Separate systems for transsaccadic comparisons of object orientation vs. identity in human cortex: An fMRI paradigm
Bibliographic record
Abstract
Recently, Dunkley et al. (Cortex, 2016) showed that extrastriate cortex and right supramarginal gyrus (SMG) were modulated by transsaccadic changes in the orientation of a Gabor-like patch. However, this result did not generalize to other features: in a similar fMRI design, Baltaretu et al. (J Vis, 2016) found that transsaccadic changes in spatial frequency activated medial occipito-parietal and middle frontal gyrus (MFG). Based on this, we hypothesized that the fundamental difference between these results was the detection of transsaccadic changes in object orientation vs. identity. To test this, we used a double-dissociation fMRI task. Participants were asked to fixate on a small cross 15.4° left or right of centre, where an object was subsequently presented (rectangle, barrel-shaped object, or hourglass-shaped object), oriented at ±45° from vertical. After this, the fixation cross either remained in the same position (Fixate condition) or shifted to the other side (Saccade condition). Then, either the same object would appear with the opposite orientation (Orientation change condition) or one of the other two objects would appear at the same orientation (Identity change condition). Participants were required to indicate whether identity or orientation had changed using a button press. Preliminary analysis in seven participants, using an RFX GLM and a (Saccade Orientation > Identity) > (Fixation Orientation > Identity) contrast, showed that right SMG, inferior occipital gyrus, and left somatosensory and superior parietal lobe were significantly modulated by transsaccadic changes in object orientation. In contrast, right MFG, left primary motor cortex, and bilateral precuneus were significantly modulated by transsaccadic changes in object identity. These results support our hypothesis that separate anterior lateral (SMG) vs. posterior medial (precuneus) parietal nodes, respectively, are involved in the monitoring of object orientation versus identity across separate visual fixations.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".