The neural transfer effect of working memory training to enhance hedonic processing in individuals with social anhedonia
Bibliographic record
Abstract
Anhedonia, the diminished ability to experience pleasure, is a challenging negative symptom in patients with schizophrenia and can be observed in at-risk individuals with schizotypy. Deficits in hedonic processing have been postulated to be related to decreased motivation to engage in potentially rewarding events. It remains unclear whether non-pharmacological interventions, such as cognitive training, could improve anhedonia. The present study aimed to examine the neural mechanism for alleviating hedonic deficits with working memory (WM) training in individuals with social anhedonia. Fifteen individuals with social anhedonia were recruited and received 20 sessions of training on a dual n-back task, five sessions a week. Functional imaging paradigms of the Monetary Incentive Delay (MID) and the Affective Incentive Delay (AID) tasks were administered both before and after the training to evaluate the neural transfer effects on hedonic processing ability. Enhanced brain activations related to anticipation were observed at the anterior cingulate cortex, the left dorsal striatum and the left precuneus with the AID task, and at the dorsolateral prefrontal cortex and the supramarginal gyrus with the MID task. The present findings support that WM training may improve monetary-based and affective-based hedonic processing in individuals with social 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".