Literature DB >> 26364862

The reliability of continuous brain responses during naturalistic listening to music.

Iballa Burunat1, Petri Toiviainen2, Vinoo Alluri2, Brigitte Bogert3, Tapani Ristaniemi4, Mikko Sams5, Elvira Brattico6.   

Abstract

Low-level (timbral) and high-level (tonal and rhythmical) musical features during continuous listening to music, studied by functional magnetic resonance imaging (fMRI), have been shown to elicit large-scale responses in cognitive, motor, and limbic brain networks. Using a similar methodological approach and a similar group of participants, we aimed to study the replicability of previous findings. Participants' fMRI responses during continuous listening of a tango Nuevo piece were correlated voxelwise against the time series of a set of perceptually validated musical features computationally extracted from the music. The replicability of previous results and the present study was assessed by two approaches: (a) correlating the respective activation maps, and (b) computing the overlap of active voxels between datasets at variable levels of ranked significance. Activity elicited by timbral features was better replicable than activity elicited by tonal and rhythmical ones. These results indicate more reliable processing mechanisms for low-level musical features as compared to more high-level features. The processing of such high-level features is probably more sensitive to the state and traits of the listeners, as well as of their background in music.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Dice coefficient; Functional magnetic resonance imaging (fMRI); Interclass correlation; Musical features; Naturalistic paradigm; Reliability

Mesh:

Year:  2015        PMID: 26364862     DOI: 10.1016/j.neuroimage.2015.09.005

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  18 in total

1.  Connectivity patterns during music listening: Evidence for action-based processing in musicians.

Authors:  Vinoo Alluri; Petri Toiviainen; Iballa Burunat; Marina Kliuchko; Peter Vuust; Elvira Brattico
Journal:  Hum Brain Mapp       Date:  2017-03-28       Impact factor: 5.038

Review 2.  Music in the brain.

Authors:  Peter Vuust; Ole A Heggli; Karl J Friston; Morten L Kringelbach
Journal:  Nat Rev Neurosci       Date:  2022-03-29       Impact factor: 38.755

Review 3.  Identifying a brain network for musical rhythm: A functional neuroimaging meta-analysis and systematic review.

Authors:  Anna V Kasdan; Andrea N Burgess; Fabrizio Pizzagalli; Alyssa Scartozzi; Alexander Chern; Sonja A Kotz; Stephen M Wilson; Reyna L Gordon
Journal:  Neurosci Biobehav Rev       Date:  2022-03-05       Impact factor: 9.052

4.  Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music.

Authors:  Chao Liu; Elvira Brattico; Basel Abu-Jamous; Carlos S Pereira; Thomas Jacobsen; Asoke K Nandi
Journal:  Front Hum Neurosci       Date:  2017-12-19       Impact factor: 3.169

5.  Inconsistency in Abnormal Brain Activity across Cohorts of ADHD-200 in Children with Attention Deficit Hyperactivity Disorder.

Authors:  Jian-Bao Wang; Li-Jun Zheng; Qing-Jiu Cao; Yu-Feng Wang; Li Sun; Yu-Feng Zang; Hang Zhang
Journal:  Front Neurosci       Date:  2017-06-06       Impact factor: 4.677

6.  Coupling of Action-Perception Brain Networks during Musical Pulse Processing: Evidence from Region-of-Interest-Based Independent Component Analysis.

Authors:  Iballa Burunat; Valeri Tsatsishvili; Elvira Brattico; Petri Toiviainen
Journal:  Front Hum Neurosci       Date:  2017-05-09       Impact factor: 3.169

7.  Global Sensory Qualities and Aesthetic Experience in Music.

Authors:  Pauli Brattico; Elvira Brattico; Peter Vuust
Journal:  Front Neurosci       Date:  2017-04-05       Impact factor: 4.677

8.  Early auditory processing in musicians and dancers during a contemporary dance piece.

Authors:  Hanna Poikonen; Petri Toiviainen; Mari Tervaniemi
Journal:  Sci Rep       Date:  2016-09-09       Impact factor: 4.379

9.  Decoding the dynamic representation of musical pitch from human brain activity.

Authors:  N Sankaran; W F Thompson; S Carlile; T A Carlson
Journal:  Sci Rep       Date:  2018-01-16       Impact factor: 4.379

10.  Decoding Musical Training from Dynamic Processing of Musical Features in the Brain.

Authors:  Pasi Saari; Iballa Burunat; Elvira Brattico; Petri Toiviainen
Journal:  Sci Rep       Date:  2018-01-15       Impact factor: 4.379

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