Pathoconnectomics of cognitive impairment in small vessel disease: A systematic review
Bibliographic record
Abstract
INTRODUCTION: Cerebral small vessel disease (CSVD) is a highly prevalent condition associated with diffuse ischemic damage and cognitive dysfunction particularly in executive function and attention. Functional brain imaging studies can reveal mechanisms of cognitive impairment in CSVD, although findings are mixed. METHODS: A systematic review integrating findings from functional magnetic resonance imaging and electroencephalography in CSVD is involved. RESULTS: CSVD damages long-range white matter tracts connecting nodes within distributed brain networks. It also disrupts frontosubcortical circuits and cholinergic fiber tracts mediating attentional processes. These changes, illustrated within a model of network dynamics, synergistically relate to neurodegenerative pathology contributing to dementia. DISCUSSION: The effects of CSVD on attention and executive functioning are best understood within a network model of cognition as revealed by functional neuroimaging. Analysis of network function in CSVD can improve characterization of disease severity and treatment effects, and it can inform theoretical models of brain function.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".