Literature DB >> 31263113

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

Ian Daly1, Duncan Williams2, Faustina Hwang3, Alexis Kirke4, Eduardo R Miranda4, Slawomir J Nasuto3.   

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.

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Year:  2019        PMID: 31263113      PMCID: PMC6603018          DOI: 10.1038/s41598-019-45105-2

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  62 in total

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  4 in total

1.  Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolutional Neural Network.

Authors:  Nagarajan Ganapathy; Yedukondala Rao Veeranki; Himanshu Kumar; Ramakrishnan Swaminathan
Journal:  J Med Syst       Date:  2021-03-04       Impact factor: 4.460

2.  A survey of brain network analysis by electroencephalographic signals.

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Journal:  Cogn Neurodyn       Date:  2021-06-14       Impact factor: 5.082

3.  Mathematical Modeling of Brain Activity under Specific Auditory Stimulation.

Authors:  Marius Georgescu; Laura Haidar; Alina-Florina Serb; Daniela Puscasiu; Daniel Georgescu
Journal:  Comput Math Methods Med       Date:  2021-04-21       Impact factor: 2.238

4.  Neural and physiological data from participants listening to affective music.

Authors:  Ian Daly; Nicoletta Nicolaou; Duncan Williams; Faustina Hwang; Alexis Kirke; Eduardo Miranda; Slawomir J Nasuto
Journal:  Sci Data       Date:  2020-06-15       Impact factor: 6.444

  4 in total

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