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EEG-defined functional microstates as basic building blocks of mental processes
Clinical Neurophysiology 122 (2011) 1073–1074
Contents lists available at ScienceDirect
Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph
Editorial
EEG-defined functional microstates as basic building blocks of mental processes See Article, pages 1179–1182
In this issue, Kindler et al. report EEG correlates of auditoryverbal hallucinations in patients with schizophrenia by comparing the EEG when patients report hallucinations with the EEG when the patients do not report hallucinations (Kindler et al., 2011). Instead of using conventional quantitative spectral analysis of the spontaneous EEG, the authors used microstate analysis (Lehmann et al., 1987) to assess differences in the temporal organization of the topographic configuration of the scalp potential fields. A series of studies over the past 20 years has shown that the electric fields of the spontaneous EEG at rest can be classified into a few prototypical configurations, each remaining stable for around 100 ms and being terminated by abrupt transitions to another stable configuration (see Lehmann et al. (2009), or Michel et al. (2009) for recent reviews). Most of these studies found that only four microstate configurations prevail in the spontaneous EEG and that they have very similar topographies across subjects (Wackerman et al., 1993; Koenig et al., 2002; Britz et al., in press). This small number of microstates might be surprising, but given that the duration as well as the sequence of these states is variable, a rich repertoire of temporal structures is possible. These transiently stable EEG maps have been called ‘‘functional microstates’’ and it has been proposed that they represent the basic building blocks of spontaneous mentation, or ‘‘atoms of thought’’ (Lehmann et al., 1998). Several studies have shown that the temporal structure of the microstates changes as a function of the conscious/mental state of the subject, such as sleep (Wehrle et al., 2007), hypnosis (Katayama et al., 2007), centrally active medication (Lehmann et al., 1993), and mental disorders such as dementia (Strik et al., 1997), depression (Strik et al., 1995), and schizophrenia (Koenig et al., 1999; Strelets et al., 2003). In schizophrenia, a reduction in microstate duration and aberrant sequencing of the microstates has been described (Lehmann et al., 2005). The study of Kindler et al. (2011) now shows for the first time that a change in microstate characteristics is related to the presence of auditory-verbal hallucinations in schizophrenic patients. The EEG of patients differed between periods with and without hallucinations (indicated by button press) in terms of the duration of the four prototypical microstates: The duration of one of the four microstates significantly decreased during the hallucinations. What is the functional significance of this shortened microstate during hallucination? By referring to an older evoked potential study (Brandeis and Lehmann, 1989), Kindler et al. speculate that this microstate map is related to focal attention. This interpretation
would remain a bit speculative if it were merely based on this apparent topographic similarity. Identical map configurations do not necessarily indicate identical intracranial generators, and stimulus-evoked brain functions are not necessarily comparable to spontaneous EEG activity (but see Lehmann et al. (2010)). However, the authors might not have been aware that the simultaneous EEG-fMRI study by Britz et al. (2010) that they cite in their introduction strongly supports their interpretation. Britz et al. analyzed resting state EEG recorded in the scanner with the same microstate cluster analysis approach as Kindler et al. In all eight subjects Britz et al. found the same four typical microstate maps whose topographies were very similar to those described in the Kindler et al. study and the studies mentioned above. The convolution of the time course of each of these microstate maps with the hemodynamic response function revealed four of the typical resting state networks reported in several fMRI studies (Damoiseaux et al., 2006; Mantini et al., 2007). The microstate map labeled as D in Kindler et al. correlated with the dorsal attention-reorientation network. It includes the superior and middle frontal gyrus as well as the superior and inferior parietal lobules. Thus, the Britz et al. study directly confirms the interpretation of Kindler et al., namely that this map represents attentional processes. In fact, fMRI studies related the activation of ventral fronto-parietal areas to reflexive aspects of attention, while the dorsal areas are related to switching and reorientation of attention (Corbetta and Shulman, 2002; Damoiseaux et al., 2006). The diminished presence of this microstate during auditory-verbal hallucinations could thus be interpreted as diminished capabilities for attention and reorientation. While the combination of EEG and fMRI allows conclusions about the functional networks that are involved in the generation of the EEG microstates, it does not help to understand their temporal dynamics because of the low temporal resolution of the fMRI. In fact, fMRI-defined resting states fluctuate at a frequency of <0.1 Hz, while EEG-defined microstates fluctuate at frequencies of about 10 Hz. It is therefore rather surprising that the convolution with the hemodynamic response function, i.e. a strong temporal low-pass filter, still reveals significant correlations. It has very recently been shown that these significant correlations can be obtained because the EEG microstate sequences show scale-free, monofractal temporal dynamics (van de Ville et al., 2010). It is interesting that this particular temporal characteristic is abolished when equalizing the microstate duration: the microstate time course then becomes indistinguishable from white noise. Thus, the duration of the microstates is an important constitutive parameter for the scale-free characteristics of the temporal structure of the microstates. A
1388-2457/$36.00 Ó 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2010.11.003
1074
Editorial / Clinical Neurophysiology 122 (2011) 1073–1074
change of the duration of one of these microstates, as observed during auditory-verbal hallucinations in Kindler et al.’s study, might lead to an altered syntax of the microstates and consequently to an altered or even abolished fractal structure. It has been proposed that the scale-free dynamics of the microstates allows for rapid reorganization and adaptation to external events (van de Ville et al., 2010). Disturbing this structure by changing the duration of one of them (in this case the attention-reorientation network) might reduce this capability and thereby lead to the hallucinations experienced by the patients. At this point, these interpretations are still highly speculative and more studies are needed to understand the neurophysiological basis of the microstates and the mechanisms that allow the maintenance of a given microstate for several tens of milliseconds and the abrupt end and fast transition to a new microstate. However, the very high reproducibility of the microstate topographies and durations across studies, their clear correlation with distinct functional resting states defined by fMRI, the recent discovery of their monofractal temporal structure, and now the correlation with auditory-verbal hallucinations in schizophrenic patients posit microstates as promising candidates for neurophysiological representations of human conscious cognition states. References Brandeis D, Lehmann D. Segments of event-related potential map series reveal landscape changes with visual attention and subjective contours. Electroenceph Clin Neurophysiol 1989;73:507–19. Britz J, van de Ville D, Michel CM. BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage 2010;52:1162–70. Corbetta M, Shulman GL. Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci 2002;3:201–15. Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM, et al. Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA 2006;103:13848–53. Katayama H, Gianotti LR, Isotani T, Faber PL, Sasada K, Kinoshita T, et al. Classes of multichannel EEG microstates in light and deep hypnotic conditions. Brain Topogr 2007;20:7–14. Kindler J, Hubl D, Strik WK, Dierks T, Koenig T. Resting state EEG in schizophrenia: auditory verbal hallucinations are related to shortening of specific microstates. Clin Neurophysiol 2011;122(6):1179–82. Koenig T, Lehmann D, Merlo MC, Kochi K, Hell D, Koukkou M. A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest. Eur Arch Psychiatry Clin Neurosci 1999;249:205–11. Koenig T, Prichep L, Lehmann D, Sosa PV, Braeker E, Kleinlogel H, et al. Millisecond by millisecond, year by year: normative EEG microstates and developmental stages. Neuroimage 2002;16:41–8. Lehmann D, Faber PL, Galderisi S, Herrmann WM, Kinoshita T, Koukkou M, et al. EEG microstate duration and syntax in acute, medication-naive, first-episode schizophrenia: a multi-center study. Psychiatry Res 2005;138:141–56. Lehmann D, Ozaki H, Pal I. EEG alpha map series: brain micro-states by spaceoriented adaptive segmentation. Electroenceph Clin Neurophysiol 1987;67:271–88. Lehmann D, Pascual-Marqui RD, Michel CM. EEG microstates. Scholarpedia 2009;4: 7632. Available from: http://www.scholarpedia.org/article/EEG_microstates.
Lehmann D, Pascual-Marqui RD, Strik WK, Koenig T. Core networks for visualconcrete and abstract thought content: a brain electric microstate analysis. Neuroimage 2010;49:1073–9. 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. Int J Psychophysiol 1998;29:1–11. 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 Res 1993;50:275–82. Mantini D, Perrucci MG, Del Gratta C, Romani GL, Corbetta M. Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci USA 2007;104:13170–5. Michel CM, Brandeis D, Koenig T. Electrical neuroimaging in the time domain. In: Michel CM, Koenig T, Brandeis D, Gianotti LRR, Wackermann J, editors. Electrical neuroimaging. Cambridge: Cambridge University Press; 2009. p. 111–43. Strelets V, Faber PL, Golikova J, Novototsky-Vlasov V, Koenig T, Gianotti LR, et al. Chronic schizophrenics with positive symptomatology have shortened EEG microstate durations. Clin Neurophysiol 2003;114:2043–51. Strik WK, Chiaramonti R, Muscas GC, Paganini M, Mueller TJ, Fallgatter AJ, et al. Decreased EEG microstate duration and anteriorisation of the brain electrical fields in mild and moderate dementia of the Alzheimer type. Psychiatry Res 1997;75:183–91. Strik WK, Dierks T, Becker T, Lehmann D. Larger topographical variance and decreased duration of brain electric microstates in depression. J Neur Transm Gen Sect 1995;99:213–22. van de Ville D, Britz J, Michel CM. EEG microstate sequences in healthy humans at rest reveal scale-free dynamics. Proc Natl Acad Sci USA 2010;107:18179–84. Wackerman J, Lehmann D, Michel CM, Strik WK. Adaptive segmentation of spontaneous EEG map series into spatially defined microstates. Int J Psychophysiol 1993;14:269–83. Wehrle R, Kaufmann C, Wetter TC, Holsboer F, Auer DP, Pollmacher T, et al. Functional microstates within human REM sleep: first evidence from fMRI of a thalamocortical network specific for phasic REM periods. Eur J Neurosci 2007;25:863–71.
Dietrich Lehmann The KEY Institute for Brain–Mind Research, University Hospital of Psychiatry, Zurich, P.O. Box 1931, 8032 Zurich, Switzerland E-mail address: [email protected] Christoph M. Michel Functional Brain Mapping Laboratory, Dept. of Fundamental Neurosciences, University Medical School, 1 rue Michel-Servet, 1211 Geneva, Switzerland E-mail address: [email protected] Available online 3 December 2010
Contents lists available at ScienceDirect
Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph
Editorial
EEG-defined functional microstates as basic building blocks of mental processes See Article, pages 1179–1182
In this issue, Kindler et al. report EEG correlates of auditoryverbal hallucinations in patients with schizophrenia by comparing the EEG when patients report hallucinations with the EEG when the patients do not report hallucinations (Kindler et al., 2011). Instead of using conventional quantitative spectral analysis of the spontaneous EEG, the authors used microstate analysis (Lehmann et al., 1987) to assess differences in the temporal organization of the topographic configuration of the scalp potential fields. A series of studies over the past 20 years has shown that the electric fields of the spontaneous EEG at rest can be classified into a few prototypical configurations, each remaining stable for around 100 ms and being terminated by abrupt transitions to another stable configuration (see Lehmann et al. (2009), or Michel et al. (2009) for recent reviews). Most of these studies found that only four microstate configurations prevail in the spontaneous EEG and that they have very similar topographies across subjects (Wackerman et al., 1993; Koenig et al., 2002; Britz et al., in press). This small number of microstates might be surprising, but given that the duration as well as the sequence of these states is variable, a rich repertoire of temporal structures is possible. These transiently stable EEG maps have been called ‘‘functional microstates’’ and it has been proposed that they represent the basic building blocks of spontaneous mentation, or ‘‘atoms of thought’’ (Lehmann et al., 1998). Several studies have shown that the temporal structure of the microstates changes as a function of the conscious/mental state of the subject, such as sleep (Wehrle et al., 2007), hypnosis (Katayama et al., 2007), centrally active medication (Lehmann et al., 1993), and mental disorders such as dementia (Strik et al., 1997), depression (Strik et al., 1995), and schizophrenia (Koenig et al., 1999; Strelets et al., 2003). In schizophrenia, a reduction in microstate duration and aberrant sequencing of the microstates has been described (Lehmann et al., 2005). The study of Kindler et al. (2011) now shows for the first time that a change in microstate characteristics is related to the presence of auditory-verbal hallucinations in schizophrenic patients. The EEG of patients differed between periods with and without hallucinations (indicated by button press) in terms of the duration of the four prototypical microstates: The duration of one of the four microstates significantly decreased during the hallucinations. What is the functional significance of this shortened microstate during hallucination? By referring to an older evoked potential study (Brandeis and Lehmann, 1989), Kindler et al. speculate that this microstate map is related to focal attention. This interpretation
would remain a bit speculative if it were merely based on this apparent topographic similarity. Identical map configurations do not necessarily indicate identical intracranial generators, and stimulus-evoked brain functions are not necessarily comparable to spontaneous EEG activity (but see Lehmann et al. (2010)). However, the authors might not have been aware that the simultaneous EEG-fMRI study by Britz et al. (2010) that they cite in their introduction strongly supports their interpretation. Britz et al. analyzed resting state EEG recorded in the scanner with the same microstate cluster analysis approach as Kindler et al. In all eight subjects Britz et al. found the same four typical microstate maps whose topographies were very similar to those described in the Kindler et al. study and the studies mentioned above. The convolution of the time course of each of these microstate maps with the hemodynamic response function revealed four of the typical resting state networks reported in several fMRI studies (Damoiseaux et al., 2006; Mantini et al., 2007). The microstate map labeled as D in Kindler et al. correlated with the dorsal attention-reorientation network. It includes the superior and middle frontal gyrus as well as the superior and inferior parietal lobules. Thus, the Britz et al. study directly confirms the interpretation of Kindler et al., namely that this map represents attentional processes. In fact, fMRI studies related the activation of ventral fronto-parietal areas to reflexive aspects of attention, while the dorsal areas are related to switching and reorientation of attention (Corbetta and Shulman, 2002; Damoiseaux et al., 2006). The diminished presence of this microstate during auditory-verbal hallucinations could thus be interpreted as diminished capabilities for attention and reorientation. While the combination of EEG and fMRI allows conclusions about the functional networks that are involved in the generation of the EEG microstates, it does not help to understand their temporal dynamics because of the low temporal resolution of the fMRI. In fact, fMRI-defined resting states fluctuate at a frequency of <0.1 Hz, while EEG-defined microstates fluctuate at frequencies of about 10 Hz. It is therefore rather surprising that the convolution with the hemodynamic response function, i.e. a strong temporal low-pass filter, still reveals significant correlations. It has very recently been shown that these significant correlations can be obtained because the EEG microstate sequences show scale-free, monofractal temporal dynamics (van de Ville et al., 2010). It is interesting that this particular temporal characteristic is abolished when equalizing the microstate duration: the microstate time course then becomes indistinguishable from white noise. Thus, the duration of the microstates is an important constitutive parameter for the scale-free characteristics of the temporal structure of the microstates. A
1388-2457/$36.00 Ó 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2010.11.003
1074
Editorial / Clinical Neurophysiology 122 (2011) 1073–1074
change of the duration of one of these microstates, as observed during auditory-verbal hallucinations in Kindler et al.’s study, might lead to an altered syntax of the microstates and consequently to an altered or even abolished fractal structure. It has been proposed that the scale-free dynamics of the microstates allows for rapid reorganization and adaptation to external events (van de Ville et al., 2010). Disturbing this structure by changing the duration of one of them (in this case the attention-reorientation network) might reduce this capability and thereby lead to the hallucinations experienced by the patients. At this point, these interpretations are still highly speculative and more studies are needed to understand the neurophysiological basis of the microstates and the mechanisms that allow the maintenance of a given microstate for several tens of milliseconds and the abrupt end and fast transition to a new microstate. However, the very high reproducibility of the microstate topographies and durations across studies, their clear correlation with distinct functional resting states defined by fMRI, the recent discovery of their monofractal temporal structure, and now the correlation with auditory-verbal hallucinations in schizophrenic patients posit microstates as promising candidates for neurophysiological representations of human conscious cognition states. References Brandeis D, Lehmann D. Segments of event-related potential map series reveal landscape changes with visual attention and subjective contours. Electroenceph Clin Neurophysiol 1989;73:507–19. Britz J, van de Ville D, Michel CM. BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage 2010;52:1162–70. Corbetta M, Shulman GL. Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci 2002;3:201–15. Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM, et al. Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA 2006;103:13848–53. Katayama H, Gianotti LR, Isotani T, Faber PL, Sasada K, Kinoshita T, et al. Classes of multichannel EEG microstates in light and deep hypnotic conditions. Brain Topogr 2007;20:7–14. Kindler J, Hubl D, Strik WK, Dierks T, Koenig T. Resting state EEG in schizophrenia: auditory verbal hallucinations are related to shortening of specific microstates. Clin Neurophysiol 2011;122(6):1179–82. Koenig T, Lehmann D, Merlo MC, Kochi K, Hell D, Koukkou M. A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest. Eur Arch Psychiatry Clin Neurosci 1999;249:205–11. Koenig T, Prichep L, Lehmann D, Sosa PV, Braeker E, Kleinlogel H, et al. Millisecond by millisecond, year by year: normative EEG microstates and developmental stages. Neuroimage 2002;16:41–8. Lehmann D, Faber PL, Galderisi S, Herrmann WM, Kinoshita T, Koukkou M, et al. EEG microstate duration and syntax in acute, medication-naive, first-episode schizophrenia: a multi-center study. Psychiatry Res 2005;138:141–56. Lehmann D, Ozaki H, Pal I. EEG alpha map series: brain micro-states by spaceoriented adaptive segmentation. Electroenceph Clin Neurophysiol 1987;67:271–88. Lehmann D, Pascual-Marqui RD, Michel CM. EEG microstates. Scholarpedia 2009;4: 7632. Available from: http://www.scholarpedia.org/article/EEG_microstates.
Lehmann D, Pascual-Marqui RD, Strik WK, Koenig T. Core networks for visualconcrete and abstract thought content: a brain electric microstate analysis. Neuroimage 2010;49:1073–9. 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. Int J Psychophysiol 1998;29:1–11. 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 Res 1993;50:275–82. Mantini D, Perrucci MG, Del Gratta C, Romani GL, Corbetta M. Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci USA 2007;104:13170–5. Michel CM, Brandeis D, Koenig T. Electrical neuroimaging in the time domain. In: Michel CM, Koenig T, Brandeis D, Gianotti LRR, Wackermann J, editors. Electrical neuroimaging. Cambridge: Cambridge University Press; 2009. p. 111–43. Strelets V, Faber PL, Golikova J, Novototsky-Vlasov V, Koenig T, Gianotti LR, et al. Chronic schizophrenics with positive symptomatology have shortened EEG microstate durations. Clin Neurophysiol 2003;114:2043–51. Strik WK, Chiaramonti R, Muscas GC, Paganini M, Mueller TJ, Fallgatter AJ, et al. Decreased EEG microstate duration and anteriorisation of the brain electrical fields in mild and moderate dementia of the Alzheimer type. Psychiatry Res 1997;75:183–91. Strik WK, Dierks T, Becker T, Lehmann D. Larger topographical variance and decreased duration of brain electric microstates in depression. J Neur Transm Gen Sect 1995;99:213–22. van de Ville D, Britz J, Michel CM. EEG microstate sequences in healthy humans at rest reveal scale-free dynamics. Proc Natl Acad Sci USA 2010;107:18179–84. Wackerman J, Lehmann D, Michel CM, Strik WK. Adaptive segmentation of spontaneous EEG map series into spatially defined microstates. Int J Psychophysiol 1993;14:269–83. Wehrle R, Kaufmann C, Wetter TC, Holsboer F, Auer DP, Pollmacher T, et al. Functional microstates within human REM sleep: first evidence from fMRI of a thalamocortical network specific for phasic REM periods. Eur J Neurosci 2007;25:863–71.
Dietrich Lehmann The KEY Institute for Brain–Mind Research, University Hospital of Psychiatry, Zurich, P.O. Box 1931, 8032 Zurich, Switzerland E-mail address: [email protected] Christoph M. Michel Functional Brain Mapping Laboratory, Dept. of Fundamental Neurosciences, University Medical School, 1 rue Michel-Servet, 1211 Geneva, Switzerland E-mail address: [email protected] Available online 3 December 2010