Parietal Mechanisms for Transsaccadic Spatial Frequency Perception: An fMRI Study
Bibliographic record
Abstract
Abstract Posterior parietal cortex (PPC), specifically right supramarginal gyrus, is involved in transsaccadic memory of object orientation for both perception and action. Here, we investigated whether PPC is involved in transsaccadic memory of other features, namely spatial frequency. We employed a functional magnetic resonance imaging paradigm where participants briefly viewed a grating stimulus with a specific spatial frequency that later reappeared with the same or different frequency, after a saccade or continuous fixation. Post-saccadic frequency modulation activated a region in the right hemisphere spanning medial PPC (ventral precuneus) and posterior cingulate cortex. Importantly, the site of peak precuneus activation showed saccade-specific feature modulation (compared to fixation) and task-specific saccade modulation (compared to a saccade localizer task). Psychophysiological interaction analysis revealed functional connectivity between this precuneus site and the precentral gyrus (M1), lingual gyrus (V1/V2), and medial occipitotemporal sulcus. This differed from the transsaccadic orientation network, perhaps because spatial frequency signaled changes in object identity . Overall, this experiment supports a general role for PPC in transsaccadic vision, but suggests that different networks are employed for specific features.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".