Literature DB >> 33857935

Analysis of cerebral blood flow entropy when listening music with emotional content.

Ruben Cavieres1, Jean Landerretche2, José L Jara3, Max Chacon4.   

Abstract

Music is one of the most sublime stimulus that human beings can experience. Despite being just an acoustic wave that exert little physical action on a subject, it triggers profound changes in emotions and physiological states. This study explores the possibility of detecting subtle changes in cerebral blood flow velocity in response to emotional reactions produced by different musical stimuli using multiscale entropy analysis. This method has shown to be able to reveal the complexity of internal dynamics of different physiological systems, which cannot be appreciated with classic approaches based on entropy on a single scale. Cerebral blood flow signals were successfully recorded for 16 subjects while performing five different music tasks. The entropy of each signal was estimated using multiscale sample entropy. Significant differences in entropy was found between two tasks, which suggests that intense cognitive activities having emotional content yield a decrease in the entropy of cerebral haemodynamics.
© 2021 Institute of Physics and Engineering in Medicine.

Entities:  

Keywords:  Cerebral Blood Flow; Haemodynamics; Multiscale Entropy; Music; Sample Entropy

Year:  2021        PMID: 33857935     DOI: 10.1088/1361-6579/abf885

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  2 in total

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Authors:  Li Yang
Journal:  J Environ Public Health       Date:  2022-09-01

2.  Machine Learning Models and Statistical Complexity to Analyze the Effects of Posture on Cerebral Hemodynamics.

Authors:  Max Chacón; Hector Rojas-Pescio; Sergio Peñaloza; Jean Landerretche
Journal:  Entropy (Basel)       Date:  2022-03-19       Impact factor: 2.524

  2 in total

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