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Record W4403159601 · doi:10.1080/17518423.2024.2410184

An exploratory study of functional brain activity associated with gross motor function improvement in children with unilateral cerebral palsy

2024· article· en· W4403159601 on OpenAlexafffund
Alicia Hilderley, Darcy Fehlings, Margot J. Taylor, Jerry L. Chen, F. Virginia Wright

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsHospital for Sick ChildrenToronto Rehabilitation InstituteUniversity of TorontoHolland Bloorview Kids Rehabilitation Hospital
FundersOntario Brain Institute
KeywordsCerebral palsyPhysical medicine and rehabilitationGross motor skillPsychologyMedicineMotor functionMotor skillPhysical therapyNeuroscience

Abstract

fetched live from OpenAlex

Purpose Identify relations of gross motor function and primary motor cortex (M1) functional activity pre and post gross motor interventions for children with unilateral cerebral palsy (UCP).Methods Thirteen children with UCP completed a gross motor intervention. Pre/post-intervention functional MRI outcomes included the laterality index (LI), activation volume, and spatial overlap of M1 activation during active ankle dorsiflexion. Advanced gross motor function (Challenge) was assessed pre/post-intervention, and 2–6 months later. Bivariate correlations and linear regression assessed relations between neuroimaging and motor function.Results Mean pre-intervention M1 activity was contralateral during dominant (LI = +0.85, SD 0.21) but variable during the affected (LI = +0.43, SD 0.57) ankle dorsiflexion. Changes in motor function and neuroimaging outcomes were not significantly associated. However, smaller affected ankle activation and less spatial overlap between ankle activations pre-intervention predicted Challenge improvements post-intervention (adjusted R2 = 0.74, p = .001.)Conclusions This exploratory study identified pre-intervention neuroimaging predictors of post-intervention improvements in advanced gross motor function.

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 score0.032
Threshold uncertainty score0.733

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 communication0.0000.001
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 head0.012
GPT teacher head0.241
Teacher spread0.228 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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