IC‐P‐087: Antisaccades in Alzheimer's disease using fMRI
Bibliographic record
Abstract
Saccades are served by a network of cortical and subcortical regions, and there are well-described abnormalities in AD. The antisaccade task is one of the most cognitively demanding saccadic tasks. The correct performance of an antisaccade requires the suppression of a reflexive response to a visual stimulus and instead, the generation of a volitional saccade to the mirror opposite location. Antisaccades are an important demonstration of the execution of internal goals, rather than sensory-driven responses. AD subjects exhibit impaired suppression and generate erroneous reflexive saccades towards the target. To date, no fMRI studies of antisaccades in AD have been reported. Fifteen AD and 16 control subjects performed the antisaccade task first in the laboratory and then during 3T fMRI. fMRI data were normalised to an elderly template. All completed a neuropsychological battery and Montreal Cognitive assessment (MoCA). There were significantly more antisaccade errors, and significantly longer correct antisaccade latencies in the AD group, which correlated with neuropsychological measures. The AD group demonstrated greater fMRI activity in the temporo-occipital cortex compared with the Control group. Overall, the AD group demonstrated reduced activity in all oculomotor regions (frontal eye fields, dorsolateral prefrontal cortex, intraparietal sulcus, pre-supplementary motor area and the supplementary eye fields) compared to Controls. The generation of a successful antisaccade requires an extensive brain network. The reduced activity in all oculomotor regions, and increased activity in the temporo-occipital cortex could be due to the cognitively challenging nature of the antisaccade task requiring the non-selective recruitment of alternative neural networks. This is consistent with the notion of a ‘resource ceiling’ of available neurons, which had been reached in the AD group.
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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 | 0.001 | 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".