Evidence map›Paper›PMID 34675231›Full record

SynthesisScientific reports2021

An ALE meta-analytic review of top-down and bottom-up processing of music in the brain.

Victor Pando-Naude, Agata Patyczek, Leonardo Bonetti, Peter Vuust

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 4 pooled it
–field-weighted citation impact
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

31 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

4 authors.

Victor Pando-Naude *Center for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Universitetsbyen, 3-0-17, 8000, Aarhus C, Denmark. pandonaude@clin.au.dk.
Agata Patyczek *MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
Leonardo BonettiCenter for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Universitetsbyen, 3-0-17, 8000, Aarhus C, Denmark.
Peter VuustCenter for Music in the Brain, Department of Clinical Medicine, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Universitetsbyen, 3-0-17, 8000, Aarhus C, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A remarkable feature of the human brain is its ability to integrate information from the environment with internally generated content. The integration of top-down and bottom-up processes during complex multi-modal human activities, however, is yet to be fully understood. Music provides an excellent model for understanding this since music listening leads to the urge to move, and music making entails both playing and listening at the same time (i.e., audio-motor coupling). Here, we conducted activation likelihood estimation (ALE) meta-analyses of 130 neuroimaging studies of music perception, production and imagery, with 2660 foci, 139 experiments, and 2516 participants. We found that music perception and production rely on auditory cortices and sensorimotor cortices, while music imagery recruits distinct parietal regions. This indicates that the brain requires different structures to process similar information which is made available either by an interaction with the environment (i.e., bottom-up) or by internally generated content (i.e., top-down).

Indexed as

Auditory PerceptionMusicAuditory CortexBrainBrain MappingHumansImagination

Identifiers

PMID34675231
PMCPMC8531391

What OpenQuestion holds

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LicenceCC BY
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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.