Functional MRI for changed brain default mode network in ischemic stroke patients
Bibliographic record
Abstract
Objective To study the changed brain default mode network in chronic ischemic stroke patients by functional MRI.Methods Seventeen chronic ischemic stroke patients served as an ischemic stroke group and 22sex-and age-matched healthy subjects undergoing physical examination served as a control group in this study.Their functional MRI data and Montreal congnitive assessment(MoCA)and Mini-Mental State Examination(MMSE)scores were recorded.Default mode network was taken from the ventromedial prefrontal cortex,right posterior cingulate cortex and left posterior cingulate cortex to generate the default mode network mask.Voxel functional connectivity in the default mode network mask was calculated.Association of functional connectivity strength with MoCA and MMSE scores and infarction size were analyzed by Pearson correlation analysis.Results The functional connectivity of medial prefrontal cortex(MPFC)and posterior cingulate cortex/precuneus was significantly lower in ischemic stroke group than in control group(P0.05).The functional connectivity of MPFC in ischemic stroke group was positively associated with the MoCA score(r=0.619,P=0.008).Conclusion Default mode network is damaged before cognitive impairment following ischemic stroke,which is the initial factor for cognitive impairment.
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 | 0.001 | 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".