Neuroplasticity-Based Brain Stimulation Interventions in the Study and Treatment of Schizophrenia: A Review
Bibliographic record
Abstract
We reviewed novel brain stimulation approaches that modify neuroplasticity and are used in the treatment and study of schizophrenia. We searched PubMed and Scholars Portal using search terms related to schizophrenia, brain stimulation, and neuroplasticity. Various brain stimulation approaches simulating a range of experimental protocols that induce synaptic long-term potentiation or depression have been developed. By far, repetitive transcranial magnetic stimulation (rTMS) has been the most widely used in the field of schizophrenia. Its application has been associated with mixed results in treating treatment-resistant symptoms and cognitive deficits associated with schizophrenia. Compared to the other approaches, rTMS is probably the least similar to plasticity-inducing cellular paradigms. Other approaches, such as paired associative stimulation, theta-burst stimulation, and transcranial direct current stimulation, are in their incipient stages in the study and treatment of schizophrenia, with promising early results. Numerous brain stimulation approaches have been developed to treat resistant dimensions of schizophrenia. Notwithstanding some promising reports, optimization of the methods and large randomized controlled trials are still needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".