Evidence map›Paper›PMID 35684685›Full record

ArticleSensors (Basel, Switzerland)2022

EEG Connectivity during Active Emotional Musical Performance.

Mahrad Ghodousi, Jachin Edward Pousson, Aleksandras Voicikas, Valdis Bernhofs, Evaldas Pipinis, Povilas Tarailis, Lana Burmistrova, Yuan-Pin Lin, Inga Griškova-Bulanova

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mahrad GhodousiDepartment of Neurobiology and Biophysics, Vilnius University, 10257 Vilnius, Lithuania.ORCID 0000-0002-4828-5741
Jachin Edward PoussonJāzeps Vītols Latvian Academy of Music, 1050 Riga, Latvia.ORCID 0000-0001-6215-1099
Aleksandras VoicikasDepartment of Neurobiology and Biophysics, Vilnius University, 10257 Vilnius, Lithuania.
Valdis BernhofsJāzeps Vītols Latvian Academy of Music, 1050 Riga, Latvia.ORCID 0000-0001-6845-2773
Evaldas PipinisDepartment of Neurobiology and Biophysics, Vilnius University, 10257 Vilnius, Lithuania.
Povilas TarailisDepartment of Neurobiology and Biophysics, Vilnius University, 10257 Vilnius, Lithuania.
Lana BurmistrovaJāzeps Vītols Latvian Academy of Music, 1050 Riga, Latvia.
Yuan-Pin LinInstitute of Medical Science and Technology, National Sun Yat-sen University, Lienhai Road, Kaohsiung 80424, Taiwan.ORCID 0000-0002-3434-9118
Inga Griškova-BulanovaDepartment of Neurobiology and Biophysics, Vilnius University, 10257 Vilnius, Lithuania.

Funding

Lietuvos Mokslo Taryba S-LLT-19-3Ministry of Science and Technology, Taiwan MOST 108-2923-E-110-001-MY3State Education Development Agency, Republic of Latvia LV-LT-TW/2021/1
6 · The paper itself

Abstract

The neural correlates of intentional emotion transfer by the music performer are not well investigated as the present-day research mainly focuses on the assessment of emotions evoked by music. In this study, we aim to determine whether EEG connectivity patterns can reflect differences in information exchange during emotional playing. The EEG data were recorded while subjects were performing a simple piano score with contrasting emotional intentions and evaluated the subjectively experienced success of emotion transfer. The brain connectivity patterns were assessed from the EEG data using the Granger Causality approach. The effective connectivity was analyzed in different frequency bands-delta, theta, alpha, beta, and gamma. The features that (1) were able to discriminate between the neutral baseline and the emotional playing and (2) were shared across conditions, were used for further comparison. The low frequency bands-delta, theta, alpha-showed a limited number of connections (4 to 6) contributing to the discrimination between the emotional playing conditions. In contrast, a dense pattern of connections between regions that was able to discriminate between conditions (30 to 38) was observed in beta and gamma frequency ranges. The current study demonstrates that EEG-based connectivity in beta and gamma frequency ranges can effectively reflect the state of the networks involved in the emotional transfer through musical performance, whereas utility of the low frequency bands (delta, theta, alpha) remains questionable.

Indexed as

MusicBrainBrain MappingElectroencephalographyEmotionsHumansactive performanceconnectivityEEGemotionmusic

Identifiers

PMID35684685
PMCPMC9185252

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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.