michel, CM, Clarke, S, Murray, MM. Single-trial topographic analysis of human EEG: a new ‘image’ of event-related potentials. Proceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB 2007; article 4407353, pp 95–98.Google Scholar
Lucia, M, Michel, CM, Clarke, S, Murray, MM. Single subject EEG analysis based on topographic information. International Journal of Bioelectromagnetism 2007;9:168–171.Google Scholar
Alarcon, G, Guy, CN, Binnie, CDet al. Intracerebral propagation of interictal activity in partial epilepsy: implications for source localisation. Journal of Neurology, Neurosurgery and Psychiatry 1994;57:435–449.CrossRefGoogle ScholarPubMed
Engel, J, Jr. Intracerebral recordings: organization of the human epileptogenic region. Journal of Clinical Neurophysiology 1993;10:90–98.CrossRefGoogle ScholarPubMed
Alarcon, G, Seoane, JJG, Binnie, CDet al. Origin and propagation of interictal discharges in the acute electrocorticogram. Implications for pathophysiology and surgical treatment of temporal lobe epilepsy. Brain 1997;120:259–282.CrossRefGoogle ScholarPubMed
Ebersole, JS. Non-invasive pre-surgical evaluation with EEG/MEG source analysis. Electroencephalography and Clinical Neurophysiology Supplement 1999;50:167–174.Google ScholarPubMed
Merlet, I, Gotman, J. Reliability of dipole models of epileptic spikes. Clinical Neurophysiology 1999;110:1013–1028.CrossRefGoogle ScholarPubMed
Scherg, M, Bast, T, Berg, P. Multiple source analysis of interictal spikes: goals, requirements, and clinical value. Journal of Clinical Neurophysiology 1999;16:214–224.CrossRefGoogle ScholarPubMed
Huppertz, HJ, Hoegg, S, Sick, Cet al. Cortical current density reconstruction of interictal epileptiform activity in temporal lobe epilepsy. Clinical Neurophysiology 2001;112:1761–1772.CrossRefGoogle ScholarPubMed
Merlet, I, Garcia-Larrea, L, Gregoire, MC, Lavenne, F, Mauguière, F. Source propagation of interictal spikes in temporal lobe epilepsy. Correlations between spike dipole modelling and [18F]fluorodeoxyglucose PET data. Brain 1996;119:377–392.CrossRefGoogle ScholarPubMed
Seeck, M, Lazeyras, F, Michel, CMet al. Non invasive epileptic focus localization using EEG-triggered functional MRI and electromagnetic tomography. Electroencephalography and Clinical Neurophysiology 1998;106:508–512.CrossRefGoogle ScholarPubMed
Lantz, G, Spinelli, L, Menendez, RG, Seeck, M, Michel, CM. Localization of distributed sources and comparison with functional MRI. Epileptic Disorders 2001;Special Issue:45–58.Google ScholarPubMed
Lantz, G, Michel, CM, Pascual-Marqui, RDet al. Extracranial localization of intracranial interictal epileptiform activity using LORETA (low resolution electromagnetic tomography). Electroencephalography and Clinical Neurophysiology 1997;102:414–422.CrossRefGoogle Scholar
Lantz, G, Grave de Peralta, R, Gonzalez, S, Michel, CM. Noninvasive localization of electromagnetic epileptic activity. II. Demonstration of sublobar accuracy in patients with simultaneous surface and depth recordings. Brain Topography 2001;14:139–147.CrossRefGoogle ScholarPubMed
Lantz, G, Spinelli, L, Seeck, Met al. Propagation of interictal epileptiform activity can lead to erroneous source localizations: a 128 channel EEG mapping study. Journal of Clinical Neurophysiology 2003;20:311–319.CrossRefGoogle ScholarPubMed
Lantz, G, Grave de Peralta, R, Spinelli, L, Seeck, M, Michel, CM. Epileptic source localization with high density EEG: how many electrodes are needed? Clinical Neurophysiology 2003;114:63–69.CrossRefGoogle ScholarPubMed
Michel, CM, Lantz, G, Spinelli, Let al. 128-channel EEG source imaging in epilepsy: clinical yield and localization precision. Journal of Clinical Neurophysiology 2004;21:71–83.CrossRefGoogle ScholarPubMed
Sperli, F, Spinelli, L, Seeck, Met al. EEG source imaging in paediatric epilepsy surgery: a new perspective in presurgical workup. Epilepsia 2006;47:981–990.CrossRefGoogle Scholar
Zumsteg, D, Friedman, A, Wennberg, RA, Wieser, HG. Source localization of mesial temporal interictal epileptiform discharges: correlation with intracranial foramen ovale electrode recordings. Clinical Neurophysiology 2005;116:2810–2818.CrossRefGoogle ScholarPubMed
Zumsteg, D, Andrade, DM, Wennberg, RA. Source localization of small sharp spikes: low resolution electromagnetic tomography (LORETA) reveals two distinct cortical sources. Clinical Neurophysiology 2006;117:1380–1387.CrossRefGoogle ScholarPubMed
Zumsteg, D, Friedman, A, Wieser, HG, Wennberg, RA. Source localization of interictal epileptiform discharges: comparison of three different techniques to improve signal to noise ratio. Clinical Neurophysiology 2006;117:562–571.CrossRefGoogle ScholarPubMed
Holmes, MD, Brown, M, Tucker, DM. Are “generalized” seizures truly generalized? Evidence of localized mesial frontal and frontopolar discharges in absence. Epilepsia 2004;45:1568–1579.CrossRefGoogle ScholarPubMed
Worrell, GA, Lagerlund, TD, Sharbrough, FWet al. Localization of the epileptic focus by low-resolution electromagnetic tomography in patients with a lesion demonstrated by MRI. Brain Topography 2000;12:273–282.CrossRefGoogle ScholarPubMed
Grave de Peralta Menendez, R, Gonzalez Andino, S, Lantz, G, Michel, CM, Landis, T. Noninvasive localization of electromagnetic epileptic activity. I. Method descriptions and simulations. Brain Topography 2001;14:131–137.CrossRefGoogle ScholarPubMed
Spinelli, L, Andino, SG, Lantz, G, Seeck, M, Michel, CM. Electromagnetic inverse solutions in anatomically constrained spherical head models. Brain Topography 2000;13:115–125.CrossRefGoogle ScholarPubMed
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