Heterogeneous Brain Dynamics Between Acute Cerebellar and Brainstem Infarction
Bibliographic record
Abstract
To evaluate the alterations in brain dynamics in patients suffering from brainstem or cerebellar infarctions and their potential associations with cognitive function. In this study, 37 patients were recruited who had acute cerebellar infarction (CI), 32 patients who had acute brainstem infarction (BsI), and 40 healthy controls (HC). Every participant had their resting-state electroencephalogram (EEG) data captured, and the EEG microstates were analyzed. The cognitive function was measured by the Neuropsychological Cognitive Scale including the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Boston Naming Test (BNT), the Digit Span Test (Digitspan), and the Symbol Digit Modalities Test (SDMT). Compared with the HC group, the transition probabilities from Microstate A(MsA) and MsD to MsC significantly decreased while the transition probabilities from MsA to MsD and from MsD to MsB significantly increased in the BsI group. By contrast, the CI group showed a significant increase in transition probabilities from MsA and MsD to MsC, whereas the transitions from MsD to MsB significantly decreased. Subgroup analysis within the CI group demonstrated that the CI patients with dizziness showed increased coverage and duration in MsB but decreased MsD occurrence than those of CI patients with vertigo. In addition, the BsI patients with pons infarction performed a decreased transition probability between MsA and MsD than those of BsI patients with medulla oblongata infarctions. Moreover, the changes in Microstate (Ms) were significantly correlated with cognitive scales in patients with CI or BsI. Altered brain dynamics in patients with CI or BsI suggested that disturbances in resting brain networks might play a functional role in the cognitive impairment of the CI or BsI patients. Through the use of microstate analysis, the dizziness or vertigo following CI could be differentiated. These findings may serve as a powerful tool in our future clinical practices.
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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) | 0.001 | 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".