Attentional salience and the neural substrates of response inhibition in borderline personality disorder
Bibliographic record
Abstract
BACKGROUND: Impulsivity is a central symptom of borderline personality disorder (BPD) and its neural basis may be instantiated in a frontoparietal network involved in response inhibition. However, research has yet to determine whether neural activation differences in BPD associated with response inhibition are attributed to attentional saliency, which is subserved by a partially overlapping network of brain regions. METHODS: = 29) underwent functional magnetic resonance imaging while completing a novel go/no-go task with infrequent odd-ball trials to control for attentional saliency. Contrasts reflecting a combination of response inhibition and attentional saliency (no-go > go), saliency processing alone (oddball > go), and response inhibition controlling for attentional saliency (no-go > oddball) were compared between BPD and HC. RESULTS: Compared to HC, BPD showed less activation in the combined no-go > go contrast in the right posterior inferior and middle-frontal gyri, and less activation for oddball > go in left-hemispheric inferior frontal junction, frontal pole, superior parietal lobe, and supramarginal gyri. Crucially, BPD and HC showed no activation differences for the no-go > oddball contrast. In BPD, higher vlPFC activation for no-go > go was correlated with greater self-rated BPD symptoms, whereas lower vlPFC activation for oddball > go was associated with greater self-rated attentional impulsivity. CONCLUSIONS: Patients with BPD show frontoparietal disruptions related to the combination of response inhibition and attentional saliency or saliency alone, but no specific response inhibition neural activation difference when attentional saliency is controlled. The findings suggest a neural dysfunction in BPD underlying attention to salient or infrequent stimuli, which is supported by a negative correlation with self-rated impulsiveness.
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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".