Visual Distraction Disrupts Category-tuned Attentional Filters in Ventral Visual Cortex
Bibliographic record
Abstract
Our behavioral goals shape how we process information via attentional filters that prioritize goal-relevant information, dictating both where we attend and what we attend to. When something unexpected or salient appears in the environment, it captures our spatial attention. Extensive research has focused on the spatiotemporal aspects of attentional capture, but what happens to concurrent nonspatial filters during visual distraction? Here, we demonstrate a novel, broader consequence of distraction: widespread disruption to filters that regulate category-specific object processing. We recorded fMRI while participants viewed arrays of face/house hybrid images. On distractor-absent trials, we found robust evidence for the standard signature of category-tuned attentional filtering: greater BOLD activation in fusiform face area during attend-faces blocks and in parahippocampal place area during attend-houses blocks. However, on trials where a salient distractor (white rectangle) flashed abruptly around a nontarget location, not only was spatial attention captured, but the concurrent category-tuned attentional filter was disrupted, revealing a boost in activation for the to-be-ignored category. This disruption was robust, resulting in errant processing-and early on, prioritization-of goal-inconsistent information. These findings provide a direct test of the filter disruption theory: that in addition to disrupting spatial attention, distraction also disrupts nonspatial attentional filters tuned to goal-relevant information. Moreover, these results reveal that, under certain circumstances, the filter disruption may be so profound as to induce a full reversal of the attentional control settings, which carries novel implications for both theory and real-world perception.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".