Functional Microstates Research Articles

The temporal dynamics of Large-Scale brain network changes in disorders of consciousness: A Microstate-Based study.

The resting-state brain is composed of several discrete networks, which remain stable for 10-100 ms. These functional microstates are considered the building blocks of spontaneous consciousness. Electroencephalography (EEG) microstate analysis may provide insight into the altered brain dynamics underlying consciousness recovery in patients with disorders of consciousness (DOC). We aimed to analyze microstates in the resting-state EEG source space in patients with DOC, the relationship between state-specific features and consciousness levels, and the corresponding patterns of microstates and functional networks. We obtained resting-state EEG data from 84 patients with DOC (27 in a minimally conscious state [MCS] and 57 in a vegetative state [VS] or with unresponsive wakefulness syndrome). We conducted a microstate analysis of the resting-state (EEG) source space and developed a state-transition analysis protocol for patients with DOC. We identified seven microstates with distinct spatial distributions of cortical activation. Multivariate pattern analyses revealed that different functional connectivity patterns were associated with source-level microstates. There were significant differences in the microstate properties, including spatial activation patterns, temporal dynamics, state shifts, and connectivity construction, between the MCS and VS groups. Our findings suggest that consciousness depends on complex dynamics within the brain and may originate from the anterior cortex.

EEG microstates in resting condition in young indians

Objectives: The map topography analysis gives an idea of temporal dynamics of electric fields, which is reference independent, making the results unambiguous. These topographic maps remain stable for 80 to 100 milliseconds, abruptly shifting to a new topographic map configuration and remains stable in that state are called the ‘functional microstates’ as described by Lehmann et al (1987). There has been no study done in the resting state eye closed and eye open conditions showing the microstate maps in healthy Indian subjects in resting eyes open and resting eyes closed condition using 128 channel EEG. So our study aim was to assess the microstates in resting eyes closed and eyes open condition. And to compare the microstate parameters such as mean duration, global explained variance (GEV) and time coverage between eyes closed and eyes open condition. Materials and Methods: A cross-sectional and observational study on 20 indian subjects (Mean age- 26.65 and (SD) - 2.78 years) was done on resting eyes closed and eyes open conditions. After EEG acquisition using 128 channel EEG machine, EEG was preprocessed and microstate analysis using CARTOOL software was performed on the EEG data. Results: After microstate analysis four maps topography were obtained. There was statistically non-significant difference observed in microstate maps between resting eyes closed and resting eyes open condition for the all parameters i.e. mean duration, time coverage and GEV. Conclusion: Our findings suggests that, both eyes closed and eyes open conditions were similar to each other in terms of stability and predominance of Maps.

+microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG

+microstate is a MATLAB toolbox for brain functional microstate analysis. It builds upon previous EEG microstate literature and toolboxes by including algorithms for source-space microstate analysis. +microstate includes codes for performing individual- and group-level brain microstate analysis in resting-state and task-based data including event-related potentials/fields. Functions are included to visualise and perform statistical analysis of microstate sequences, including novel advanced statistical approaches such as statistical testing for associated functional connectivity patterns, cluster-permutation topographic ANOVAs, and χ2 analysis of microstate probabilities in response to stimuli. Additionally, codes for simulating microstate sequences and their associated M/EEG data are included in the toolbox, which can be used to generate artificial data with ground truth microstates and to validate the methodology. +microstate integrates with widely used toolboxes for M/EEG processing including Fieldtrip, SPM, LORETA/sLORETA, EEGLAB, and Brainstorm to aid with accessibility, and includes wrappers for pre-existing toolboxes for brain-state estimation such as Hidden Markov modelling (HMM-MAR) and independent component analysis (FastICA) to aid with direct comparison with these techniques. In this paper, we first introduce +microstate before subsequently performing example analyses using open access datasets to demonstrate and validate the methodology. MATLAB live scripts for each of these analyses are included in +microstate, to act as a tutorial and to aid with reproduction of the results presented in this manuscript.

EEG microstate complexity for aiding early diagnosis of Alzheimer\u2019s disease

The dynamics of the resting brain exhibit transitions between a small number of discrete networks, each remaining stable for tens to hundreds of milliseconds. These functional microstates are thought to be the building blocks of spontaneous consciousness. The electroencephalogram (EEG) is a useful tool for imaging microstates, and EEG microstate analysis can potentially give insight into altered brain dynamics underpinning cognitive impairment in disorders such as Alzheimer’s disease (AD). Since EEG is non-invasive and relatively inexpensive, EEG microstates have the potential to be useful clinical tools for aiding early diagnosis of AD. In this study, EEG was collected from two independent cohorts of probable AD and cognitively healthy control participants, and a cohort of mild cognitive impairment (MCI) patients with four-year clinical follow-up. The microstate associated with the frontoparietal working-memory/attention network was altered in AD due to parietal inactivation. Using a novel measure of complexity, we found microstate transitioning was slower and less complex in AD. When combined with a spectral EEG measure, microstate complexity could classify AD with sensitivity and specificity > 80%, which was tested on an independent cohort, and could predict progression from MCI to AD in a small preliminary test cohort of 11 participants. EEG microstates therefore have potential to be a non-invasive functional biomarker of AD.

Shape facilitates number: brain potentials and microstates reveal the interplay between shape and numerosity in human vision

Recognition of simple shapes and numerosity estimation for small quantities are often studied independently of each other, but we know that these processes are both rapid and accurate, suggesting that they may be mediated by common neural mechanisms. Here we address this issue by examining how spatial configuration, shape complexity, and luminance polarity of elements affect numerosity estimation. We directly compared the Event Related Potential (ERP) time-course for numerosity estimation under shape and random configurations and found a larger N2 component for shape over lateral-occipital electrodes (250–400 ms), which also increased with higher numbers. We identified a Left Mid Frontal (LMF; 400–650 ms) component over left-lateralised medial frontal sites that specifically separated low and high numbers of elements, irrespective of their spatial configuration. Different luminance-polarities increased N2 amplitude only, suggesting that shape but not numerosity is selective to polarity. Functional microstates confined numerosity to a strict topographic distribution occurring within the LMF time-window, while a microstate responding only to shape-configuration was evidenced earlier, in the N2 time-window. We conclude that shape-coding precedes numerosity estimation, which can be improved when the number of elements and shape vertices are matched. Thus, numerosity estimation around the subitizing range is facilitated by a shape-template matching process.

EEG time signature in Alzheimer´s disease: Functional brain networks falling apart.

Spontaneous mental activity is characterized by dynamic alterations of discrete and stabile brain states called functional microstates that are thought to represent distinct steps of human information processing. Electroencephalography (EEG) directly reflects functioning of brain synapses with a uniquely high temporal resolution, necessary for investigation of brain network dynamics. Since synaptic dysfunction is an early event and best correlate of cognitive status and decline in patients along Alzheimer's disease (AD) continuum, EEG microstates might serve as valuable early markers of AD. The present study investigated differences in EEG microstate topographies and parameters (duration, occurrence and contribution) between a large cohort of healthy elderly (n=308) and memory clinic patients: subjective cognitive decline (SCD, n=210); mild cognitive impairment (MCI, n=230) and AD (n=197) and how they correlate to conventional cerebrospinal fluid (CSF) markers of AD. Four most representative microstate maps assigned as classes A, B (asymmetrical), C and D (symmetrical) were computed from the resting state EEGs since it has been shown previously that this is sufficient to explain most of the resting state EEG data. Statistically different topography of microstate maps were found between the controls and the patient groups for microstate classes A, C and D. Changes in the topography of microstate class C were associated with the CSF Aβ42 levels, whereas changes in the topography of class B were linked with the CSF p-tau levels. Gradient-like increase in the contribution of asymmetrical (A and B) and gradient-like decrease in the contribution of symmetrical (C and D) maps were observed with the more severe stage of cognitive impairment. Our study demonstrated extensive relationship of resting state EEG microstates topographies and parameters with the stage of cognitive impairment and AD biomarkers. Resting state EEG microstates might therefore serve as functional markers of early disruption of neurocognitive networks in patients along AD continuum.

Examining the steps towards Recognition: Functional Microstates in the Misleading Information Paradigm

Examining the steps towards Recognition: Functional Microstates in the Misleading Information Paradigm

Hyperactivation of left inferior parietal lobule and left temporal gyri shortens resting EEG microstate in schizophrenia

ObjectiveThe momentary spatial configuration of the brain electric field at the scalp reflects quasi-stable “functional microstates” caused by activity of different intracranial generators. There is paucity in literature on the intracranial generators of resting state EEG microstate alterations in stable patients with schizophrenia. The present study aimed to investigate resting state microstate alterations and their neural generators in patients with schizophrenia and their first-degree relatives as compared to healthy controls in an attempt to establish state and trait marker. MethodThirty-four patients with schizophrenia (DSM-5 criteria), 29 first-degree relatives and 25 matched healthy controls participated in the study. Brain activity during eyes closed condition was recorded using 128 channel electroencephalography. Microstates were clustered into 5 maps across groups according to their topography. Microstate map parameters and their cortical sources were compared among groups. ResultsMap 5 mean duration (χ2(2) = 7.617, p = 0.022) was significantly lower in patients compared to controls (U = 256, p = 0.010). Maximum activation was seen in left inferior parietal lobule (MNI coordinates: −65, −35, 25, Log-Fmax = 0.748). Suprathreshold cortical voxels with increased activations were found localized at left temporal gyri. ConclusionHyperactivation in left inferior parietal lobule and temporal gyri might have shortened Map 5 duration at rest in patients with schizophrenia. This could imply microstate alterations as the potential state marker of schizophrenia.

Dissociating Attention Effects from Categorical Perception with ERP Functional Microstates.

When faces appear in our visual environment we naturally attend to them, possibly to the detriment of other visual information. Evidence from behavioural studies suggests that faces capture attention because they are more salient than other types of visual stimuli, reflecting a category-dependent modulation of attention. By contrast, neuroimaging data has led to a domain-specific account of face perception that rules out the direct contribution of attention, suggesting a dedicated neural network for face perception. Here we sought to dissociate effects of attention from categorical perception using Event Related Potentials. Participants viewed physically matched face and butterfly images, with each category acting as a target stimulus during different blocks in an oddball paradigm. Using a data-driven approach based on functional microstates, we show that the locus of endogenous attention effects with ERPs occurs in the N1 time range. Earlier categorical effects were also found around the level of the P1, reflecting either an exogenous increase in attention towards face stimuli, or a putative face-selective measure. Both category and attention effects were dissociable from one another hinting at the role that faces may play in early capturing of attention before top-down control of attention is observed. Our data support the conclusion that certain object categories, in this experiment, faces, may capture attention before top-down voluntary control of attention is initiated.

The primary somatosensory cortex contributes to the latest part of the cortical response elicited by nociceptive somatosensory stimuli in humans

Nociceptive laser pulses elicit temporally-distinct cortical responses (the N1, N2 and P2 waves of laser-evoked potentials, LEPs) mainly reflecting the activity of the primary somatosensory cortex (S1) contralateral to the stimulated side, and of the bilateral operculoinsular and cingulate cortices. Here, by performing two different EEG experiments and applying a range of analysis approaches (microstate analysis, scalp topography, single-trial estimation), we describe a distinct component in the last part of the human LEP response (P4 wave). We obtained three main results. First, the LEP is reliably decomposed in four main and distinct functional microstates, corresponding to the N1, N2, P2, and P4 waves, regardless of stimulus territory. Second, the scalp and source configurations of the P4 wave follow a clear somatotopical organization, indicating that this response is likely to be partly generated in contralateral S1. Third, single-trial latencies and amplitudes of the P4 are tightly coupled with those of the N1, and are similarly sensitive to experimental manipulations (e.g., to crossing the hands over the body midline), suggesting that the P4 and N1 may have common neural sources. These results indicate that the P4 wave is a clear and distinct LEP component, which should be considered in LEP studies to achieve a comprehensive understanding of the brain response to nociceptive stimulation.

An automated method for micro-state segmentation of evoked potentials

We present a method for segmenting evoked potentials into functional micro-states. The method is based on measuring the similarity between all the topographic maps in the evoked potential and grouping them into functional micro-states based on minimizing an error function. The similarity is measured as the normalized cross-correlation coefficient. The method was validated on simulated data and tested on its ability to segment a visual evoked potential. On simulated data the method missed from 1% to 8.5% of the micro-state boundaries for evoked potentials with a signal-to-noise ratio of 20–1 dB, respectively. The proposed segmentation method was compared with segmentation based on K-mean clustering. It was found that the proposed method was better at detecting the correct number of micro-states and was computationally more efficient. The automatic segmentation of the visual evoked potential was compared to the manual segmentation performed by eleven EEG specialists. No significant difference in the deviation of micro-state boundaries was observed between two random EEG specialists and between a random EEG specialist and the automatic method. Thus it was found that the method could reliably segment evoked potentials into their functional micro-states.

Rapid and slow brain systems of abstract and concrete words differentiation

Previous studies have repeatedly found that late (300–800 ms) components of event-related potentials (ERP) reflected semantic analysis, i.e. the differentiation between abstract and concrete words. However, the human brain may detect the meaning of the words much earlier. This study investigated the brain mechanisms of the processing of abstract and concrete written words in four experimental conditions: i) Simple Reading, during which volunteers were required to silently read words; ii) Simple Classification, during which volunteers were required to classify the presented word into the abstract and concrete categories; and iii) Cued and iv) Uncued Selective Classification conditions, during which subjects had to classify only the words typed in a particular colour. 19-channel EEG was recorded during the experiment from 13 subjects. The ERP to abstract and concrete words differed not only at the late but also at early (40–100 ms) latencies in the Simple Reading and Classification conditions, as well as for the words that should not be explicitly classified in the Cued Selective Classification condition. This means that semantic analysis can occur in a manner which is both very rapid and implicit. Moreover, increasing task demands can even suppress this rapid semantic analysis. The functional microstate analysis revealed a topographical difference in response to abstract and concrete words, which indicated that at least partly distinct brain networks are involved in the processing of words during both early (implicit differentiation) and late (explicit classification) latencies.

Functional microstates within human REM sleep: first evidence from fMRI of a thalamocortical network specific for phasic REM periods

High thalamocortical neuronal activity characterizes both, wakefulness and rapid eye movement (REM) sleep, but apparently this network fulfills other roles than processing external information during REM sleep. To investigate thalamic and cortical reactivity during human REM sleep, we used functional magnetic resonance imaging with simultaneous polysomnographic recordings while applying acoustic stimulation. Our observations indicate two distinct functional substates within general REM sleep. Acoustic stimulation elicited a residual activation of the auditory cortex during tonic REM sleep background without rapid eye movements. By contrast, periods containing bursts of phasic activity such as rapid eye movements appear characterized by a lack of reactivity to sensory stimuli. We report a thalamocortical network including limbic and parahippocampal areas specifically active during phasic REM periods. Thus, REM sleep has to be subdivided into tonic REM sleep with residual alertness, and phasic REM sleep with the brain acting as a functionally isolated and closed intrinsic loop.

Rhyme processing in the brain: An ERP mapping study

The event-related potential (ERP) N450 component has been described in rhyme detection tasks as a negative response elicited by non-rhyming words in comparison to rhyming ones. This response, which peaked around 450 ms over the midline and right hemisphere recording sites, has been subsequently suggested to start already at ∼ 300 ms. Moreover, although, the phonological N450 has first been linked to the semantic N400 component, its cognitive nature and cerebral origin remained debated. In this study, we re-investigated the time course of the electrophysiological responses to rhyming and non-rhyming words and estimated their cerebral generators using source localization methods. Waveform analysis showed that, prior to the N450 response to non-rhyming, a slightly earlier negativity characterized the rhyming condition over left fronto-temporal electrodes and peaked at ∼ 350 ms. The analysis of the ERP map series in terms of functional microstates revealed a specific map segment in the rhyming condition and another one in the non-rhyming condition. Source localization indicated that the rhyming-elicited microstate engaged predominantly left frontal and temporal areas while the non rhyming-specific response recruited temporal and parietal regions bilaterally. Our results suggest that, similar to the N400 component that is also induced by mismatch contexts, the N450 might rely on temporal generators.

Face-elicited ERPs and affective attitude: brain electric microstate and tomography analyses

Objectives: Although behavioral studies have demonstrated that normative affective traits modulate the processing of facial and emotionally charged stimuli, direct electrophysiological evidence for this modulation is still lacking.Methods: Event-related potential (ERP) data associated with personal, traitlike approach- or withdrawal-related attitude (assessed post-recording and 14 months later) were investigated in 18 subjects during task-free (i.e. unrequested, spontaneous) emotional evaluation of faces. Temporal and spatial aspects of 27 channel ERP were analyzed with microstate analysis and low resolution electromagnetic tomography (LORETA), a new method to compute 3 dimensional cortical current density implemented in the Talairach brain atlas.Results: Microstate analysis showed group differences 132-196 and 196-272 ms poststimulus, with right-shifted electric gravity centers for subjects with negative affective attitude. During these (over subjects reliably identifiable) personality-modulated, face-elicited microstates, LORETA revealed activation of bilateral occipito-temporal regions, reportedly associated with facial configuration extraction processes. Negative compared to positive affective attitude showed higher activity right temporal; positive compared to negative attitude showed higher activity left temporo-parieto-occipital.Conclusions: These temporal and spatial aspects suggest that the subject groups differed in brain activity at early, automatic, stimulus-related face processing steps when structural face encoding (configuration extraction) occurs. In sum, the brain functional microstates associated with affect-related personality features modulate brain mechanisms during face processing already at early information processing stages.

Microstates in Language-Related Brain Potential Maps Show Noun–Verb Differences

Brain processing of grammatical word class was studied analyzing event-related potential (ERP) brain fields. Normal subjects observed a randomized sequence of single German nouns and verbs on a computer screen, while 20-channel ERP field map series were recorded separately for both word classes. Spatial microstate analysis was applied, based on the observation that series of ERP maps consist of epochs of quasi-stable map landscapes and based on the rationale that different map landscapes must have been generated by different neural generators and thus suggest different brain functions. Space-oriented segmentation of the mean map series identified nine successive, different functional microstates, i.e., steps of brain information processing characterized by quasi-stable map landscapes. In the microstate from 116 to 172 msec, noun-related maps differed significantly from verb-related maps along the left–right axis. The results indicate that different neural populations represent different grammatical word classes in language processing, in agreement with clinical observations. This word class differentiation as revealed by the spatial–temporal organization of neural activity occurred at a time after word input compatible with speed of reading.

Event-related potential maps depend on prestimulus brain electric microstate map.

The brain functional microstate immediately before each of about 3000 identical tone stimuli was classified using extracted reference-free descriptors (locations of maximal and minimal potential) of the landscape of the brain's momentary electric field, in 8 volunteers. Six prestimulus microstate map classes occurred more than 30 times in each subject, and were clustered into two map class types (totals of 242 and 283 cases, respectively, on the average per subject). Event-related potential (ERP) map series were averaged for each subject and prestimulus map class. Map descriptors were extracted from the ERP maps at times of maximal Global Field Power during the component time windows N100, P200 and P330. Discriminant functions were estimated; for the maps of N100 and P330, the discriminant scores differed significantly between the maps associated with the two prestimulus map class types (paired t-tests, df = 7, p = .014 and p = .005, respectively). The dominant axis of the poststimulus class type II ERP maps deviated clockwise from that of the type I ERP maps in all components. We conclude that subtle changes in the brain's spontaneous momentary functional microstate (as classified by spatial descriptors of a single map) influence event-related information processing by the brain, following common rules over subjects.

42-channel potential map series to visual contrast and stereo stimuli: perceptual and cognitive event-related segments

Event-related potential maps to perceptual (stimulus type) and cognitive (stimulus relevance) manipulations were studied in 12 healthy volunteers using 42-channel mapping. Perceptual manipulation used three types of visual stimuli: rectangles constituted by: (1) contrast; (2) different densities of monocular Dynamic Random Dots (Flat DRD); and (3) different binocular disparities of Dynamic Random Dots (Stereo DRD). Cognitive manipulation within each stimulus type consisted of presenting the rectangles horizontally and vertically, one of the two with a probability of 33%, and requesting the subjects to count and thus attend to the ‘rare’ rectangles. Spatial characteristics of the maps were analyzed; this allowed conclusions about the generating sources. The map series were adaptively segmented using the minima points of the grand mean Global Field Power curve. Segment strength (Global Field Power) and segment landscape (locations of extreme potentials) were assessed. Stimulus type had effects from 78 to 310 ms, stimulus relevance was effective from 210 to 1000 ms. In the 78–174 ms segment, Stereo DRD and Flat DRD stimuli produced similar map landscapes, while contrast stimuli produced different map landscapes. Attended and ignored stimuli produced contrary effects on landscapes at 210–310 ms as compared to those at 310–546 ms, indicative of different neural populations activated by attention processes during these late event-related potential segments. Interaction between perceptual and cognitive manipulation occurred at 210–310 ms when perceiving stereo stimuli and attending to relevant monocular visible stimuli produced similar map landscapes, suggesting a common brain resource during this segment for automatic figure perception and voluntary attention. The observed functional differences of the segments contribute to the identification of global functional microstates of brain electric activity.

Past, present and future of topographic mapping

Traditional EEG and EP analysis is trace-oriented. When mapping became popular, results of waveform analysis were mapped. Increased exposure to brain field maps has begun to orient analysis to the spatial aspects. Different maps must be generated by different neuronal populations; this offers direct key to the analysis of higher brain function. Space-oriented data reduction selects maps with optimal signal/noise ratio using Global Dissimilarity index. Classification and statistics of map landscapes uses extracted descriptors (locations of extrema or centroids) or three-dimensional dipole models. Map classification leads to adaptive segmentation of evoked or spontaneous map series into functional micro-states, the putative building blocks of perception and cognition.

Segments of event-related potential map series reveal landscape changes with visual attention and subjective contours

Changes of the event-related potential (ERP) map landscape with time and condition were used to identify qualitative changes in the ERP generating process which are indicative of a change in the functional microstate. Twelve subjects attended or ignored unilaterally presented visual stimuli with and without subjective contours. ERP map series from 16 electrodes were adaptively segmented to identify periods of stable map landscape, using topographic descriptions (map maxima and minima). Attention as well as the subjective contours changed the map topography and increased the map amplitude. From 170 to 380 msec, they had similar effects on the antero-posterior map topography. Topographic differences between the effects of attention and subjective contours were also present, but affected mainly the left-right topography. The results are in line with the notion of attentional involvement in subjective contour perception and show that global modulation of exogenous brain activity cannot account for topographic changes with attention or with subjective contours. They further establish space-oriented data reduction as a powerful tool to identify components and to distinguish among hypotheses about the underlying generator processes.