Performance of antisaccades in patients with cerebral small vessel disease accompanied by white matter hyperintensities
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Bibliographic record
Abstract
Objectives The antisaccades (AS) task is considered a reliable indicator of inhibitory control of eye movements in humans. Achieving good AS performance requires efficient cognitive processes that are sensitive to changes in brain structure. White matter hyperintensities (WMH) can cause subcortical-cortical dysconnectivity, affecting diverse cognitive domains. Thus, the AS task was investigated in patients with WMH in cerebral small vessel disease (CSVD).Methods In this retrospective study, 75 participants with WMH, determined by neuroimaging standards for CSVD research, were admitted to the Department of Neurology of Beijing Luhe Hospital, Capital Medical University from January 2021 to December 2022. All subjects underwent the AS task, Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), and 3.0T brain MRI. Additionally, 61 healthy subjects were recruited to characterize WMH profiles.Results Compared to the control group, patients with WMH had a significantly increased AS error rate (49.81%, p = 0.001) and lower gain (76.00%, p = 0.042). The AS error rate was significantly higher in patients with WMH in the frontal lobe than in those without WMH (p = 0.004). After adjusting for confounders (age), a positive correlation was found between the AS error rate and MoCA scores for patients with WMH (coefficient = 0.262, p = 0.024).Conclusions Patients with WMH due to CSVD exhibited abnormal AS performances, particularly in the frontal lobe. The eye movement paradigms, the new diagnostic forms in neurology, can be utilized to investigate the distributed cortical and subcortical systems involved in cognitive control processes, offering simple, well-tolerated and highly sensitive advantages over traditional measures.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it