Effects of visual attention modulation on dynamic functional connectivity during own-face viewing in body dysmorphic disorder
Bibliographic record
Abstract
Abstract Background In individuals with body dysmorphic disorder (BDD), selective attention biases and aberrant visual scanning patterns may cause imbalances in global vs. detailed visual processing, contributing to perceptual distortions for appearance. The mechanistic effects of modifying visual attention on brain function in BDD, which may be critical to developing perceptual-based treatments, have not been explored. This study tested the effects of visual-attention modulation on dorsal and ventral visual stream activation and connectivity, and eye behaviors. Methods We acquired functional magnetic resonance imaging data in 37 unmedicated adults with BDD and 30 controls. Participants viewed their faces under two conditions: a) unconstrained (naturalistically), and b) holding their gaze on the center of the image (visual-attention modulation), monitored with an eye-tracking camera. We analyzed activation and dynamic effective connectivity in dorsal and ventral visual streams and visual fixation duration. Results Visual-attention modulation resulted in longer fixation duration and reduced activation in dorsal and ventral visual streams in both groups compared with naturalistic viewing. Longer fixation duration was associated with greater effective connectivity from V1 to early dorsal visual stream during the second naturalistic viewing, across groups. During naturalistic viewing, there was greater V1 to early dorsal visual stream connectivity after, compared with before, visual-attention modulation. Conclusions When viewing one’s face, longer visual fixation may confer greater communication in dorsal visual system, facilitating global/holistic visual processing. The finding that reduction in visual scanning while viewing one’s face results in persistent effects during unconstrained viewing has implications for perceptual retraining treatment design for BDD.
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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) | 0.001 | 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".