Functional connectivity between the amygdala and prefrontal cortex in medication-naive individuals with major depressive disorder
Bibliographic record
Abstract
BACKGROUND: Convergent evidence suggests dysfunction within the prefrontal cortex (PFC) and amygdala, important components of a neural system that subserves emotional processing, in individuals with major depressive disorder (MDD). Abnormalities in this system in the left hemisphere and during processing of negative emotional stimuli are especially implicated. In this study, we used functional magnetic resonance imaging (fMRI) to investigate amygdala-PFC functional connectivity during emotional face processing in medication-naive individuals with MDD. METHODS: Individuals with MDD and healthy controls underwent fMRI scanning while processing 3 types of emotional face stimuli. We compared the strength of functional connectivity from the amygdala between the MDD and control groups. RESULTS: Our study included 28 individuals with MDD and 30 controls. Decreased amygdala-left rostral PFC (rPFC) functional connectivity was observed in the MDD group compared with controls for the fear condition (p < 0.05, corrected). No significant differences were found in amygdala connectivity to any cerebral regions between the MDD and control groups for the happy or neutral conditions. LIMITATIONS: All participants with MDD were experiencing acute episodes, therefore the findings could not be generalized to the entire MDD population. CONCLUSION: Medication-naive individuals with MDD showed decreased amygdala-left rPFC functional connectivity in response to negative emotional stimuli, suggesting that abnormalities in amygdala-left rPFC neural circuitry responses to negative emotional stimuli might play an important role in the pathophysiology of MDD.
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How this classification was reachedexpand
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 | 0.002 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".