Reduced deactivation in reward circuitry and midline structures during emotion processing in borderline personality disorder
Bibliographic record
Abstract
OBJECTIVES. Borderline personality disorder (BPD) is characterized by a pervasive affective dysregulation. While recent imaging studies demonstrated the neural correlates of abnormal emotion processing in BPD and recently one study reported alterations of the reward circuit in this patient group, the exact neural mechanisms underlying the impact of abnormal emotion on reward behavior remain unclear. METHODS. We therefore conducted an fMRI study in healthy controls and BPD patients to investigate the modulation of the anticipation of reward by simultaneously presented emotional pictures. RESULTS. BPD patients revealed a disturbed differentiation between reward and non-reward anticipation in the bilateral pregenual anterior cingulate cortex if a positive or negative emotional picture is presented simultaneously. In the ventral striatum and the bilateral ventral tegmental area, BPD patients and healthy controls are able to differentiate between reward and non-reward even under emotional stimulation, but BPD patients show a reduced deactivation in the above mentioned regions compared to healthy controls. CONCLUSIONS. Altered emotion processing in BPD patients is likely to affect the reward system. More basic deficits in reward circuitry and other midline regions' level of resting state activity may contribute to this effect.
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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) | 0.002 | 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".