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Cortical Thickness in Congenital Amusia: When Less Is Better Than More

2007· article· en· W2049371668 on OpenAlexafffund
Krista L. Hyde, Jason P. Lerch, Robert J. Zatorre, Timothy D. Griffiths, Alan C. Evans, Isabelle Peretz

Bibliographic record

VenueJournal of Neuroscience · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité de MontréalMcGill UniversityHospital for Sick ChildrenMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchWellcome TrustCentre for Interdisciplinary Research in Music Media and Technology
KeywordsPsychologyGyrusWhite matterCortex (anatomy)Cerebral cortexNeuroscienceAudiologyAuditory cortexInferior frontal gyrusVoxelVoxel-based morphometryMagnetic resonance imagingCognitionMedicine

Abstract

fetched live from OpenAlex

Congenital amusia (or tone deafness) is a lifelong disorder characterized by impairments in the perception and production of music. A previous voxel-based morphometry (VBM) study revealed that amusic individuals had reduced white matter in the right inferior frontal gyrus (IFG) relative to musically intact controls (Hyde et al., 2006). However, this VBM study also revealed associated increases in gray matter in the same right IFG region of amusics. The objective of the present study was to better understand this morphological brain anomaly by way of cortical thickness measures that provide a more specific measure of cortical morphology relative to VBM. We found that amusic subjects (n = 21) have thicker cortex in the right IFG and the right auditory cortex relative to musically intact controls (n = 26). These cortical thickness differences suggest the presence of cortical malformations in the amusic brain, such as abnormal neuronal migration, that may have compromised the normal development of a right frontotemporal pathway.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.321
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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

Citations302
Published2007
Admission routes2
Has abstractyes

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