Comparing properties of the spatial integration of local signals into perceived global structure
Bibliographic record
Abstract
Sensitivity to global structure was investigated using a stimulus containing perceived vertical or horizontal bands generated by superimposing a pair of narrowband noise images modulated by two out of phase periodic functions (Watson & Eckert, 1994 JOSA, A(11)496-505). We probed a moving version of the stimulus in which components making up the pair of noise images have opposite directions of motion and then a static analogue in which the pair of components have orthogonal directions of carrier orientation. The stimuli contain local signals characterised by the carrier frequency which have to be integrated over a larger spatial extent determined by the modulation frequency, which we therefore considered a global parameter. We obtained threshold luminance and modulator contrast sensitivities using a two interval 2AFC psychophysical detection task. We found that the motion stimulus showed band-pass tuning of the ratio of carrier to modulation frequency with a peak corresponding to an optimum sensitivity where the modulator is of a scale of ten times the carrier. This optimal sensitivity was found to be scale invariant over a range of retinal image sizes varied up to a factor of 10 with a fixed number of modulator cycles. This result suggests a coupling between the spatial frequency of local motion detection stages and the integration process, which happen at a larger scale. In the case of the static orientation stimulus, a much broader tuning was found, which showed an optimum at a higher ratio (<50). Observers were more sensitive to carrier orientation in the cardinal axes that the obliques, with the broader optimum ratio also shifted slightly in the two cases. Our results suggest that there is substantial spatial pooling of local signals which exhibits different properties for moving stimuli compared with orientation stimuli.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".