Resting-State Neuroimaging Studies: A New Way of Identifying Differences and Similarities among the Anxiety Disorders?
Bibliographic record
Abstract
This review examines recent functional neuroimaging research of resting-state regional connectivity between brain regions in anxiety disorders. Studies compiled in the PubMed- National Center for Biotechnology Information database targeting resting-state functional connectivity in anxiety disorders were reviewed. Diagnoses included posttraumatic stress disorder (PTSD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), obsessive-compulsive disorder (OCD), panic disorder (PD), and specific phobia (SP). Alterations to network connectivity were demonstrated in PTSD, GAD, SAD, OCD, and PD in several resting-state investigations. Differences from control subjects were primarily observed in the default mode network within PTSD, SAD, and OCD. Alterations within the salience network were observed primarily in PTSD, GAD, and SAD. Alterations in corticostriatal networks were uniquely observed in OCD. Finally, alterations within somatosensory networks were observed in SAD and PD investigations. Resting-state studies involving SPs as a primary diagnosis (with or without comorbidities) were not generated during the literature search. The emerging use of resting-state paradigms may be an effective method for understanding associations between anxiety disorders. Targeted studies of PD and SPs, meta-analyses of the studies conducted to date, and studies of the impact of specific comorbid presentations, are recommended future research directions.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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".