Simulating oculomotor inhibition of return with a two-dimensional dynamic neural field model of the superior colliculus
Bibliographic record
Abstract
Sensory adaptation and oculomotor inhibition of return (IOR) have been extensively modeled using a onedimensional dynamic neural field (DNF) model of the superior colliculus (SC). However, a great deal of paradigms are incapable of being simulated in a single dimension, limiting the generality of previous implementations. Here, we expand on previous work by implementing the inhibitory cueing mechanisms underlying IOR in a two-dimensional DNF. With such a model, we were able to reproduce the results reported in our previous work, validating the use of two-dimensional DNF models in future theoretical investigations. We discuss a number of new findings in the literature that should be simulated in two dimensions to further our understanding of inhibitory cueing mechanisms and saccade dynamics, such as the center of gravity effect of IOR.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".