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Record W2048752780 · doi:10.3109/17518423.2010.547545

Exploring the neural mechanisms that underlie motor difficulties in children with Attention Deficit Hyperactivity Disorder

2011· review· en· W2048752780 on OpenAlexaff
Marie Brossard‐Racine, Annette Majnemer, Michael Shevell

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2011
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsMontreal Children's HospitalMcGill University
FundersH2020 European Research Council
KeywordsNeuroimagingPsychologyAttention deficit hyperactivity disorderNeuroscienceModalitiesAttention deficitsAttention deficitPopulationCognitive psychologyPhysical medicine and rehabilitationClinical psychologyMedicineCognition

Abstract

fetched live from OpenAlex

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is the most common neurobehavioural disorder of childhood. Motor performance appears to be impaired for an important sub-set of this population. OBJECTIVES: This structured review draws attention to the neurological mechanisms that could potentially explain these difficulties. METHODS: In August 2010, Medline, PsychINFO and Embase databases were searched with keywords related to ADHD, neuroimaging modalities and motor performance. RESULTS: Four studies were retrieved that examined both motor performance and possible neural substrates. Each study explored different hypotheses and no common conclusion is emerging. The cortical activation dysregulation hypothesis, the cerebellar dysfunction hypothesis and the delayed white matter maturation hypothesis were proposed, applying combinations of motor observations and neuroimaging findings. CONCLUSION: Published literature to date is insufficient to confirm specific hypotheses. Additional studies coupling discrete motor evaluations to neuroimaging techniques are needed in children with ADHD to better understand the neurobiological mechanisms of their motor difficulties.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.120
GPT teacher head0.304
Teacher spread0.185 · 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 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

Citations24
Published2011
Admission routes1
Has abstractyes

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