Evaluation of short interval cortical inhibition and intracortical facilitation from the dorsolateral prefrontal cortex in patients with schizophrenia
Bibliographic record
Abstract
Abstract GABAergic and glutamatergic dysfunction in the dorsolateral prefrontal cortex (DLPFC) are thought to be the core pathophysiological mechanisms of schizophrenia. Recently, we have established a method to index these functions from the DLPFC using the paired transcranial magnetic stimulation (TMS) paradigms of short interval intracortical inhibition (SICI) and facilitation (ICF) combined with electroencephalography (EEG). In this study, we aimed to evaluate neurophysiological indicators related to GABA A and glutamate receptor-mediated functions respectively from the DLPFC in patients with schizophrenia using these paradigms, compared to healthy controls. Given that these activities contribute to cognitive functions, the relationship between the TMS-evoked potential (TEP) modulations by SICI/ICF and cognitive/clinical measures were explored. Compared to controls, patients showed reduced inhibition in P60 (t 22 = −4.961, p < 0.0001) by SICI and reduced facilitation in P60 (t 22 = 5.174, p < 0.0001) and N100 (t 22 = 3.273, p = 0.003) by ICF. In patients, the modulation of P60 by SICI was correlated with the longest span of the Letter-Number Span Test (r = −0.775, p = 0.003), while the modulation of N100 by ICF was correlated with the total score of the Positive and Negative. Syndrome Scale (r = 0.817, p = 0.002). These findings may represent the pathophysiology, which may be associated with prefrontal GABA A and glutamatergic dysfunctions, in the expression of symptoms of schizophrenia.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".