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Record W4293826017 · doi:10.3389/fnsys.2022.886427

Musical abilities in children with developmental cerebellar anomalies

2022· article· en· W4293826017 on OpenAlexaboutno aff
Antoine Guinamard, Sylvain Clément, Sophie Goemaere, Alice Mary, Audrey Riquet, Delphine Dellacherie

Bibliographic record

VenueFrontiers in Systems Neuroscience · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsnot available
Fundersnot available
KeywordsMelodyPsychologySingingRhythmAudiologyPerceptionAuditory perceptionCognitive psychologyDevelopmental psychologyNeuroscienceMusicalMedicine

Abstract

fetched live from OpenAlex

Developmental Cerebellar Anomalies (DCA) are rare diseases (e.g., Joubert syndrome) that affect various motor and non-motor functions during childhood. The present study examined whether music perception and production are affected in children with DCA. Sixteen children with DCA and 37 healthy matched control children were tested with the Montreal Battery for Evaluation of Musical Abilities (MBEMA) to assess musical perception. Musical production was assessed using two singing tasks: a pitch-matching task and a melodic reproduction task. Mixed model analyses showed that children with DCA were impaired on the MBEMA rhythm perception subtest, whereas there was no difference between the two groups on the melodic perception subtest. Children with DCA were also impaired in the melodic reproduction task. In both groups, singing performance was positively correlated with rhythmic and melodic perception scores, and a strong correlation was found between singing ability and oro-bucco-facial praxis in children with DCA. Overall, children with DCA showed impairments in both music perception and production, although heterogeneity in cerebellar patient's profiles was highlighted by individual analyses. These results confirm the role of the cerebellum in rhythm processing as well as in the vocal sensorimotor loop in a developmental perspective. Rhythmic deficits in cerebellar patients are discussed in light of recent work on predictive timing networks including the cerebellum. Our results open innovative remediation perspectives aiming at improving perceptual and/or production musical abilities while considering the heterogeneity of patients' clinical profiles to design music-based therapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.221
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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