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Record W4393279223 · doi:10.1093/brain/awae094

Lesion network of oculogyric crises maps to brain dopaminergic transcriptomic signature

2024· article· en· W4393279223 on OpenAlexaff
Bassam Al‐Fatly, Clemens Neudorfer, Diego Kaski, Anthony E. Lang, Andrea A. Kühn, Michael Fox, Andreas Horn, Christos Ganos

Bibliographic record

VenueBrain · 2024
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsToronto Western Hospital
FundersVolkswagen Foundation
KeywordsNeuroscienceLesionBasal gangliaMedicineDopamine receptorDopamineDopaminergicPsychologyPathologyCentral nervous system

Abstract

fetched live from OpenAlex

Oculogyric crises are acute episodes of sustained, typically upward, conjugate deviation of the eyes. Oculogyric crises usually occur as the result of acute D2-dopamine receptor blockade, but the brain areas causally involved in generating this symptom remain elusive. Here, we used data from 14 previously reported cases of lesion-induced oculogyric crises and employed lesion network mapping to identify their shared connections throughout the brain. This analysis yielded a common network that included basal ganglia, thalamic and brainstem nuclei, as well as the cerebellum. Comparison of this network with gene expression profiles associated with the dopamine system revealed spatial overlap specifically with the gene coding for dopamine receptor type 2 (DRD2), as defined by a large-scale transcriptomic database of the human brain. Furthermore, spatial overlap with DRD2 and DRD3 gene expression was specific to brain lesions associated with oculogyric crises when contrasted to lesions that led to other movement disorders. Our findings identify a common neural network causally involved in the occurrence of oculogyric crises and provide a pathophysiological link between lesion locations causing this syndrome and its most common pharmacological cause, namely DRD2 blockade.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.514

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 communication0.0000.000
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 head0.014
GPT teacher head0.281
Teacher spread0.266 · 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 designNot applicable
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

Citations5
Published2024
Admission routes1
Has abstractyes

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