Published: Jan. 1, 2025
Language: Английский
Brain Topography, Journal Year: 2023, Volume and Issue: 37(2), P. 218 - 231
Published: July 29, 2023
Over the last decade, EEG resting-state microstate analysis has evolved from a niche existence to widely used and well-accepted methodology. The rapidly increasing body of empirical findings started yield overarching patterns associations biological psychological states traits with specific classes. However, currently, this cross-referencing among apparently similar classes different studies is typically done by "eyeballing" printed template maps individual authors, lacking systematic procedure. To improve reliability validity future findings, we present tool systematically collect actual data as many published possible them in their entirety matrix spatial similarity. also allows importing novel extracting associated ongoing or studies. literature. 40 included sets indicated that: (i) there high degree similarity across studies, (ii) were converging (iii) representative meta-microstates can be extracted We hope that will useful coming more comprehensive, objective, representation findings.
Language: Английский
Citations
35
Brain Topography, Journal Year: 2024, Volume and Issue: 37(2), P. 169 - 180
Published: Feb. 13, 2024
The analysis of EEG microstates for investigating rapid whole-brain network dynamics during rest and tasks has become a standard practice in the research community, leading to substantial increase publications across various affective, cognitive, social clinical neuroscience domains. Recognizing growing significance this analytical method, authors aim provide microstate community with comprehensive discussion on methodological standards, unresolved questions, functional relevance microstates. In August 2022, conference was hosted Bern, Switzerland, which brought together many researchers from 19 countries. During conference, gave scientific presentations engaged roundtable discussions aiming at establishing steps toward standardizing methods. Encouraged by conference's success, special issue launched Brain Topography compile current state-of-the-art research, encompassing advancements, experimental findings, applications. call submissions garnered 48 contributions worldwide, spanning reviews, meta-analyses, tutorials, studies. Following rigorous peer-review process, 33 papers were accepted whose findings we will comprehensively discuss Editorial.
Language: Английский
Citations
9
Journal of Neuroscience Methods, Journal Year: 2025, Volume and Issue: 416, P. 110355 - 110355
Published: Jan. 22, 2025
The neural mechanisms underlying real-time social interaction remain poorly understood. While hyperscanning has emerged as a popular method to better understand inter-brain mechanisms, methods underdeveloped, and primarily focused on synchronization (IBS). We developed novel approach employing two-brain EEG microstates, investigate during symmetric asymmetric interactive tasks. Microstates are quasi-stable configurations of brain activity that have been proposed represent basic building blocks for mental processing. Expanding the microstate methodology dyads interacting participants enables us moments synchronous activity. Conventional microstates fitted individuals were not related different conditions. However, modulated in observer-actor condition, compared all other conditions where had more task demands, same trend was observed follower-leader condition. This indicates differences resting state default-mode network interactions with Hyperscanning studies estimated IBS based functional connectivity measures. localized connections often hard interpret larger scale when multiple across brains found be important. Two-brain offer an alternative evaluate from large-scale global perspective, by quantifying task-driven states between individuals. present using including open-source code, which expands current hyperscanning-EEG measure potentially identify both interaction.
Language: Английский
Citations
1
Brain Topography, Journal Year: 2023, Volume and Issue: 37(4), P. 479 - 495
Published: July 31, 2023
Abstract Social interactions require both the rapid processing of multifaceted socio-affective signals (e.g., eye gaze, facial expressions, gestures) and their integration with evaluations, social knowledge, expectations. Researchers interested in understanding complex cognition behavior face a “black box” problem: What are underlying mental processes rapidly occurring between perception action why there such vast individual differences? In this review, we promote electroencephalography (EEG) microstates as powerful tool for examining states whether someone is need given situation) identifying sources heterogeneity traits general willingness to help others). EEG identified by analyzing scalp field maps (i.e., distribution electrical on scalp) over time. This data-driven, reference-independent approach allows identifying, timing, sequencing, quantifying activation large-scale brain networks relevant our mind. light these benefits, should become an indispensable part methodological toolkit laboratories working affective neuroscience.
Language: Английский
Citations
22
Brain Topography, Journal Year: 2023, Volume and Issue: 37(2), P. 243 - 264
Published: Sept. 13, 2023
Language: Английский
Citations
19
Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 173, P. 108366 - 108366
Published: March 22, 2024
Language: Английский
Citations
6
Brain Topography, Journal Year: 2023, Volume and Issue: unknown
Published: Aug. 24, 2023
Abstract To reduce the psycho-social burden increasing attention has focused on brain abnormalities in most prevalent and highly co-occurring neuropsychiatric disorders, such as mood anxiety. However, high inter-study variability these patients results inconsistent contradictory alterations fast temporal dynamics of large-scale networks measured by EEG microstates. Thus, this meta-analysis, we aim to investigate consistency changes better understand possible common neuro-dynamical mechanisms disorders. In systematic search, twelve studies investigating microstate participants with anxiety disorders individuals subclinical depression were included adding up 787 participants. The suggest that microstates consistently discriminate impairments from general population states. Specifically, found a small significant effect size for B compared healthy controls, larger sizes increased presence unmedicated comorbidity. subgroup meta-analysis ten disorder studies, D showed decreased presence. When only two significantly A medium E (one study). more are needed elucidate whether findings diagnostic-specific markers. Results discussed relation functional meaning contribution an explanatory mechanism overlapping symptomatology
Language: Английский
Citations
14
Frontiers in Neuroscience, Journal Year: 2024, Volume and Issue: 18
Published: March 14, 2024
Recently, the microstate analysis method has been widely used to investigate temporal and spatial dynamics of electroencephalogram (EEG) signals. However, most studies have focused on EEG at resting state, few use study emotional EEG. This paper aims patterns in states, specific neurophysiological significance microstates during emotion cognitive process, further explore feasibility effectiveness applying recognition.
Language: Английский
Citations
5
Neural Networks, Journal Year: 2023, Volume and Issue: 171, P. 171 - 185
Published: Dec. 6, 2023
Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related meditation. However, previous mostly power in different frequency bands. The practical objective of this study was comprehensively test whether other types time-series analysis methods are better suited characterize To achieve this, we compared >7000 features the EEG signal differences meditators, using many measures that novel meditation research. Eyes-closed resting-state from 49 meditators and 46 non-meditators decomposed into top eight principal components (PCs). We extracted 7381 each PC participant used them train classification algorithms identify meditators. Highly differentiating individual successful classifiers were analysed detail. Only third (which had a central-parietal maximum) showed above-chance accuracy (67%, pFDR = 0.007), for which 405 significantly distinguished (all < 0.05). Top-performing indicated exhibited more consistent statistical properties across shorter subsegments their (higher stationarity) displayed an altered distributional shape values about mean. By contrast, trained with traditional band-power did not distinguish groups (pFDR > Our approach suggests key signatures meditators' higher temporal stability distribution suggestive longer, larger, or frequent non-outlying voltage deviations mean within data. observed component might underpin attentional associated identified here have considerable potential future exploration neural dynamics broadly.
Language: Английский
Citations
11
Cognitive Neurodynamics, Journal Year: 2025, Volume and Issue: 19(1)
Published: Jan. 3, 2025
Language: Английский
Citations
0