Attention to Form or Surface Properties Modulates Different Regions of Human Occipitotemporal Cortex
Bibliographic record
Abstract
We carried out 2 functional magnetic resonance imaging experiments to investigate the cortical mechanisms underlying the contribution of form and surface properties to object recognition. In experiment 1, participants performed same-different judgments in separate blocks of trials on pairs of unfamiliar "nonsense" objects on the basis of their form, surface properties (i.e., both color and texture), or orientation. Attention to form activated the lateral occipital (LO) area, whereas attention to surface properties activated the collateral sulcus (CoS) and the inferior occipital gyrus (IOG). In experiment 2, participants were required to make same-different judgments on the basis of texture, color, or form. Again attention to form activated area LO, whereas attention to texture activated regions in the IOG and the CoS, as well as regions in the lingual sulcus and the inferior temporal sulcus. Within these last 4 regions, activation associated with texture was higher than activation associated with color. No color-specific cortical areas were identified in these regions, although parts of V1 and the cuneus yielded higher activation for color as opposed to texture. These results suggest that there are separate form and surface-property pathways in extrastriate cortex. The extraction of information about an object's color seems to occur relatively early in visual analysis as compared with the extraction of surface texture, perhaps because the latter requires more complex computations.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".