A Review of Impaired Neuroplasticity in Schizophrenia Investigated with Non-invasive Brain Stimulation
Bibliographic record
Abstract
BACKGROUND: Several lines of evidence implicate dysfunctional neuronal plasticity in the pathophysiology of schizophrenia (SCZ). Aberrant glutamatergic and gamma amino--butyric acid neurotransmission are thought to underlie core cognitive deficits and negative symptoms of SCZ. Non-invasive brain stimulation (NIBS) allows for the in vivo study of cortical plasticity and excitability at the systems level of the human motor cortex. This review will focus on summarizing the available neurophysiological evidence for impaired motor cortical plasticity in SCZ assessed by NIBS. METHODS: A search of MEDLINE, Embase, and PubMed was performed on the use of NIBS techniques to investigate neuroplasticity in the motor cortex of SCZ patients. The relevant articles were summarized. CONCLUSION: Our review of the literature reveals evidence for disrupted neuroplasticity in SCZ and its close association to alterations in cortical inhibition and dysfunctional intracortical connectivity. Further investigations are required to elucidate the neurobiological mechanisms that underlie dysfunctional plasticity in SCZ in order to develop more targeted therapeutic interventions for SCZ patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".