Analysis of functional brain networks in patients with subcortical vascular cognitive impairment
Bibliographic record
Abstract
Objective To investigate the change of the resting-state brain function of patients with Subcortical Vascular Cognitive Impairment (SVCI) by complex network theory which is based on the graph theory and determine the possible imaging characteristics. Methods 34 patients with SVCI and 22 controls were recruited. All of them were interviewed using a set of neuropsychological tests including mini-mental state examination(MMSE) and Montreal cognitive assessment(MoCA), and were subject to the MRI scan. Based on the acquired data, functional network were constructed for the subsequent analysis. Results Both of the two groups showed small-world attributes. The node degree of SVCI group was significantly decreased in the left triangular part of inferior frontal gyrus(-45.58, 29.91, 13.99) and left lingual gyrus(-14.62, -67.56, -4.63), and significantly increased in the right precentral gyrus(41.37, 8.21, 52.09), right rolandic operculum(52.65, -6.25, 14.63), left superior temporal gyrus(-53.16, -20.68, 7.13), right superior temporal gyrus(58.15, -21.78, 6.80) and left middle temporal gyrus(-55.52, -33.80, -2.20). The betweenness centrality of the SVCI group significantly decreased in the left triangular part of inferior frontal gyrus(-45.58, 29.91, 13.99), right anterior cingulate/paracingulate cortex(8.46, 37.01, 15.84), right middle occipital gyrus(37.39, -79.70, 19.42) and left angular gyrus(-42.80, 45.82, 46.74), while it was significantly increased in the right anterior central gyrus(41.37, -8.21, 52.09), right rolandic operculum(52.65, -6.25, 14.63), left inferior occipital gyrus(-36.36, -78.29, -7.84) and left fusiform gyrus(-31.16, -40.30, -20.23). Node degree of left lingual gyrus and betweenness centrality of the left triangular part of inferior frontal gyrus had significantly positive correlation with MoCA. Node degree of left lingual gyrus and the left triangular part of inferior frontal gyrus and betweenness centrality of the left triangular part of inferior frontal gyrus had significantly positive correlation with MMSE. Conclusion Both of the SVCI group and the control group show small-world attributes. The change of the node attributes in some regions of the brain can help to understand the underlying mechanism of the cognitive impairment. Key words: Subcortical vascular cognition impairment; Magnetic resonance imaging; Brain network
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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".