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Record W2140975371 · doi:10.3389/fnhum.2014.00294

Music as a Mnemonic to Learn Gesture Sequences in Normal Aging and Alzheimer’s Disease

2014· article· en· W2140975371 on OpenAlexafffund
Aline Moussard, Emmanuel Bigand, Sylvie Belleville, Isabelle Peretz

Bibliographic record

VenueFrontiers in Human Neuroscience · 2014
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsMcGill UniversityCentre for Research on Brain Language and MusicInternational Laboratory for Brain, Music and Sound ResearchInstitut Universitaire de Gériatrie de MontréalUniversity of TorontoUniversité de MontréalBaycrest Hospital
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaAlzheimer Society
KeywordsMnemonicGesturePsychologyMetronomeCognitive psychologyDementiaNeuroscienceAudiologyDiseaseRhythmComputer scienceMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

Strong links between music and motor functions suggest that music could represent an interesting aid for motor learning. The present study aims for the first time to test the potential of music to assist in the learning of sequences of gestures in normal and pathological aging. Participants with mild Alzheimer's disease (AD) and healthy older adults (controls) learned sequences of meaningless gestures that were either accompanied by music or a metronome. We also manipulated the learning procedure such that participants had to imitate the gestures to-be-memorized in synchrony with the experimenter or after the experimenter during encoding. Results show different patterns of performance for the two groups. Overall, musical accompaniment had no impact on the controls' performance but improved those of AD participants. Conversely, synchronization of gestures during learning helped controls but seemed to interfere with retention in AD. We discuss these findings regarding their relevance for a better understanding of auditory-motor memory, and we propose recommendations to maximize the mnemonic effect of music for motor sequence learning for dementia care.

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)0.000
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 score0.013
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.034
GPT teacher head0.309
Teacher spread0.275 · 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

Citations27
Published2014
Admission routes2
Has abstractyes

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