Disrupted Cortical Conductivity in Schizophrenia: TMS-EEG Study
Bibliographic record
Abstract
Schizophrenia is conceptualized as a failure of cognitive integration, and altered oscillatory properties of neurocircuits are associated with its symptoms. We hypothesized that abnormal characteristics of neural networks may alter functional connectivity and distort propagation of activation in schizophrenic brains. Thus, electroencephalography (EEG) responses to transcranial magnetic stimulation (TMS) of motor cortex were compared between schizophrenia and healthy subjects. There was no difference in the initial response. However, TMS-induced waves of recurrent excitation spreading across the cortex were observed in schizophrenia, while in healthy subjects the activation faded away soon after stimulation. This widespread activation in schizophrenia was associated with increased oscillatory activities in the proximal central leads and in fronto-temporo-parietal leads bilaterally. A positive correlation was found between increased TMS-induced cortical activation in gamma frequency and positive symptoms of schizophrenia, while negative symptoms were correlated with activation in theta and delta bands. We suggest that excessive activation in response to stimulation in schizophrenia brains may lead to abnormal propagation of the signal that could potentially result in aberrant activity in areas remote from the activation origin. This mechanism may account for the positive symptoms of schizophrenia and could worsen signal to noise deficits, jeopardizing adequate information processing with ensuing cognitive deficits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".