A Whole Brain EEG Analysis of Musicianship

Ribeiro, Estela; Thomaz, Carlos Eduardo

doi:10.1525/mp.2019.37.1.42

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…age, sex, musical experience. However, studies suggest that significant differences in music processing exist between different genders [92] as well as musicians and non-musicians [93][94][95]. Investigating these differences in the context of our proposed network-based features could potentially lead to increased decoding performance and should be taken into consideration in future studies.…”

Section: Future Perspectivesmentioning

confidence: 99%

On the estimate of music appraisal from surface EEG: a dynamic-network approach based on cross-sensor PAC measurements

2021

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Objective. The aesthetic evaluation of music is strongly dependent on the listener and reflects manifold brain processes that go well beyond the perception of incident sound. Being a high-level cognitive reaction, it is difficult to predict merely from the acoustic features of the audio signal and this poses serious challenges to contemporary music recommendation systems. We attempted to decode music appraisal from brain activity, recorded via wearable EEG, during music listening. Approach. To comply with the dynamic nature of music stimuli, cross-frequency coupling measurements were employed in a time-evolving manner to capture the evolving interactions between distinct brain-rhythms during music listening. Brain response to music was first represented as a continuous flow of functional couplings referring to both regional and inter-regional brain dynamics and then modelled as an ensemble of time-varying (sub)networks. Dynamic graph centrality measures were derived, next, as the final feature-engineering step and, lastly, a support-vector machine was trained to decode the subjective music appraisal. A carefully designed experimental paradigm provided the labeled brain signals. Main results. Using data from 20 subjects, dynamic programming to tailor the decoder to each subject individually and cross-validation, we demonstrated highly satisfactory performance (MAE= 0.948, R 2= 0.63) that can be attributed, mostly, to interactions of left frontal gamma rhythm. In addition, our music-appraisal decoder was also employed in a part of the DEAP dataset with similar success. Finally, even a generic version of the decoder (common for all subjects) was found to perform sufficiently. Significance. A novel brain signal decoding scheme was introduced and validated empirically on suitable experimental data. It requires simple operations and leaves room for real-time implementation. Both the code and the experimental data are publicly available.

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Section: Future Perspectivesmentioning

confidence: 99%

On the estimate of music appraisal from surface EEG: a dynamic-network approach based on cross-sensor PAC measurements

2021

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“…These studies show the role of music in the development of human cognitive abilities [13]. Activation of neuronal patterns in response to music can show whether a participant has music education [14]. The acquisition of music changes the perception of hearing and the related organization of the brain, so it characterizes the plasticity of the brain.…”

Section: Introductionmentioning

confidence: 99%

EEG Spectral Feature Markers as an Indicator of Human Cognitive Process

Porozovs¹,

Veliks

Kļaviņa

et al. 2023

Int. J. Emerg. Technol. Learn.

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Information technologies allow using modern and timely effective analyses of EEG waves and the methods of data processing that allows effective usage of this method into pedagogically and psychologically oriented researches. Aim of this study was to develop and validate method of EEG signal spectral properties usage in the investigations of the process of cognition in the process of the perception of music by the choice of professional studies. 23 research participants took part in the research – the students of the University of Latvia, the division of participants "non-musician" and "musician". The EEG recording synchronized with the musical signal using the generated synchronization signal that given to one of the unipolar input channels of the EEG equipment. The research analyses the basic rhythm of EEG the changes of the maximum frequency and the wave frequency power in the processes connected with the perception and cognition of music for 15 seconds long intervals. During the time of listening to the chorus songs, the range frequency of the range rhythm of alpha and beta does not change to the musicians but during the time of listening to the instrumental music it increases but it was more vivid in the range of beta frequency. Non-musicians reacted differently - while listening to chorus songs and instrumental music the frequency of alfa waves of EEG increased, but the beta wave frequency decreased. EEG as a method of investigation is recommended for pedagogical research to evaluate the neurological functions in the cognitive processes.

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A Whole Brain EEG Analysis of Musicianship

Cited by 2 publications

References 26 publications

On the estimate of music appraisal from surface EEG: a dynamic-network approach based on cross-sensor PAC measurements

On the estimate of music appraisal from surface EEG: a dynamic-network approach based on cross-sensor PAC measurements

EEG Spectral Feature Markers as an Indicator of Human Cognitive Process

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