Altered Regional Brain Spontaneous Activity and Functional Connectivity in Patients of Non-Acute Subcortical Stroke With versus Without Cognitive Impairment: A Resting-State fMRI Study.
Bibliographic record
Abstract
Abstract The reasons why not all stroke survivors have cognitive dysfunction are unclear. We hypothesize that resting-state fMRI (rs-fMRI) will reveal differences in regional brain spontaneous activity and functional connectivity (FC) in stroke patients with and without cognitive impairment. We classified 62 first-ever non-acute subcortical stroke patients into two groups: post-stroke with abnormal cognition (PSAC) and with normal cognition (PSNC). Rs-MRI was utilized to assess regional homogeneity (ReHo) in 32 PSAC, 30 PSNC, and 62 age- and sex-matched healthy controls. We set regions with significant alteration within stroke groups as regions of interest and performed the seed-based whole brain FC analysis. A partial correlation analysis examined the relationship between altered ReHo or FC and Montreal Cognitive Assessment (MoCA) scores. Compared to PSNC, PSAC had decreased ReHo in the left gyrus rectus (REC) and increased ReHo in cerebellar lobules (CBL) left IX and right VIII, while FC decreased in PSAC between bilateral REC, and between the left REC and the middle temporal gyrus (MTG). In all stroke patients, ReHo value in the left REC correlated positively and in the CBL correlated negatively with MoCA. All the significant FC correlated with MoCA positively. Regional brain spontaneous activity and FC alteration in the REC, MTG, and cerebellum may be associated with cognitive impairment following non-acute subcortical stroke.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".