Heritability of Response Inhibition in Children
Bibliographic record
Abstract
We report the heritability of response inhibition, latency, and variability, which are potential markers of genetic risk in neuropsychiatric conditions. Genetic and environmental influences on cancellation and restraint, response latency, and variability measured in a novel variant of the stop signal task were studied in 139 eight-year-old twin pairs from a birth cohort. Cancellation (50%), restraint (27%), and response latency (41%) showed significant heritability, the balance being non-shared environmental influences and/or error. Response variability was not heritable, with 23% of the variance attributable to shared environmental influences and 77% to non-shared environmental risk or error. The phenotypic correlation between response cancellation and restraint was -.44 and between response latency and restraint was .21. These phenotypic correlations were entirely genetic in origin. The phenotypic correlation between response variability and % successful inhibition was .27, but was not genetic. Cancellation and restraint were heritable and shared genetic influences, indicating that they may be influenced by a common gene or genes. Response latency was moderately heritable and shared genetic influences with restraint, but was not correlated with cancellation. Response variability was not heritable. These results support the potential of response inhibition and latency as endophenotypes in genetic research.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".