Evidence map›Paper›PMID 25773370›Full record

ArticleMedical & biological engineering & computing2015

Comparison between human awake, meditation and drowsiness EEG activities based on directed transfer function and MVDR coherence methods.

Chamila Dissanayaka, Eti Ben-Simon, Michal Gruberger, Adi Maron-Katz, Haggai Sharon, Talma Hendler, Dean Cvetkovic

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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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0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Chamila DissanayakaSchool of Electrical and Computer Engineering, RMIT University, GPO Box 2476V, Melbourne, VIC, 3001, Australia, s3315014@student.rmit.edu.au.
Eti Ben-Simon
Michal Gruberger
Adi Maron-Katz
Haggai Sharon
Talma Hendler
Dean Cvetkovic

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

MeditationSignal Processing, Computer-AssistedAdultBrainElectroencephalographyHumansMiddle AgedSleep StagesWakefulness

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.