Abnormal Functional Connectivity of Frontopolar Subregions in Treatment-Nonresponsive Major Depressive Disorder
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Approximately 30% of patients with major depressive disorder develop treatment-nonresponsive depression (TNRD); novel interventions targeting the substrates of this illness population are desperately needed. Convergent evidence from lesion, stimulation, connectivity, and functional neuroimaging studies implicates the frontopolar cortex (FPC) as a particularly important region in TNRD pathophysiology; regions functionally connected to the FPC, once identified, could present favorable targets for novel brain stimulation treatments. METHODS: We recently published a parcellation of the FPC based on diffusion tensor imaging data, identifying distinct medial and lateral subregions. Here, we applied this parcellation to resting-state functional magnetic resonance imaging scans obtained in 56 patients with TNRD and 56 matched healthy control subjects. RESULTS: In patients, the medial FPC showed reduced connectivity to the anterior midcingulate cortex and insula. The left lateral FPC showed reduced connectivity to the right lateral orbitofrontal cortex and increased connectivity to the fusiform gyri. In addition, TNRD symptom severity correlated significantly with connectivity of the left lateral FPC subregion to a medial orbitofrontal cortex region of the classical reward network. CONCLUSIONS: Taken together, these findings suggest that changes in FPC subregion connectivity may underlie several dimensions of TNRD pathology, including changes in reward/positive valence, nonreward/negative valence, and cognitive control domains. Nodes of functional networks showing abnormal connectivity to the FPC could be useful in generating novel candidates for therapeutic brain stimulation in TNRD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it