Prenatal exposure to recreational drugs affects global motion perception in preschool children
Bibliographic record
Abstract
Prenatal exposure to recreational drugs impairs motor and cognitive development; however it is currently unknown whether visual brain areas are affected. To address this question, we investigated the effect of prenatal drug exposure on global motion perception, a behavioural measure of processing within the dorsal extrastriate visual cortex that is thought to be particularly vulnerable to abnormal neurodevelopment. Global motion perception was measured in one hundred and forty-five 4.5-year-old children who had been exposed to different combinations of methamphetamine, alcohol, nicotine and marijuana prior to birth and 25 unexposed children. Self-reported drug use by the mothers was verified by meconium analysis. We found that global motion perception was impaired by prenatal exposure to alcohol and improved significantly by exposure to marijuana. Exposure to both drugs prenatally had no effect. Other visual functions such as habitual visual acuity and stereoacuity were not affected by drug exposure. Prenatal exposure to methamphetamine did not influence visual function. Our results demonstrate that prenatal drug exposure can influence a behavioural measure of visual development, but that the effects are dependent on the specific drugs used during pregnancy.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".