The persistence of global form (Part II): Figure-specific fMRI activity in V1
Bibliographic record
Abstract
In Part I we showed persistence-related activity in V1. Was this activity localized to the retinotopic location of the figure? If so, this would suggest that higher-tier visual areas facilitate the representation of figure-specific visual information in V1.We measured fMRI activity in V1 during the visual persistence of global forms. We used global forms of three different sizes in two different experiments: an eccentricity-localizer and the main persistence experiment. The purpose of the eccentricity-localizer was to identify three retinotopic locations (ROIs) in V1, each of which would correspond to the eccentricity of the figures used in the persistence experiment. The purpose of the persistence experiment was to assess the relationship between persistence-related fMRI activity and figure size (eccentricity). We observed a sustained increase in fMRI activity (persistence) in ROIs that corresponded to the size of a given figure. Activity was reduced in the remaining two ROIs, indicating suppression. That is, we observed fMRI responses retinotopically such that increases in fMRI activity corresponding to a maintained representation of figure were delineated from background-specific decreases in fMRI activity (related to the suppression of the background). Part I suggested that higher-tier visual areas influence activity in V1 via feedback. The results presented here suggest that this influence is specific to the retinotopic location of the figure, which explains why previous studies (prior to Part I) failed to observe persistence in V1. These studies used large early visual ROIs that included both sustained fMRI activity (persistence) and reduced fMRI activity (suppression), which combined to produce a null effect. More importantly, our present results are consistent with a recurrent processing account of figure-ground segregation that predicts which image regions are preferentially perceived as figure or as background.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".