Dataset Information

Relationship between Spatiotemporal Dynamics of the Brain at Rest and Self-Reported Spontaneous Thoughts: An EEG Microstate Approach.

ABSTRACT: The resting-state paradigm is frequently applied in electroencephalography (EEG) research; however, it is associated with the inability to control participants' thoughts. To quantify subjects' subjective experiences at rest, the Amsterdam Resting-State Questionnaire (ARSQ) was introduced covering ten dimensions of mind wandering. We aimed to estimate associations between subjective experiences and resting-state microstates of EEG. 5 min resting-state EEG data of 197 subjects was used to evaluate temporal properties of seven microstate classes. Bayesian correlation approach was implemented to assess associations between ARSQ domains assessed after resting and parameters of microstates. Several associations between Comfort, Self and Somatic Awareness domains and temporal properties of neuroelectric microstates were revealed. The positive correlation between Comfort and duration of microstates E showed the strongest evidence (BF10 > 10); remaining correlations showed substantial evidence (10 > BF10 > 3). Our study indicates the relevance of assessments of spontaneous thought occurring during the resting-state for the understanding of the intrinsic brain activity reflected in microstates.

SUBMITTER: Tarailis P

PROVIDER: S-EPMC8625384 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Relationship between Spatiotemporal Dynamics of the Brain at Rest and Self-Reported Spontaneous Thoughts: An EEG Microstate Approach.

Tarailis Povilas P Šimkutė Dovilė D Koenig Thomas T Griškova-Bulanova Inga I

Journal of personalized medicine 20211117 11

<h4>Rationale</h4>The resting-state paradigm is frequently applied in electroencephalography (EEG) research; however, it is associated with the inability to control participants' thoughts. To quantify subjects' subjective experiences at rest, the Amsterdam Resting-State Questionnaire (ARSQ) was introduced covering ten dimensions of mind wandering. We aimed to estimate associations between subjective experiences and resting-state microstates of EEG.<h4>Methods</h4>5 min resting-state EEG data of ...[more]

PMID: 34834568

Similar Datasets

Project description:The brain, as a complex dynamically distributed information processing system, involves the coordination of large-scale brain networks such as neural synchronization and fast brain state transitions, even at rest. However, the neural mechanisms underlying brain states and the impact of dysfunction following brain injury on brain dynamics remain poorly understood. To this end, we proposed a microstate-based method to explore the functional connectivity pattern associated with each microstate class. We capitalized on microstate features from eyes-closed resting-state EEG data to investigate whether microstate dynamics differ between subacute stroke patients (N = 31) and healthy populations (N = 23) and further examined the correlations between microstate features and behaviors. An important finding in this study was that each microstate class was associated with a distinct functional connectivity pattern, and it was highly consistent across different groups (including an independent dataset). Although the connectivity patterns were diminished in stroke patients, the skeleton of the patterns was retained to some extent. Nevertheless, stroke patients showed significant differences in most parameters of microstates A, B, and C compared to healthy controls. Notably, microstate C exhibited an opposite pattern of differences to microstates A and B. On the other hand, there were no significant differences in all microstate parameters for patients with left-sided vs. right-sided stroke, as well as patients before vs. after lower limb training. Moreover, support vector machine (SVM) models were developed using only microstate features and achieved moderate discrimination between patients and controls. Furthermore, significant negative correlations were observed between the microstate-wise functional connectivity and lower limb motor scores. Overall, these results suggest that the changes in microstate dynamics for stroke patients appear to be state-selective, compensatory, and related to brain dysfunction after stroke and subsequent functional reconfiguration. These findings offer new insights into understanding the neural mechanisms of microstates, uncovering stroke-related alterations in brain dynamics, and exploring new treatments for stroke patients.

Project description:ObjectiveThis study aims to investigate the relationship between the subjective performance evaluations on pilot trainees' aircraft control abilities and their brainwave dynamics reflected in the results from EEG microstate analysis. Specifically, we seek to identify correlations between distinct microstate patterns and each dimension included in the subjective flight control evaluations, shedding light on the neurophysiological mechanisms underlying aviation expertise and possible directions for future improvements in pilot training.BackgroundProficiency in aircraft control is crucial for aviation safety and modern aviation where pilots need to maneuver aircraft through an array of situations, ranging from routine takeoffs and landings to complex weather conditions and emergencies. However, the neurophysiological aspects of aviation expertise remain largely unexplored. This research bridges the gap by examining the relationship between pilot trainees' specific brainwave patterns and their subjective evaluations of flight control levels, offering insights into the cognitive underpinnings of pilot skill efficiency and development.MethodEEG microstate analysis was employed to examine the brainwave dynamics of pilot trainees while they performed aircraft control tasks under a flight simulator-based pilot training process. Trainees' control performance was evaluated by experienced instructors across five dimensions and their EEG data were analyzed to investigate the associations between the parameters of specific microstates with successful aircraft control.ResultsThe experimental results revealed significant associations between aircraft control levels and the parameters of distinct EEG microstates. Notably, these associations varied across control dimensions, highlighting the multifaceted nature of control proficiency. Noteworthy correlations included positive correlations between microstate class E and class G with aircraft control, emphasizing the role of attentional processes, perceptual integration, working memory, cognitive flexibility, decision-making, and executive control in aviation expertise. Conversely, negative correlations between microstate class C and class F with aircraft control indicated links between pilot trainees' cognitive control and their control performance on flight tasks.ConclusionThe findings underscore the multidimensional nature of aircraft control proficiency and emphasize the significance of attentional and cognitive processes in achieving aviation expertise. These neurophysiological markers offer a basis for designing targeted pilot training programs and interventions to enhance trainees' aircraft control skills.

Dataset Information

Relationship between Spatiotemporal Dynamics of the Brain at Rest and Self-Reported Spontaneous Thoughts: An EEG Microstate Approach.

Publications

Relationship between Spatiotemporal Dynamics of the Brain at Rest and Self-Reported Spontaneous Thoughts: An EEG Microstate Approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets