Evidence map›Paper›PMID 31263113›Full record

ArticleScientific reports2019

Electroencephalography reflects the activity of sub-cortical brain regions during approach-withdrawal behaviour while listening to music.

Ian Daly, Duncan Williams, Faustina Hwang, Alexis Kirke, Eduardo R Miranda, Slawomir J Nasuto

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.7field-weighted citation impact, top 6% of its field
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

21 citing papers in PubMed, 71 citations in OpenAlex.

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  12. Neural decoding of music from the EEG.Scientific reports · 2023
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  18. Mathematical Modeling of Brain Activity under Specific Auditory Stimulation.Computational and mathematical methods in medicine · 2021
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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

6 authors at 4 institutions in 1 country.

Ian DalyBrain-Computer Interfacing and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, Colchester, CO4 3SQ, UK. i.daly@essex.ac.uk.ORCID http://orcid.org/0000-0001-5489-0393
Duncan WilliamsDigital Creativity Labs, Department of Computer Science, University of York, Heslington, YO10 5RG, UK.
Faustina HwangBrain Embodiment Laboratory, Biomedical Sciences and Biomedical Engineering Division, School of Biological Sciences, University of Reading, Reading, RG6 6AY, UK.
Alexis KirkeInterdisciplinary Centre for Computer Music Research, University of Plymouth, Plymouth, PL4 8AA, UK.
Eduardo R MirandaInterdisciplinary Centre for Computer Music Research, University of Plymouth, Plymouth, PL4 8AA, UK.
Slawomir J NasutoBrain Embodiment Laboratory, Biomedical Sciences and Biomedical Engineering Division, School of Biological Sciences, University of Reading, Reading, RG6 6AY, UK.
University of Plymouth · GBUniversity of Reading · GBUniversity of Essex · GBUniversity of York · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability of music to evoke activity changes in the core brain structures that underlie the experience of emotion suggests that it has the potential to be used in therapies for emotion disorders. A large volume of research has identified a network of sub-cortical brain regions underlying music-induced emotions. Additionally, separate evidence from electroencephalography (EEG) studies suggests that prefrontal asymmetry in the EEG reflects the approach-withdrawal response to music-induced emotion. However, fMRI and EEG measure quite different brain processes and we do not have a detailed understanding of the functional relationships between them in relation to music-induced emotion. We employ a joint EEG - fMRI paradigm to explore how EEG-based neural correlates of the approach-withdrawal response to music reflect activity changes in the sub-cortical emotional response network. The neural correlates examined are asymmetry in the prefrontal EEG, and the degree of disorder in that asymmetry over time, as measured by entropy. Participants' EEG and fMRI were recorded simultaneously while the participants listened to music that had been specifically generated to target the elicitation of a wide range of affective states. While listening to this music, participants also continuously reported their felt affective states. Here we report on co-variations in the dynamics of these self-reports, the EEG, and the sub-cortical brain activity. We find that a set of sub-cortical brain regions in the emotional response network exhibits activity that significantly relates to prefrontal EEG asymmetry. Specifically, EEG in the pre-frontal cortex reflects not only cortical activity, but also changes in activity in the amygdala, posterior temporal cortex, and cerebellum. We also find that, while the magnitude of the asymmetry reflects activity in parts of the limbic and paralimbic systems, the entropy of that asymmetry reflects activity in parts of the autonomic response network such as the auditory cortex. This suggests that asymmetry magnitude reflects affective responses to music, while asymmetry entropy reflects autonomic responses to music. Thus, we demonstrate that it is possible to infer activity in the limbic and paralimbic systems from pre-frontal EEG asymmetry. These results show how EEG can be used to measure and monitor changes in the limbic and paralimbic systems. Specifically, they suggest that EEG asymmetry acts as an indicator of sub-cortical changes in activity induced by music. This shows that EEG may be used as a measure of the effectiveness of music therapy to evoke changes in activity in the sub-cortical emotion response network. This is also the first time that the activity of sub-cortical regions, normally considered "invisible" to EEG, has been shown to be characterisable directly from EEG dynamics measured during music listening.

Indexed as

MusicAcoustic StimulationAdultBrainBrain MappingElectroencephalographyFemaleHumansMagnetic Resonance ImagingYoung Adult

Identifiers

PMID31263113
PMCPMC6603018
OpenAlexW2955826210

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.