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Record W4315436313 · doi:10.1002/aur.2888

Cerebellar gamma‐aminobutyric acid: Investigation of group effects in neurodevelopmental disorders

2023· article· en· W4315436313 on OpenAlexafffund
Elizabeth W. Pang, Christopher Hammill, Margot J. Taylor, Jamie Near, Russell Schachar, Jennifer Crosbie, Paul Arnold, Evdokia Anagnostou, Jason P. Lerch

Bibliographic record

VenueAutism Research · 2023
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of CalgarySunnybrook Health Science CentreUniversity of TorontoSickKids FoundationSunnybrook HospitalHospital for Sick Children
FundersAlberta InnovatesHospital for Sick ChildrenKing's College LondonOntario Brain Institute
KeywordsCerebellumNeuroscienceGlutamate receptorPsychologyAutismAutism spectrum disordergamma-Aminobutyric acidCognitionMedicinePsychiatryInternal medicineReceptor

Abstract

fetched live from OpenAlex

Neurodevelopmental disorders (NDDs) including autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD) are thought to arise in part from the disruption in the excitatory/inhibitory balance of gamma-aminobutyric acid (GABA) and glutamate in the brain. Recent evidence has shown the involvement of the cerebellum in cognition and affect regulation, and cerebellar atypical function or damage is reported frequently in NDDs. Magnetic resonance spectroscopy studies have reported decreases in GABA in cortical brain areas in the NDDs, however, GABA levels in the cerebellum have not been examined. To determine possible group effects, we used a MEGA-PRESS acquisition to investigate GABA+ levels in a cerebellar voxel in 343 individuals (aged 2.5-22 years) with ASD, ADHD, OCD and controls. Using a mixed effects model, we found no significant differences between groups in GABA+ concentration. Our findings suggest that cerebellar GABA+ levels do not differentiate NDD groups.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.625
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.007
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.061
GPT teacher head0.340
Teacher spread0.279 · 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

Citations11
Published2023
Admission routes2
Has abstractyes

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