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Early Musical Training and White-Matter Plasticity in the Corpus Callosum: Evidence for a Sensitive Period

2013· article· en· W2157938614 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Neuroscience · 2013
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsMcGill UniversityMontreal Neurological Institute and HospitalConcordia University
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsCorpus callosumWhite matterDiffusion MRIPeriod (music)Fractional anisotropyNeuroscienceNeuroplasticityTraining (meteorology)PsychologyAudiologyMedicineMagnetic resonance imagingPhysics

Abstract

fetched live from OpenAlex

Training during a sensitive period in development may have greater effects on brain structure and behavior than training later in life. Musicians are an excellent model for investigating sensitive periods because training starts early and can be quantified. Previous studies suggested that early training might be related to greater amounts of white matter in the corpus callosum, but did not control for length of training or identify behavioral correlates of structural change. The current study compared white-matter organization using diffusion tensor imaging in early- and late-trained musicians matched for years of training and experience. We found that early-trained musicians had greater connectivity in the posterior midbody/isthmus of the corpus callosum and that fractional anisotropy in this region was related to age of onset of training and sensorimotor synchronization performance. We propose that training before the age of 7 years results in changes in white-matter connectivity that may serve as a scaffold upon which ongoing experience can build.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.845
Threshold uncertainty score0.162

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.151
GPT teacher head0.377
Teacher spread0.226 · 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