|Dietrich Lehmann et al. (2009), Scholarpedia, 4(3):7632.||doi:10.4249/scholarpedia.7632||revision #88985 [link to/cite this article]|
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).
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.
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