Evidence map›Paper›PMID 31600231›Full record

ArticlePloS one2019

Discerning the functional networks behind processing of music and speech through human vocalizations.

Arafat Angulo-Perkins, Luis Concha

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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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

2 authors.

Arafat Angulo-PerkinsInstituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Querétaro, México.
Luis ConchaInstituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Querétaro, México.ORCID 0000-0002-7842-3869

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental question regarding music processing is its degree of independence from speech processing, in terms of their underlying neuroanatomy and influence of cognitive traits and abilities. Although a straight answer to that question is still lacking, a large number of studies have described where in the brain and in which contexts (tasks, stimuli, populations) this independence is, or is not, observed. We examined the independence between music and speech processing using functional magnetic resonance imagining and a stimulation paradigm with different human vocal sounds produced by the same voice. The stimuli were grouped as Speech (spoken sentences), Hum (hummed melodies), and Song (sung sentences); the sentences used in Speech and Song categories were the same, as well as the melodies used in the two musical categories. Each category had a scrambled counterpart which allowed us to render speech and melody unintelligible, while preserving global amplitude and frequency characteristics. Finally, we included a group of musicians to evaluate the influence of musical expertise. Similar global patterns of cortical activity were related to all sound categories compared to baseline, but important differences were evident. Regions more sensitive to musical sounds were located bilaterally in the anterior and posterior superior temporal gyrus (planum polare and temporale), the right supplementary and premotor areas, and the inferior frontal gyrus. However, only temporal areas and supplementary motor cortex remained music-selective after subtracting brain activity related to the scrambled stimuli. Speech-selective regions mainly affected by intelligibility of the stimuli were observed on the left pars opecularis and the anterior portion of the medial temporal gyrus. We did not find differences between musicians and non-musicians Our results confirmed music-selective cortical regions in associative cortices, independent of previous musical training.

Indexed as

MusicAcoustic StimulationAdultAuditory PerceptionBrainBrain MappingFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMotor CortexSpeechSpeech PerceptionVoice

Identifiers

PMID31600231
PMCPMC6786620

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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.