Effect of DLPFC rTMS on anhedonia and alpha asymmetry in depressed patients
Bibliographic record
Abstract
Anhedonia, a core symptom of depression, has been defined as the loss of pleasure or lack of reactivity to pleasurable stimuli. Considering the relevance of alpha asymmetry to MDD and anhedonia, we explored the effect of dorsolateral prefrontal cortex (DLPFC) stimulation on frontal and posterior EEG alpha asymmetry (FAA and PAA, respectively), in this exploratory investigation. 61 participants randomly received sham (n = 11), bilateral (BS; n = 25), or unilateral stimulation (US; n = 25) of the DLPFC. The Snaith-Hamilton Pleasure Scale (SHAPS) was administered. FAA and PAA were calculated by subtracting the natural log-transformed alpha power of the right (F8 or T6) from that of the left (F7 or T5) EEG channel. Furthermore, alpha peak was defined as the frequency where alpha power was at its maximum. BS and US both reduced anhedonia symptoms in the active compared to the sham group. Even non-responders in the BS group showed a decreased anhedonia. Interestingly in the BS group, only the patients who showed a right-lateralized FAA or PAA at baseline showed a reduction in anhedonia. However, in the US group, only patients with left-lateralized FAA or right-lateralized PAA showed a decrease in anhedonia. PAA at baseline predicted symptoms post treatment. Furthermore, a significant positive correlation between baseline alpha peak values and SHAPS scores post treatment were found in the BS group. PAA was a better predictor of anhedonia and reduction of depressive symptoms in both groups. BS may produce larger effects with regard to anhedonia.
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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 | 0.000 |
| 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".