Neural function in <i>DCC</i> mutation carriers with and without mirror movements
Bibliographic record
Abstract
Objective Recently identified mutations of the axon guidance molecule receptor gene, DCC, present an opportunity to investigate, in living human brain, mechanisms affecting neural connectivity and the basis of mirror movements, involuntary contralateral responses that mirror voluntary unilateral actions. We hypothesized that haploinsufficient DCC +/− mutation carriers with mirror movements would exhibit decreased DCC mRNA expression, a functional ipsilateral corticospinal tract, greater “mirroring” motor representations, and reduced interhemispheric inhibition. DCC +/− mutation carriers without mirror movements might exhibit some of these features. Methods The participants (n = 52) included 13 DCC +/− mutation carriers with mirror movements, 7 DCC +/− mutation carriers without mirror movements, 13 relatives without the mutation or mirror movements, and 19 unrelated healthy volunteers. The multimodal approach comprised quantitative real time polymerase chain reaction, transcranial magnetic stimulation (TMS), functional magnetic resonance imaging (fMRI) under resting and task conditions, and measures of white matter integrity. Results Mirror movements were associated with reduced DCC mRNA expression, increased ipsilateral TMS‐induced motor evoked potentials, increased fMRI responses in the mirroring M1 and cerebellum, and markedly reduced interhemispheric inhibition. The DCC +/− mutation, irrespective of mirror movements, was associated with reduced functional connectivity and white matter integrity. Interpretation Diverse connectivity abnormalities were identified in mutation carriers with and without mirror movements, but corticospinal effects and decreased peripheral DCC mRNA appeared driven by the mirror movement phenotype. ANN NEUROL 2019;85:433–442.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".