Impact of Regular Low-Level Alcohol Consumption on Cognitive Interference and Response Inhibition: An fMRI Investigation in Young Adults
Bibliographic record
Abstract
The purpose of the present dissertation was to shed light on the neurophysiological effect of regular consumption of low amounts of alcohol on two important aspects of executive functions, cognitive interference and response inhibition, using functional magnetic resonance imaging (fMRI) in a sample of young adults. Participants were recruited from the Ottawa Prenatal Prospective Study (OPPS), a longitudinal study that has collected data from participants from infancy to young adulthood, which permitted control of a number of potentially confounding drug and lifestyle variables. This allowed for investigation of the unique effect of alcohol use on executive functions. The dissertation itself is comprised of two original manuscripts: the first study compared low-level alcohol users to controls on performance of the Counting Stroop, a task of cognitive interference; and the second study compared users to controls on performance of the Go/No-Go, a task of response inhibition.Although the results of both studies found no performance differences between groups, low-level alcohol users had significantly more brain activation in several regions, including areas not typically associated with task processing, compared to irregular or non-drinker controls. This difference in neurophysiology may be reflective of compensatory strategies within the brain, whereby the recruitment of additional regions may be attempting to compensate for potential underlying deficits that occur with increasing cognitive demand. While further research is needed to validate this hypothesis, the present findings highlight the vulnerability of the developing brain.
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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) | 0.000 | 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".