Mapping the cerebral structural changes related to the multi-dimensional neuropsychiatric deficits in patients with ischemic thalamic stroke
Bibliographic record
Abstract
BACKGROUND: The thalamus serves as a central hub in the brain's neural network, playing a crucial role in sensory processing, cognitive functions, and emotional regulation. Although isolated thalamic strokes are relatively rare, their profound impact on cognitive and emotional outcomes highlights the importance of comprehensive investigation into thalamic involvement in post-stroke neuropsychiatric deficits. METHOD: This study enrolled 44 patients with first-ever unilateral thalamic ischemic stroke. All participants underwent MRI acquisition and neuropsychological evaluation, including Beijing version of the Montreal Cognitive Assessment (MoCA-BJ), Symbol Trails Test (STT), Stroop Color-Word Test (Stroop), Chinese Auditory Verbal Learning Test (CAVLT), Hamilton Anxiety Rating Scale (HAMA), and Hamilton Depression Rating Scale (HAMD). Gray matter volume (GMV) was extracted using CAT12 across 170 ROIs. Partial least squares (PLS) regression was applied to examine the association between GMV and 11 neuropsychological scores. Variable Importance in Projection (VIP) and loading analysis were conducted to identify key contributing regions. Additionally, Partial Least Squares-Discriminant Analysis (PLS-DA) was performed using 80 lesioned-side and 80 contralateral GMV features to distinguish lesion laterality, further validating the discriminative contribution of selected ROIs. RESULTS: PLS regression with three components achieved the optimal balance between explanatory power and model performance. Several cerebellar, temporal, and limbic structures showed high VIP scores and strong loadings, indicating their contribution to neuropsychological impairment. PLS-DA yielded satisfactory classification performance (mean AUC = 0.928 ± 0.093), highlighting robust lateralized structural differences. CONCLUSION: This study shows that structural alterations in cerebello-thalamo-cortical circuits are significantly associated with cognitive and emotional deficits following thalamic infarction. The integration of PLS and PLS-DA approaches provides robust evidence for identifying relevant biomarkers, Future research should validate these findings.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".