Maladaptive Self-Focused Attention and Default Mode Network Connectivity: A Transdiagnostic Investigation Across Social Anxiety and Body Dysmorphic Disorders
Bibliographic record
Abstract
Abstract Background Maladaptive self-focused attention (SFA) is a bias toward internal thoughts, feelings, and physical states. Despite its role as a core maintaining factor of symptoms in cognitive theories of social anxiety and body dysmorphic disorders, studies have not examined its neural basis. We hypothesized that maladaptive SFA would be associated with hyperconnectivity in the default mode network (DMN) in self-focused patients with these disorders. Methods Thirty patients and 28 healthy individuals were eligible and scanned. Eligibility was determined by scoring greater than 1SD or below 1SD of the Public Self-Consciousness Scale normative mean, respectively, for each group. Fifteen patients had primary social anxiety disorder and 15 had primary body dysmorphic disorder. Seed-to-voxel functional connectivity was computed using a DMN posterior cingulate cortex (PCC) seed. Results Patients (regardless of diagnosis) showed reduced functional connectivity of the PCC with several brain regions, including the bilateral superior parietal lobule (SPL), bilateral insula, cingulate cortex, and postcentral gyrus, compared to controls. PCC-SPL connectivity was inversely correlated with maladaptive SFA in patients but was not associated with social anxiety or body dysmorphic symptom severity, depression severity, or rumination. There was no evidence of increased functional connectivity within the DMN in patients compared to controls. Conclusions As the SPL is part of the dorsal attention network, which is typically activated during tasks requiring externally-oriented attention, abnormal PCC-SPL connectivity in patients may reflect difficulty shifting between internal versus external attention, and may represent a transdiagnostic neural marker of maladaptive SFA that could be targeted in interventions. Clinical Trials Registration ClinicalTrials.gov Identifier: NCT02808702 https://clinicaltrials.gov/ct2/show/NCT02808702
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".