Oculomotor planning (deficits) in coronary artery disease and mild-cognitive impairment
Bibliographic record
Abstract
Coronary artery disease (CAD) is a diverse clinical impairment that impacts not only vascular integrity but also elicits wide-ranging changes to central nervous system (CNS) structures. In particular, recent neuroimaging work by our group has shown that some persons with CAD exhibit cortical atrophy in the frontal brain structures supporting goal-directed movements (Goswami et al. 2011: Neuroimage). To address the behavioral consequences of cortical atrophy, the present study contrasted pro- and antisaccade latencies in persons with CAD (N = 10) and age-matched controls (N = 15). Importantly, we contrasted pro- and antisaccades between-groups to determine whether CAD differentially impacts stimulus-driven (i.e., prosaccades) and intentionally mediated (i.e., antisaccades) oculomotor networks. Surprisingly, results indicated that neither pro- nor antisaccade reaction times (RTs) differed between groups (ts < 1). Subsequently, we sought to determine whether a co-morbidity of CAD contributes to the above-mentioned changes in CNS structures. As such, we used the same pro- and antisaccade task in a corpus of individuals (N=13) falling under the clinical spectrum of mild-cognitive impairment (MCI). Results showed that persons with MCI elicited a marked increase in pro- and antisaccade RTs relative to the CAD group and their age-matched controls. That persons with MCI exhibit increased pro- and antisaccade planning times suggests that sensory- and intentionally-based actions are delayed even when an individual is in the very early stages of cognitive decline. Most notably, the present results suggest that a simple oculomotor task may provide the basis for identifying persons at risk for MCI.Acknowledgments: Supported by the Canadian Institutes for Health Research and the Natural Sciences and Engineering Research Council of Canada.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".