A complex system such as the brain that comprises many local functional states can be said to be in one particular global functional state at each moment in time (Ashby, 1960). Brain states change in a non-continuous manner: brain functional state over time shows extended periods during which there is small variance of state; these periods of quasi-stability are concatenated by rapid and major changes of state. An example is wakeful consciousness and its sudden disappearance with sleep onset. Such state changes are associated with major changes in brain electric activity as recorded from the scalp of the intact human head as electroencephalogram ("EEG"). In the sub-second time range which is relevant for human conscious mentation and for useful interaction with the environment, brain electric activity can be parsed into brief split second microstates characterized by quasi-stable spatial distributions (landscapes) of electric potential that are connected by quick changes in landscapes. As different electric potential landscapes must have been generated by different distributions of neuronal electric activity in the brain, it is reasonable to assume that different microstates embody different functions of the brain. The experimental results suggest that the seemingly continual stream of consciousness is incorporated by successive steps of brain operations, reminiscent of the flight-perch-sequences of subjective experience (James, 1890). Microstate analysis has begun to develop a dictionary of functions of these sub-second brain microstates and to explore their syntax.
Brain electric fields
Brain electric field data (EEG and event-related potentials [ERP]) recorded simultaneously from many electrodes (locations) on the human head surface can be viewed as series of maps of the momentary spatial distributions of electric potential, as 'potential landscapes' (Lehmann, 1971, 1972). Typically, 128 to 512 maps per second are used.
The historical and unfortunate discussions in the EEG community about the choice of a presumable 'inactive' electric reference location are not an issue here, because a given landscape cannot be changed by the location of the point from which it is measured; this choice merely determines the value labels of the isopotential lines - quite like the rising or receding water level of a lake in a mountainous area changes the location of the zero water level mark, but not the landscape (Lehmann, 1987; Geselowitz, 1998).
Over time, the potential landscapes vary in electric strength. Map Hilliness (Lehmann, 1971) assesses map strength; it is defined as the sum of the absolute microvolt values measured at all electrodes divided by the number of electrodes; the assessment must be done after the values in each map have been expressed as deviations from the mean of all momentary values (spatial DC offset removal, 'average reference'). Global Field Power is a related, parametric assessment of map strength, computed as standard deviation of the momentary potential values (Lehmann and Skrandies, 1980).
Over time, the potential landscapes vary also in configuration. For numerical comparisons of map landscapes, Global Map Dissimilarity is computed (Lehmann and Skrandies, 1980): The two maps to be compared are average-referenced and scaled to unity Global Field Power; then, one map is subtracted form the other one. The value of Global Field Power of the resulting difference map is the magnitude of Global Map Dissimilarity.
Statistical comparison of potential landscapes between experimental conditions or between different groups of subjects uses as dependent measure Global Map Dissimilarity, or extracted parameters such as the location of the two centroid locations of the map's positive and negative potential areas (Wackermann et al., 1993) or the electric gravity center (the mean of the two centroid locations); all are strength-independent measures. Such analyses determine whether different neuronal generators have been involved in the different conditions or groups at a given time. Typically, non-parametric randomization tests are used (Karniski et al. 1994; Kondakor et al., 1995; Strik et al., 1998; see Murray et al., 2008). Statistical assessment of the specificity of the microstates for different experimental conditions has been achieved by spatial fitting procedures using Global Map Dissimilarity as metric (Brandeis et al., 1992; Pegna et al., 1997; Michel et al., 1999; Michel et al., 2001; Murray et al., 2008).
Parsing the series of momentary potential maps into microstates
In continually recorded human EEG, series of momentary maps of electric potential landscapes during task-free resting show discontinuous changes of landscapes (Lehmann, 1971, 1972). The movie (Fig. 1) visualizes this: it shows the sequence of EEG landscapes recorded from 19 electrodes during a 2 second epoch from a healthy young man who was asked to relax with closed eyes (128 maps per second; the head is seen from above, nose up; red are positive, blue are negative potential regions referenced to the mean of all momentary potentials).
Map strength in general is irrelevant for landscape comparisons: only the spatial configuration of the potential distribution is considered when assessing map similarity. In the case of EEG where there is oscillatory activity of the generator processes, polarity also is irrelevant. In the case of event-related potential (ERP) maps, map polarity is important; polarity was used to label the conventional 'components', the peaks and troughs of ERP waveshapes.In EEG as well as ERP map series, for brief, sub-second time periods, map landscapes typically remain quasi-stable, then change very quickly into different landscapes. A sequential microstate analysis approach first showed the feature of non-continuity of landscape changes in spontaneous EEG, using plots of the electrode locations of extreme (maximum or minimum) potential values over time. Fig. 2 shows such plots for the movie sequence of Fig. 1
Functional significance of EEG microstatesIn spontaneous EEG, four standard classes of microstate landscapes were distinguished (Fig. 6), whose parameters (e.g. duration, occurrences per second, covered percentage of analysis time) change as function of age (Koenig et al., 2002). hypnosis (Katayama et al., 2007), and to increase in meditation (Faber et al., 2005). Cognition-enhancing medication affected microstate topography in a dose-dependent way (Lehmann et al., 1993). Spontaneous thoughts which are high or low on a visual imagery scale are associated with two different EEG microstate classes immediately before the prompted reports (Lehmann et al., 1998); these spontaneous microstates and event-related microstates 286-354 ms post-stimulus while reading abstract or imagery words (Koenig et al., 1998) when analyzed with tomographic imaging ('LORETA', Pascual-Marqui et al., (1994) showed common activated intracerebral brain areas: left anterior brain areas for abstract, right posterior for imagery (Lehmann et al., 2004).
Microstates as atoms of thought and consciousness
Durations of microstates during spontaneous task-free resting EEG on average are in the range of 70 to 125 milliseconds (Lehmann et al., 1987, 1998, 2005; Koenig et al., 2002). The type of momentary thought (e.g. visual versus abstract thinking) is incorporated in different microstates (Lehmann et al., 1998, 2004). The observations on microstates in spontaneous brain electric activity suggest that the apparent continual "stream of consciousness" consists of concatenated identifiable brief packets in the time range of fractions of seconds, in a time range postulated for ‘elementary deliberations’ (Newell, 1992), for visual and auditory perceptions (Efron, 1970), and as needed or available for changing or bridging perceptual input organization or attention (Michaels and Turvey, 1979; DiLollo, 1980; Reeves and Sperling, 1986; Posner et al., 1987; Motter, 1994). Entry of content chunks into consciousness (e.g., Baars' Global Workspace, Baars, 2007) apparently requires such minimum durations. In sum, the evidence suggests that brain electric microstates qualify for basic building blocks of mentation, as candidates for conscious or non-conscious 'atoms of thought and emotion' (Lehmann 1990; Lehmann et al., 1998, 2004, 2005; Changeux and Michel, 2004).
Numerous studies on ERP microstates contribute to a microstate dictionary of different brain functions. For example, subjective contour perception and attention were incorporated in specific ERP microstates (Brandeis and Lehmann, 1989). Specific microstates distinguish visual depth from contour perception (Michel et al., 1992) and perception of color in motion as compared to achromatic moving stimuli (Morand et al., 2000). A microstate has been identified that systematically increased in duration with the angle of rotation of a letter that had to be rotated mentally (Pegna et al., 1997). Similar mental rotation microstates were found for body parts (Overnay et al., 2005; Petit et al., 2006; Arzy et al., 2006). In schizotypy, perceptual aberration of body image correlated with increased duration of the microstate 310-390 ms after task onset that asked to report the orientation of the displayed body image (Arzy et al., 2007). Reading abstract and visual imaginable (concrete) words evoked two different microstate classes around 300 ms after word onset (Koenig et al., 1998; Sysoeva et al., 2007) and during a 40–100 ms microstate (Sysoeva et al., 2007). Priming differently affected ERP microstates to abstract and concrete words (Wirth et al., 2008). An early distinct microstate also was identified for emotional words (Ortigue et al., 2004). When reading emotional words, their emotional valence is represented in an earlier microstate than their arousing strength (Gianotti et al., 2008). Correct rejection of irrelevant visual information is reflected in a specific microstate very early after stimulus presentation (Schnider et al., 2002). Unique microstates have been described for auditory and somatosensory what and where perception (Ducommun et al., 2002; Spierer et al., 2007) as well as for multisensory information processing (Murray et al., 2004). Also reported were pharmacological effects on specific ERP microstates (e.g., Michel et al., 1993).
Microstate-dependent information processing
The general rule that information processing by the brain depends on the brain's momentary functional state also holds at the microstate level: The microstate just before stimulus onset determines how the stimulus is going to be processed. When evoked potentials are separately averaged for different pre-stimulus microstate classes, they drastically differ, despite physically identical stimuli (Kondakor et al., 1997; Lehmann et al., 1994). Different pre-stimulus microstates also change the perception of physically identical stimuli: Specific microstates precede the change of illusory motion perception (Müller et al., 2005) as well as the switch in perception of a Necker-cube (Britz et al., 2008). Perception of emoitional words presented to the left visual field (right hemisphere) is facilitated when a specific microstate is present just before word presentation (Mohr et al., 2005). Together these studies demonstrate the state-dependency of brain information processing in the subsecond time range.
- Arzy S, Mohr C, Michel CM & Blanke O (2007) Duration and not strength of activation in temporo-parietal cortex positively correlates with schizotypy. Neuroimage 35:326-333, 2007.
- Arzy S, Thut G, Mohr C, Michel CM & Blanke O (2006) Neural basis of embodiment: distinct contributions of temporoparietal junction and extrastriate body area. J Neurosci 26:8074-8081.
- Ashby WR (1960) Design for a brain; the origin of adaptive behavior, 2nd ed. New York: Wiley.
- Baars BJ & Franklin S (2007) An architectural model of conscious and unconscious brain functions: Global Workspace Theory and IDA. Neural Networks 20:955-961.
- Brandeis D & Lehmann D (1986) Event related potentials of the brain and cognitive processes: Approaches and applications. Neuropsychologia 24:151-168.
- Brandeis D & Lehmann D (1989) Segments of ERP map series reveal landscape changes with visual attention and subjective contours. Electroenceph Clin Neurophysiol 73:507-519.
- Brandeis D, Naylor H, Halliday R, Callaway E, Yano L (1992) Scopolamine effects on visual information processing, attention, and event-related potential map latencies. Psychophysiology 29:315–336.
- Britz J, Landis T & Michel CM (2008) Right parietal brain activity precedes perceptual alternation of bi-stable stimuli. Cereb Cortex (in press).
- Cantero JL, Atienza M & Salas RM (2002) Human alpha oscillations in wakefulness, drowsiness period, and REM sleep: different electroencephalographic phenomena within the alpha band. Neurophysiol Clin 32:54-71.
- Cantero JL, Atienza M, Salas RM & Gomez, CM (1999) Brain spatial microstates of human spontaneous alpha activity in relaxed wakefulness. Brain Topography 11:257-263.
- Changeux J-P & Michel CM (2004) Mechanism of neural Integration at the Brain-scale Level. In: Grillner S, Graybiel AM (eds): Microcircuits. Cambridge: MIT Press. p. 347-370.
- DiLollo, V., 1980. Temporal integration in visual memory. J. Exp. Psychol. Genet. 109, 75-97.
- Ducommun CY, Murray MM, Thut G, Bellmann A, Viaud-Delmon I, Clarke S & Michel CM (2002) Segregated processing of auditory motion and auditory location: an ERP mapping study. Neuroimage 16:76-88.
- Efron R (1970) The minimum duration of a perception. Neuropsychologia 8:57-63.
- Faber PL, Lehmann D, Barendregt H, Kaelin M, & Gianotti LRR (2005) Increased duration of EEG microstates during meditation. Brain Topography 18:131.
- Geselowitz DB (1998) The zero of potential. IEEE Eng Med Biol Mag 17:128-132.
- Gianotti LRR, Faber PL, Pascual-Marqui RD, Kochi K & Lehmann D (2007) Processing of positive versus negative emotional words is incorporated in anterior versus posterior brain areas: an ERP microstate LORETA study. Chaos and Complexity Letters 2[2/3]:189-211.
- Gianotti LRR, Faber PL, Schuler M, Pascual-Marqui RD, Kochi K & Lehmann D (2008) First valence, then arousal: The temporal dynamics of brain electric activity evoked by emotional stimuli. Brain Topography 20:143-156.
- Irisawa S, Isotani T, Yagyu T, Morita S, Nishida K, Yamada K, Yoshimura M, Okugawa G, Nobuhara K & Kinoshita T (2006) Increased omega complexity and decreased microstate duration in nonmedicated schizophrenic patients. Neuropsychobiol 54:134-139.
- James W (1890) The Principles of Psychology. New York, H. Holt and Company.
- Karniski W, Blair RC & Snider AD (1994) An exact statistical method for comparing topographic maps, with any number of subjects and electrodes. Brain Topogr 6:203-210.
- Katayama H, Gianotti LRR, Isotani T, Faber PL, Sasada K, Kinoshita T & Lehmann D (2007) Classes of multichannel EEG microstates in light and deep hypnotic conditions. Brain Topogr 20:7-14.
- Koenig T & Lehmann D (1996) Microstates in language-related brain potential maps show noun-verb differences. Brain Lang 53:169-182.
- Koenig T, Kochi K & Lehmann D (1998) Event-related electric microstates of the brain differ between words with visual and abstract meaning. Electroenceph Clin Neurophysiol 106:535-546.
- Koenig T, Lehmann D, Merlo MCG, Kochi K, Hell D & Koukkou M (1999) A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest. Europ Arch Psychiat Clin Neurosci 249:205-211.
- Koenig T, Prichep LS, Lehmann D, Valdes-Sosa P, Braeker E, Kleinlogel H, Isenhart R & John ER (2002) Millisecond by millisecond, year by year: normative EEG microstates and developmental stages. NeuroImage 16:41-48.
- Kondakor I, Lehmann D, Michel CM, Brandeis D, Kochi K & Koenig T (1997) Prestimulus EEG microstates influence visual event-related potential microstates in field maps with 47 channels. J Neural Transm Gen Sect 104[2 3]:161-173.
- Kondakor I, Pascual-Marqui RD, Michel CM, Lehmann D (1995) Event-related potential map differences depend on the prestimulus microstates. J Med Eng Technol 19:66-69.
- Lehmann D & Skrandies W (1980) Reference-free identification of components of checkerboard-evoked multichannel potential fields. Electroenceph Clin Neurophysiol 48:609-621.
- Lehmann D & Skrandies W (1984) Spatial analysis of evoked potentials in man - a review. Progr Neurobiol 23:227-250.
- Lehmann D (1971) Multichannel topography of human alpha EEG fields. Electroenceph Clin Neurophysiol 31:439-449.
- Lehmann D (1972) Human scalp EEG fields: Evoked, alpha, sleep and spike-wave patterns. In: H.H. Petsche & M.A.B. Brazier (eds): Synchronization of EEG Activity in Epilepsies. Springer, Wien. pp. 307-325.
- Lehmann D (1990) Brain electric microstates and cognition: the atoms of thought. In: E.R. John (ed): Machinery of the Mind. Birkhäuser, Boston. pp. 209-224.
- Lehmann D (1987) Principles of spatial analysis. In: A. Gevins and A. Remond (eds): Handbook of Electroencephalography and Clinical Neurophysiology, Vol. 1: Methods of Analysis of Brain Electrical and Magnetic Signals. Elsevier, Amsterdam. [ISBN 0-444-80804-3]. pp. 309-354.
- Lehmann D, Michel CM, Pal I & Pascual-Marqui RD (1994) Event-related potential maps depend on prestimulus brain electric microstate map. Int J Neurosci 74:239-248.
- Lehmann D, Faber PL, Galderisi S, Herrmann WM, Kinoshita T, Koukkou M, Mucci A, Pascual-Marqui RD, Saito N, Wackermann J, Winterer G & Koenig T (2005) EEG microstate duration and syntax in acute, medication-naïve, first-episode schizophrenia: a multi-center study. Psychiatry Res Neuroimaging 138:141-156.
- Lehmann D, Koenig T, Henggeler B, Strik W, Kochi K, Koukkou M & Pascual-Marqui RD (2004) Brain areas activated during electric microstates of mental imagery versus abstract thinking. (abstract) Klinische Neurophysiologie 35: 169. click to see poster
- Lehmann D, Ozaki H & Pal I (1987) EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. Electroenceph Clin Neurophysiol 67:271-288.
- Lehmann D, Strik WK, Henggeler B, Koenig T & Koukkou, M (1998) Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts. Int J Psychophysiol 29:1-11.
- Lehmann D, Wackermann J, Michel CM & Koenig T (1993) Space-oriented EEG segmentation reveals changes in brain electric field maps under the influence of a nootropic drug. Psychiatry Res Neuroimaging 50:275-282.
- Michaels, C.F., Turvey, M.T., 1979. Central sources of visual masking: indexing structures supporting seeing at a single, brief glance. Psychol. Res. 41, 1-61.
- Michel CM & Lehmann D (1993) Single doses of piracetam affect 42-channel event-related potential microstate maps in a cognitive paradigm. Neuropsychobiology 28:212-221.
- Michel CM, Henggeler B & Lehmann D (1992) 42-channel potential map series to visual contrast and stereo stimuli: perceptual and cognitive event-related segments. Int J Psychophysiol 12:133-145.
- Michel CM, Seeck M & Landis T (1999) Spatiotemporal dynamics of human cognition. News Physiol Sci 14:206-214.
- Michel CM, Seeck M & Murray MM (2004) The speed of visual cognition. Suppl Clin Neurophysiol 57:617-627.
- Michel CM, Thut G, Morand S, Khateb A, Pegna AJ, Grave de Peralta R, Gonzalez S, Seeck M & Landis T (2001) Electric source imaging of human brain functions. Brain Res Brain Res Rev 36:108-118.
- Mohr C, Michel CM, Lantz G, Ortigue S, Viaud-Delmon I & Landis T (2005) Brain state-dependent functional hemispheric specialization in men but not in women. Cereb Cortex 15:1451-1458.
- Morand S, Thut G, Grave de Peralta R, Clarke S, Khateb A, Landis T & Michel CM (2000) Electrophysiological evidence for fast visual processing through the human koniocellular pathway when stimuli move. Cereb Cortex 10:817-825.
- Motter, B.C., 1994. Neural correlates of feature selective memory and pop-out in extrastriate area V4. J. Neurosci. 14, 2190-2199.
- Müller TJ, Koenig T, Wackermann J, Kalus P, Fallgatter A, Strik W & Lehmann D (2005) Subsecond changes of global brain state in illusionary multistable motion perception. J Neural Transm 112:565-576.
- Murray MM, Brunet D & Michel CM (2008) Topographic ERP analyses: a step-by-step tutorial review. Brain Topogr 20:249-264.
- Murray MM, Michel CM, Grave de Peralta R, Ortigue S, Brunet D, Gonzalez Andino S & Schnider A (2004) Rapid discrimination of visual and multisensory memories revealed by electrical neuroimaging. Neuroimage 21:125-135.
- Newell, A (1992) Precis of unified theories of cognition. Behav Brain Sci 15:425-492.
- Ortigue S, Michel CM, Murray MM, Mohr C, Carbonnel S & Landis T (2004) Electrical neuroimaging reveals early generator modulation to emotional words. Neuroimage 21:1242-1251.
- Overney LS, Michel CM, Harris IM & Pegna AJ (2005) Cerebral processes in mental transformations of body parts: recognition prior to rotation. Brain Res Cogn Brain Res 25:722-734.
- Pascual-Marqui RD, Michel CM & Lehmann D (1994) Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 18:49-65.
- Pascual-Marqui RD, Michel CM & Lehmann D (1995) Segmentation of brain electrical activity into microstates: model estimation and validation. IEEE Trans Bio-Med Eng 42:658-665.
- Pegna AJ, Khateb A, Spinelli L, Seeck M, Landis T & Michel CM (1997) Unravelling the cerebral dynamics of mental imagery. Hum Brain Mapp 5:410-421.
- Petit LS, Pegna AJ, Harris IM & Michel CM (2006) Automatic motor cortex activation for natural as compared to awkward grips of a manipulable object. Exp Brain Res 168[1-2]:120-130.
- Posner, M.I., Walker, J.A., Friedrich, F.A., Rafael, R.D., 1987. How do the parietal lobes direct covert attention? Neuropsychologia 25, 135-145.
- Reeves, A., Sperling, G., 1986. Attention gating in short-term visual memory. Psychol. Rev. 93, 180-206.
- Schnider A, Valenza N, Morand S & Michel CM (2002) Early cortical distinction between memories that pertain to ongoing reality and memories that don't. Cereb Cortex 12:54-61.
- Skrandies W (1998) Evoked potential correlates of semantic meaning--A brain mapping study. Brain Res Cogn Brain Res 6:173-183.
- Spierer L, Tardif E, Sperdin H, Murray MM, Clarke S (2007) Learning-induced plasticity in auditory spatial representations revealed by electrical neuroimaging. J Neurosci 27:5474-5483.
- Strelets V, Faber PL, Golikova J, Novototsky-Vlasov V, Koenig T, Gianotti LRR, Gruzelier JH & Lehmann D (2003) Chronic schizophrenics with positive symptomatology have shortened EEG microstate durations. Clinical Neurophysiology 14:2043-2051.
- Strik WK & Lehmann D (1993) Data determined window size and space-oriented segmentation of spontaneous EEG map series. Electroencephalogr Clin Neurophysiol 87:169-174.
- Strik WK, Dierks T, Becker T, Lehmann D (1995) Larger topographical variance and decreased duration of brain electric microstates in depression. J Neural Transm Gen Sect 99:213-222.
- Strik WK, Fallgatter AJ, Brandeis D, Pascual-Marqui RD (1998) Three-dimensional tomography of event-related potentials during response inhibition: evidence for phasic frontal lobe activation. Electroencephalogr Clin Neurophysiol 108:406-413.
- Sysoeva OV, Ilyuchenok IR & Ivanitsky AM (2007) Rapid and slow brain systems of abstract and concrete words differentiation. Int J Psychophysiol 65:272-283.
- Wackermann J, Lehmann D, Michel CM & Strik WK (1993) Adaptive segmentation of spontaneous EEG map series into spatially defined microstates. Int J Psychophysiol 14:269-283.
- Wirth M, Horn H, Koenig T, Razafimandimby A, Stein M, Mueller T, Federspiel A, Meier B, Dierks T & Strik W (2008) The early context effect reflects activity in semantic system: Evidence from electrical neuroimaging of abstract and concrete word reading. Neuroimage, 42:423-436.
- Yoshimura M, Koenig T, Irisawa S, Isotani T, Yamada K, Kikuchi M, Okugawa G, Yagyu T, Kinoshita T, Strik W & Dierks T (2007) A pharmaco-EEG study on antipsychotic drugs in healthy volunteers. Psychopharmacology (Berl) 191:995-1004.
- Valentino Braitenberg (2007) Brain. Scholarpedia, 2(11):2918.
- Paul L. Nunez and Ramesh Srinivasan (2007) Electroencephalogram. Scholarpedia, 2(2):1348.
- Rodolfo Llinas (2008) Neuron. Scholarpedia, 3(8):1490.
- Philip Holmes and Eric T. Shea-Brown (2006) Stability. Scholarpedia, 1(10):1838.