ArticleMedical & biological engineering & computing2015
Comparison between human awake, meditation and drowsiness EEG activities based on directed transfer function and MVDR coherence methods.
Article in Medical & biological engineering & computing, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- The Modulatory Effect of tDCS Onset Timing in Alleviating Vigilance Decrement.Brain sciences · 2025Article
- Estimation of Task-Related Dynamic Brain Connectivity via Data Inflation and Classification Model Explainability.Neuroinformatics · 2025Article
- EEG-based investigation of effects of mindfulness meditation training on state and trait by deep learning and traditional machine learning.Frontiers in human neuroscience · 2023Article
- Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study.Frontiers in aging neuroscience · 2023Article
- A Feature Extraction Algorithm of Brain Network of Motor Imagination Based on a Directed Transfer Function.Computational intelligence and neuroscience · 2022Article
- A Critical Analysis on Characterizing the Meditation Experience Through the Electroencephalogram.Frontiers in systems neuroscience · 2020Review
- EEG indices correlate with sustained attention performance in patients affected by diffuse axonal injury.Medical & biological engineering & computing · 2018Article
- Commentary: Patanjali and neuroscientific research on meditation.Frontiers in psychology · 2018Article
- A unified canonical correlation analysis-based framework for removing gradient artifact in concurrent EEG/fMRI recording and motion artifact in walking recording from EEG signal.Medical & biological engineering & computing · 2017Article
- Exploring time- and frequency- dependent functional connectivity and brain networks during deception with single-trial event-related potentials.Scientific reports · 2016Article
- Combining Partial Directed Coherence and Graph Theory to Analyse Effective Brain Networks of Different Mental Tasks.Frontiers in human neuroscience · 2016Article
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7 authors.
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Abstract
This study examined the electroencephalogram functional connectivity (coherence) and effective connectivity (flow of information) of selected brain regions during three different attentive states: awake, meditation and drowsiness. For the estimation of functional connectivity (coherence), Welch and minimum variance distortionless response (MVDR) methods were compared. The MVDR coherence was found to be more suitable since it is both data and frequency dependent and enables higher spectral resolution, while Welch's periodogram-based approach is both data and frequency independent. The directed transfer function (DTF) method was applied in order to estimate the effective connectivity or brain's flow of information between different regions during each state. DTF enables to identify the main brain areas that initiate EEG activity and the spatial distribution of these activities with time. Analysis was conducted using the EEG data of 30 subjects (ten awake, ten drowsy and ten meditating) focusing on six main electrodes (F3, F4, C3, C4, P3, P4, O1 and O2). For each subject, EEG data were recorded during 5-min baseline and 15 min of a specific condition (awake, meditation or drowsiness). Statistical analysis included the Kruskal-Wallis (KW) nonparametric analysis of variance followed by post hoc tests with Bonferroni alpha correction. The results reveal that both states of drowsiness and meditation states lead to a marked difference in the brain's flow of information (effective connectivity) as shown by DTF analyses. In specific, a significant increase in the flow of information in the delta frequency band was found only in the meditation condition and was further found to originate from frontal (F3, F4), parietal (P3, P4) and occipital (O1, O2) regions. Altogether, these results suggest that a change in attentiveness leads to significant changes in the spectral profile of the brain's information flow as well as in its functional connectivity and that these changes can be captured using coherence and DTF analyses.
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