Microstate EEGlab toolbox: An introductory guide

At, Poulsen; Pedroni, Andreas; Langer, Nicolas; Hansen, LK

doi:10.1101/289850

Cited by 130 publications

(222 citation statements)

References 30 publications

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“…The aim of a microstate-segment analysis is to provide information about the brain activity associated with the sequence of discrete (and non-periodic) information-processing operations evoked by a stimulus or task [38]. Microstate segment analyses were carried out using Microstate Analysis Toolbox (MST) [39] from the EEGLAB toolbox [40]. All ERP data from the 6 conditions (male or female × 6 stimuli) were added together and grand-averaged.…”

Section: Discussionmentioning

confidence: 99%

Gender differences in subliminal affective face priming: A high-density ERP study

Tanaka¹,

Yamada²,

Maekawa³

et al. 2019

Preprint

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Background Subliminal affective priming effects (SAPEs) refer to the phenomenon by which the presentation of an affective prime stimulus influences the subsequent affective evaluation of a target stimulus. Previous studies have shown that behavioural performance is affected more by unconsciously processed stimuli than by consciously processed stimuli. However, the impact of SAPEs on the face-specific N170 component is unclear. In the current study, we investigated how subliminal processing of fearful faces affected the N170 for subsequent supraliminal target faces using event-related potentials (ERPs).Methods We used event-related potentials (ERPs) to study how SAEPs for fearful faces affect the N170 for subsequent supraliminal target faces. Japanese adults (n=51, 24 females) participated in this study. Subliminal prime faces (neutral or fearful) were presented for 17 ms, followed by a backward mask for 283 ms and target faces for 800 ms (neutral, emotionally ambiguous-fearful, or fearful). ERPs (128-ch) were recorded while participants judged the expression of target faces as neutral or fearful.Results Behavioral data revealed that participants judged target faces as more fearful in the fearful face prime condition compared with the neutral prime condition, regardless of emotional expression. Interestingly, we found gender-related differences in N170 amplitude; only female participants exhibited enhanced N170 amplitude for neutral faces primed by fearful faces. Therefore, a noticeable gender difference exists in the neural processing of subliminally perceived facial emotions.Conclusions Our ERP results suggest the existence of a gender difference in target-face processing preceded by subliminally presented face stimuli in the right occipito-temporal regions.

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Section: Discussionmentioning

confidence: 99%

Gender differences in subliminal affective face priming: A high-density ERP study

Tanaka¹,

Yamada²,

Maekawa³

et al. 2019

Preprint

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“…The microstate analysis was performed using the Microstate EEGLAB Toolbox (Poulsen et al, 2018) . Before running the microstate analysis, data from all sessions were concatenated to create one continuous epoch of around 20 minutes.…”

Section: Microstate Analysismentioning

confidence: 99%

“…This analysis was polarity invariant, which means that LFP data at two time points with similar spatial pattern but opposite polarity were labeled as the same microstate. Minimum duration of microstates was set to be 25 ms (Poulsen et al, 2018) .…”

Section: Microstate Analysismentioning

confidence: 99%

Dynamics of neural microstates in the VTA-striatal-prefrontal loop during novelty exploration in the rat

Mishra

Marzban

Cohen

et al. 2020

Preprint

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EEG microstates refer to quasi-stable spatial patterns of scalp potentials, and their dynamics have been linked to cognitive and behavioral states. Neural activity at single and multiunit levels also exhibit spatiotemporal coordination, but this spatial scale is difficult to relate to EEG. Here, we translated EEG microstate analysis to triple-area local field potential (LFP) recordings from up to 192 electrodes in rats to investigate the mesoscopic dynamics of neural microstates within and across brain regions.We performed simultaneous recordings from the prefrontal cortex (PFC), striatum (STR), and ventral tegmental area (VTA) during awake behavior (object novelty and exploration). We found that the LFP data can be accounted for by multiple, recurring, quasi-stable spatial activity patterns with an average period of stability of ~60-100 ms. The top four maps accounted for 60-80% of the total variance, compared to ~25% for shuffled data. Cross-correlation of the microstate time-series across brain regions revealed rhythmic patterns of microstate activations, which we interpret as a novel indicator of inter-regional, mesoscale synchronization. Furthermore, microstate features, and patterns of temporal correlations across microstates, were modulated by behavioural states such as movement and novel object exploration. These results support the existence of a functional mesoscopic organization across multiple brain areas, and open up the opportunity to investigate their relation to EEG microstates, of particular interest to the human research community.Significance StatementThe coordination of neural activity across the entire brain has remained elusive. Here we combine large-scale neural recordings at fine spatial resolution with the analysis of microstates, i.e. short-lived, recurring spatial patterns of neural activity. We demonstrate that the local activity in different brain areas can be accounted for by only a few microstates per region. These microstates exhibited temporal dynamics that were correlated across regions in rhythmic patterns. We demonstrate that these microstates are linked to behavior and exhibit different properties in the frequency domain during different behavioural states. In summary, LFP microstates provide an insightful approach to studying both mesoscopic and large-scale brain activation within and across regions.

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“…Selection of the number of microstates is based on a combination of maximizing the Global Explained Variance (GEV) (a measure of how well the given microstate topographies explain the variance across the data), and minimizing both the Cross Validation Criterion (CV; a measure of unexplained noise) and the total number of microstate prototypes. We used the modified K-means clustering algorithm to determine the number of microstates, using n = 2:8 [Poulsen et al, 2018]. I II back-fit the five topographies onto the quiet rest data.…”

Section: Microstate Analysismentioning

confidence: 99%

Using EEG Microstates to Examine Post-Encoding Quiet Rest and Subsequent Word-Pair Memory

Poskanzer

Denis

Herrick³

et al. 2020

Preprint

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Evidence suggests that the brain preferentially consolidates memories during "offline" periods, in which an individual is not performing a task and their attention is otherwise undirected, including spans of quiet, resting wakefulness. Moreover, research has demonstrated that factors such as the initial encoding strength of information influence which memories receive the greatest benefit. Recent studies have begun to investigate these periods of post-learning quiet rest using EEG microstate analysis to observe the electrical dynamics of the brain during these stretches of memory consolidation, specifically finding an increase in the amount of the canonical microstate D during a post-encoding rest period.Here, we implement an exploratory analysis to probe the activity of EEG microstates during post-encoding sessions of quiet rest in order to scrutinize the impact of learning on microstate dynamics and to further understand the role these microstates play in the consolidation of memories. In two different studies, we examined a combined 74 subjects (55 female) as they completed a word-pair memory task designed to use repetition and presentation-time to vary the initial encoding strength of the word-pair memories. In both studies, we were able to replicate previous research in which there was a significant increase (both p's < .05) in the amount of microstate D (often associated with the dorsal attention network) during post-encoding rest. This change was accompanied, in both studies, by a significant decrease (both p's < .05) in the amount of microstate C (often associated with the default mode network). We also found preliminary evidence indicating a positive relationship between the amount of microstate D and improved memory for weakly encoded memories, which merits further exploration.3

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Microstate EEGlab toolbox: An introductory guide

Cited by 130 publications

References 30 publications

Gender differences in subliminal affective face priming: A high-density ERP study

Gender differences in subliminal affective face priming: A high-density ERP study

Dynamics of neural microstates in the VTA-striatal-prefrontal loop during novelty exploration in the rat

Using EEG Microstates to Examine Post-Encoding Quiet Rest and Subsequent Word-Pair Memory

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