How do resting state changes in depression translate into psychopathological symptoms? From ‘Spatiotemporal correspondence’ to ‘Spatiotemporal Psychopathology’
Bibliographic record
Abstract
PURPOSE OF REVIEW: To review the recent findings in resting-state activity in major depressive disorder (MDD) and link them to psychopathological symptoms. RECENT FINDINGS: MDD shows changes in resting state functional connectivity (rsFC) mainly within the default-mode network with a focus on especially the perigenual anterior cingulate cortex. rsFC in perigenual anterior cingulate cortex is abnormally high in MDD and decreased in the lateral prefrontal cortex with the central executive network (CEN). rsFC in other networks like the salience network, including the insula, amygdala, and supragenual anterior cingulate cortex and the sensorimotor network is also affected in MDD. SUMMARY: Resting-state activity in MDD shows abnormal topographical and spatiotemporal pattern. The spatiotemporal alterations in resting state may translate into corresponding spatiotemporal changes underlying the sensorimotor, affective, and cognitive functions, and thus, the various symptoms. Such spatiotemporal correspondence between resting state changes and psychopathological symptoms may make necessary the development of what I describe as 'Spatiotemporal Psychopathology'.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".