Amplitude of low frequency fluctuation in female depression patients: a resting-state functional magnetic resonance imaging study
Bibliographic record
Abstract
Objective To explore energy feature of the spontaneous neural activity in young female depressive patients, and its correlation to the severity of depressive symptoms. Methods Fourteen female depressive patients and 18 healthy controls were scanned with 3.0 T MRI scanner. The difference with amplitude of low frequency fluctuation (ALFF) between both groups was compared with the t-test, and the correlation analysis between ALFF of brain regions with significant difference and the severity of depressive symptoms was conducted. Results Compared with healthy group, the depression group showed significantly increased ALFF in the right cerebellum anterior lobe (Montreal Neurological Institute(MNI) coordinates (x,y,z):39, -54, -36; k=20; t=3.678，P<0.05), and decreased ALFF in the left posterior cingulate (MNI coordinates (x,y,z):-6, -45, 15; k=18) and the left superior parietal lobule (MNI coordinates (x,y,z): -21, -78, 48; k=20；t=-3.967,-3.669; both P<0.05; corrected by Alphasim). The ALFF in the right cerebellum anterior lobe was positively correlated to the number of depressive episodes (r=0.607, P=0.021), and negatively correlated to the HAMD17 total score and cognitive disturbance score (r=-0.595，P=0.025; r=-0.542，P=0.045, respectively). Conclusion Abnormal brain activity could emerge in female depressive patients during resting-state, the level of ALFF may be associated with severity of depressive symptoms and cognitive disturbance. Key words: Depression; Magnetic resonance imaging; Amplitude of low frequency fluctuation
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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".