Reducing magnocellular processing of various motion trajectories tests single process theories of visual position perception
Bibliographic record
Abstract
Spatial projection and temporal integration are two prominent theories of visual localization for moving stimuli which gain most of their explanatory power from a single process. Spatial projection theories posit that a moving stimulus' perceived position is projected forwards in order to compensate for processing delays (Eagleman & Sejnowski, 2007; Nijhawan, 2008). Temporal integration theories (Krekelberg & Lappe, 2000) suggest that an averaging over positions occupied by the moving stimulus for a period of time is the dominant process underlying perception of position. We found that when magnocellular (M) pathway processing was reduced, there were opposite effects on localization judgments when a smooth, continuous trajectory was used, compared to when the moving object suddenly appeared, or suddenly reversed direction. The flash-lag illusion was decreased for the continuous trajectory, but increased for the onset and reversal trajectories. This cross-over interaction necessitates processes additional to those proposed by either the spatial projection or temporal integration theories in order to explain the perception of the position of moving stimuli across all our conditions. Differentiating our onset trajectory conditions from a Fröhlich illusion, in a second experiment, we found a null Fröhlich illusion under normal luminance-defined conditions, significantly smaller than the corresponding flash-lag illusion, but significantly increased when M processing was reduced. Our data are most readily accounted for by Kirschfeld and Kammer's (1999) backward-inhibition and focal attention theory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".