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Record W2610161052 · doi:10.1002/hbm.23624

Age‐related mapping of intracortical myelin from late adolescence to middle adulthood using T<sub>1</sub>‐weighted MRI

2017· article· en· W2610161052 on OpenAlexaff
Christopher D. Rowley, Manpreet Sehmbi, Pierre‐Louis Bazin, Christine Tardif, Luciano Minuzzi, Benício N. Frey, Nicholas A. Bock

Bibliographic record

VenueHuman Brain Mapping · 2017
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcGill UniversityDouglas Mental Health University InstituteMcMaster University
Fundersnot available
KeywordsWhite matterNeurosciencePremotor cortexPsychologyMagnetic resonance imagingCortex (anatomy)MyelinTrajectoryVentromedial prefrontal cortexPrefrontal cortexMedicinePhysicsCentral nervous systemAnatomyCognitionRadiology

Abstract

fetched live from OpenAlex

-weighted signal trajectory from late adolescence to middle adulthood in humans to characterize the age range when mental illnesses tend to present, and efficacy of treatments are evaluated. We compared linear to quadratic predictors of age on signal in 67 healthy individuals, 17-45 years old. We investigated ¼, ½, and ¾ depths in the cortex representing intracortical myelin (ICM), in the superficial white matter (SWM), and in a reference deep white matter tract. We found that the quadratic fit was superior in all regions of the cortex, while signal in the SWM and deep white matter showed no global dependence on age over this range. The signal trajectory in any region followed a similar shape regardless of cortical depth. The quadratic fit was analyzed in 70 cortical regions to obtain the age of maximum signal intensity. We found that visual, cingulate, and left ventromedial prefrontal cortices peak first around 34 years old, whereas motor and premotor areas peak latest at ∼38 years. Our analysis suggests that ICM trajectories over this range can be modeled well in small cohorts of subjects using quadratic functions, which are amenable to statistical analysis, thus suitable for investigating regional changes in ICM with disease. This study highlights a novel approach to map ICM trajectories using an age range that coincides with the onset of many mental illnesses. Hum Brain Mapp 38:3691-3703, 2017. © 2017 Wiley Periodicals, Inc.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.105
GPT teacher head0.343
Teacher spread0.238 · 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.

Study designBench or experimental
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

Citations48
Published2017
Admission routes1
Has abstractyes

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