Modulation of Cortical-Limbic Pathways in Major Depression
Bibliographic record
Abstract
BACKGROUND: Functional imaging studies of major depressive disorder demonstrate response-specific regional changes following various modes of antidepressant treatment. OBJECTIVE: To examine changes associated with cognitive behavior therapy (CBT). METHODS: Brain changes underlying response to CBT were examined using resting-state fluorine-18-labeled deoxyglucose positron emission tomography. Seventeen unmedicated, unipolar depressed outpatients (mean +/- SD age, 41 +/- 9 years; mean +/- SD initial 17-item Hamilton Depression Rating Scale score, 20 +/- 3) were scanned before and after a 15- to 20-session course of outpatient CBT. Whole-brain, voxel-based methods were used to assess response-specific CBT effects. A post hoc comparison to an independent group of 13 paroxetine-treated responders was also performed to interpret the specificity of identified CBT effects. RESULTS: A full course of CBT resulted in significant clinical improvement in the 14 study completers (mean +/- SD posttreatment Hamilton Depression Rating Scale score of 6.7 +/- 4). Treatment response was associated with significant metabolic changes: increases in hippocampus and dorsal cingulate (Brodmann area [BA] 24) and decreases in dorsal (BA 9/46), ventral (BA 47/11), and medial (BA 9/10/11) frontal cortex. This pattern is distinct from that seen with paroxetine-facilitated clinical recovery where prefrontal increases and hippocampal and subgenual cingulate decreases were seen. CONCLUSIONS: Like other antidepressant treatments, CBT seems to affect clinical recovery by modulating the functioning of specific sites in limbic and cortical regions. Unique directional changes in frontal cortex, cingulate, and hippocampus with CBT relative to paroxetine may reflect modality-specific effects with implications for understanding mechanisms underlying different treatment strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".