Posterior parietal cortex damage causes endpoint biases relative to the visual target during anti-saccades
Bibliographic record
Abstract
Anti-saccades are eye movements in which the saccade is executed in the opposite direction of a visual target. Because the visual target and saccade goal are decoupled, it has been suggested that competition between the two locations occurs and needs to be resolved. The posterior parietal cortex (PPC) has been implicated in anti-saccade production. To gain insight into the processes of competition and saccade planning within the PPC, we investigated anti-saccade performance in three patients with PPC lesions and 21 age-matched controls on three different anti-saccades paradigms: 90° away across hemifields, 90° away within the same hemifield and 180° away (diagonally opposite). Specifically, we examined how saccade endpoints demonstrated the extent of competition, i.e., the visual target’s interference with anti-saccade programming and execution processes. We observed that anti-saccade endpoints showed bias toward the visual target in all of control participants, and this appeared exacerbated in two of our patients. Our third patient showed, instead, a strong bias away from the visual target. Modified t-tests revealed a significant difference between two of patients and their controls in terms of amplitude relative to the visual target for the across and classic conditions, and no significant difference for the within condition. However, one patient showed no significant difference compared to controls across all conditions. Overall, we showed some evidence of a stronger bias relative to the visual target in our patients. This suggests that the PPC may contribute to competition resolution between visual target and saccade goal during anti-saccades.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".