Functional Connectivity and White Matter integrity of intercommunity hub nodes in Subjective Cognitive Decline
Bibliographic record
Abstract
Abstract Background Subjective Cognitive Decline (SCD) is considered an early preclinical stage of Alzheimer’s Disease and related dementias (ADRD) which may show promise for targeted preventative treatments. Subtle changes in functional connectivity and white matter integrity (WMI) may occur in SCD. Few studies have applied both functional graph theory (GT) and diffusional kurtosis imaging (DKI) techniques in tandem to identify differences in vulnerable network hubs. We addressed these issues by applying GT and DKI to study differences in intercommunity brain hubs. The hypothesis was that in hubs identified in healthy controls, SCD subjects’ hubs would show decreased GT diversity coefficient (DC) and DKI mean kurtosis (MK). Method Images were acquired on a Siemens PRISMA scanner. Matlab was used to calculate DC and identify 5 hubs in 107 healthy controls (HC) and DC in 30 SCD (93 females, mean age = 67.51). SCD classification was determined by a comprehensive clinician evaluation or Everyday Cognition average item score>1.6, with objectively healthy cognitive performance (Montreal Cognitive Assessment score>22). Hub DC was the target in GLMM analysis, with diagnosis as predictor. Mean Kurtosis (MK) was analyzed in DSI Studio’s cross‐sectional connectometry using the hubs as seeds. Only the covariate of gray matter volume approached significance (p = .059), and was included in analysis. Mean age, education, head motion, and sex balance did not significantly differ between groups. Result All hubs had lower DC in SCD compared to HC (p ≤ .006). Connectometry identified positive correlation between MK and diagnosis in Left hemisphere tracts associated with two hubs: Inferior Fronto‐Occipital, Extreme capsule, and Uncinate tracts from Insular cortex, and Superior Longitudinal, Superior Corticalstriatal, Arcuate, Frontal Aslant, and Corticalspinal tracts from Middle Frontal gyrus. Conclusion Conclusion Rs‐fMRI findings show that intercommunity functional hubs are weaker in SCD compared to healthy individuals. Furthermore, the study identified a relationship of higher MK values in SCD for hubs located in insular cortex and middle frontal gyrus, all left hemisphere biased. Higher MK in SCD also runs counter to our hypothesis but is supported by recent paradoxical increase theories of decline. WMI differences between groups may be subtler than functional changes, warranting examination of the 2 modalities’ relationship.
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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 | 0.002 |
| 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) | 0.003 | 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".