Aberrant connectivity of resting-state networks in borderline personality disorder
Bibliographic record
Abstract
BACKGROUND: Several functional neuroimaging studies have reported regionally abnormal activation of the frontal cortex in individuals with borderline personality disorder (BPD) during cognitive and affective task performance. However, little is known about neural function in individuals with BPD during the resting state. Using functional magnetic resonance imaging (fMRI), this study investigated the functional connectivity of prefrontal and limbic networks in patients with BPD. METHODS: Between January 2009 and March 2010, we investigated patients with BPD according to DSM-IV criteria and healthy controls by means of resting-state fMRI. The data were analyzed using a spatial group independent component analysis, and random effects t tests were used to compare spatial components between groups (p < 0.005, uncorrected). RESULTS: There were 17 women with BPD and 17 female healthy controls enrolled in this study. Within a network comprising cortical midline regions ("default mode network"), patients with BPD showed an increase in functional connectivity in the left frontopolar cortex (FPC) and the left insula, whereas decreased connectivity was found in the left cuneus. Within a network comprising predominantly right lateral prefrontal and bilateral parietal regions, patients with BPD showed decreased connectivity of the left inferior parietal lobule and the right middle temporal cortex compared with healthy controls. Two networks comprising lateral prefrontal and cingulate regions did not exhibit significant between-group differences. We found correlations between functional connectivity of the FPC and measures of impulsivity as well as between connectivity of the insula/cuneus and dissociation tension. LIMITATIONS: Co-occurrent axis I disorders and medication use in this sample of patients with BPD have to be considered as potential limitations. CONCLUSION: These data suggest that abnormal functional connectivity of temporally coherent resting-state networks may underlie certain symptom clusters in patients with BPD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".