Dysfunctional Neural Plasticity in Patients With Schizophrenia
Bibliographic record
Abstract
CONTEXT: Neural plasticity in the human cortex involves a reorganization of synaptic connections in an effort to adapt to a changing environment. In schizophrenia, dysfunctional neural plasticity has been proposed as a key pathophysiological mechanism. OBJECTIVE: To evaluate neural plasticity in unmedicated and medicated patients with schizophrenia compared with healthy subjects. DESIGN: Neural plasticity can be evaluated from the motor cortex in healthy subjects using transcranial magnetic stimulation through a paradigm known as use-dependent plasticity. This paradigm involves several steps: (1) measuring the spontaneous direction of transcranial magnetic stimulation-induced thumb movements; (2) training subjects to practice thumb movements opposite to this baseline direction for 30 minutes; and (3) measuring the direction of transcranial magnetic stimulation-induced thumb movement after training. Previous experiments have shown that in healthy subjects, posttraining transcranial magnetic stimulation-induced movements occur in a vector commensurate with the practiced movements, which may be associated with time-limited reorganization of motor circuits. SETTING: All of the participants were recruited and evaluated at the Centre for Addiction and Mental Health. PARTICIPANTS: Fourteen medicated and 6 unmedicated patients with schizophrenia and 20 healthy subjects were recruited. MAIN OUTCOME MEASURE: It was anticipated that patients with schizophrenia would demonstrate attenuated motor reorganization in the direction of training. RESULTS: Both medicated and unmedicated patients with schizophrenia demonstrated significantly reduced motor reorganization compared with healthy subjects. CONCLUSIONS: It is possible that in schizophrenia, these deficits in neural plasticity are related to disturbances of gamma-aminobutyric acid, N-methyl-D-aspartate neurotransmission, or dopamine that may potentially account for the aberrant motor performance of these patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".