Perisaccadic Perception of Visual Space in People with Schizophrenia
Bibliographic record
Abstract
Corollary discharge signals are found in the nervous systems of many animals, where they serve a large variety of functions related to the integration of sensory and motor signals. In humans, an important corollary discharge signal is generated by oculomotor structures and communicated to sensory systems in concert with the execution of each saccade. This signal is thought to serve a number of purposes related to the maintenance of accurate visual perception. The properties of the oculomotor corollary discharge can be probed by asking subjects to localize stimuli that are flashed briefly around the time of a saccade. The results of such experiments typically reveal large errors in localization. Here, we have exploited these well-known psychophysical effects to assess the potential dysfunction of corollary discharge signals in people with schizophrenia. In a standard perisaccadic localization task, we found that, compared with controls, patients with schizophrenia exhibited larger errors in localizing visual stimuli. The pattern of errors could be modeled as an overdamped corollary discharge signal that encodes instantaneous eye position. The dynamics of this signal predicted symptom severity among patients, suggesting a possible mechanistic basis for widely observed behavioral manifestations of schizophrenia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".