The Influence of Cognitive Status on Brain Activity during Simulated Driving
Bibliographic record
Abstract
BACKGROUND: Driving with mild cognitive impairment (MCI) or early-stage Alzheimer's disease is common in many countries, despite the substantially increased risk of fatal accidents. In of Ontario, Canada, the government mandates that elderly drivers over 80 take cognitive screening tests (CSTs) every two years. However, there is little evidence to date that CST scores predict changes in the neural mechanisms underlying driving. The present work addresses this void by studying the correlation of brain activity during a simulated bus-following task with results of the Montreal Cognitive Assessment (MoCA) in a cohort of older drivers with and without MCI. It is hypothesized that drivers with low MoCA scores show increased activity of prefrontal areas (typically engaged during complex driving) when successfully performing bus following (staying in lane while following at safe distance on curved roads). Confirming these assertions would constitute early supporting evidence that simulated driving performance is modulated by cognitive status. METHODS: Thirty-two licensed drivers (50-76yrs, 28% female) were recruited from patients diagnosed with MCI (N = 12; MoCA: 22-27) and age-matched controls (N = 20; MoCA: 24-29). Participants performed a simulated bus-following task (∼220s) during fMRI at 3.0 Tesla, which required navigation of multiple roads while keeping a constant distance to a leading bus driving at variables speed. Brain activity associated with curved segments was estimated using participant-level general linear models, and subsequently correlated with MoCA score and age at group level using partial least squares analysis. RESULTS: Sixty-two percent of the covariance in brain activation during bus following was explained by a latent variable combining increasing age (bootstrapped z-score=2.0) and decreasing MoCA score (z-score=8.5; Figure 1). This latent variable correlated with increased brain activity in widespread prefrontal areas (Figure 2), including medial superior prefrontal cortex and dorsolateral superior and medial prefrontal cortex. CONCLUSIONS: The present study showed, for the first time, correlations between brain activity evoked during simulated safe driving and MoCA scores. Participants of lower MoCA score showed increased engagement of widespread prefrontal area, commonly associated with sustained attention and planning. Future work will design an adaptive test battery specifically screening for declines in fitness to drive.
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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 | 0.002 |
| 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".