Cognitive and emotional effects of bilateral prefrontal anodal tDCS and high-frequency tRNS in schizophrenia: a randomized sham-controlled study
Bibliographic record
Abstract
Abstract Cognitive deficits in schizophrenia significantly hinder functional outcomes and often remain unresponsive to conventional treatments. While initial evidence suggested potential pro-cognitive effects of electrical brain stimulation in schizophrenia, recent meta-analyses have not supported these findings, warranting further investigation on intervention optimization. This sham-controlled crossover study explored cognitive and emotional effects of bilateral dorsolateral prefrontal cortex (DLPFC) anodal transcranial direct current stimulation (tDCS) and high-frequency transcranial random noise stimulation (tRNS) in schizophrenia. Thirty-six male patients with schizophrenia participated in a crossover trial, receiving three sessions (tDCS, tRNS, sham) in counterbalanced order with one-week intervals. tDCS and tRNS sessions involved 20-minute 2 mA anodal stimulation (tDCS) and 2 mA 100–640 Hz random noise stimulation targeting the left and right DLPFCs (F3-F4) with two extracephalic return electrodes. Executive functions (working memory, planning) were assessed during stimulation, and emotional changes were measured with the Positive and Negative Affect Schedule (PANAS) pre- and post-stimulation. Side effects and blinding efficacy were evaluated. Both bilateral tDCS and tRNS significantly improved executive functions (i.e., problem solving) compared to sham, with tRNS additionally enhancing working memory accuracy and strategy score. Both interventions increased positive affect and reduced negative affect after the intervention, with tRNS showing greater enhancement of positive emotions. Reduced negative affect correlated with better executive functions during tRNS. Side effects were minimal, and blinding was effective for the sham condition. Bilateral DLPFC anodal tDCS and high-frequency tRNS show promise as adjunctive treatments for schizophrenia, especially for cognitive deficits, with broader cognitive and emotional benefits observed with tRNS.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".