White Matter Degradation is Associated with Reduced Financial Capacity in Mild Cognitive Impairment and Alzheimer’s Disease
Bibliographic record
Abstract
Financial capacity (FC) is a cognitively complex activity of daily living that declines in mild cognitive impairment (MCI) and Alzheimer's disease (AD), limiting an individual's ability to manage one's finances and function independently. The neural underpinnings of this decline in function are poorly understood but likely involve age-related and disease-related degradation across structural networks. The purpose of the current study was to determine if altered white matter integrity is associated with declining FC in persons with MCI and AD compared to older controls. Individuals with MCI due to AD (n = 31), mild dementia (n = 39), and cognitively healthy older adults (n = 60) were administered a neuropsychological battery including the FC Instrument, a performance-based measure of FC. All 130 participants also underwent diffusion tensor imaging (DTI) upon which tract-based spatial statistics were performed. Both FC and white matter integrity decreased in accordance with disease severity with little to no effect in healthy elderly, significant effects in MCI, and greater effects in AD. Regional white matter degradation (increased diffusivities and decreased fractional anisotropy) was associated with reduced FC in both MCI and AD groups even after controlling for age, education, and gender. Specifically, in MCI, decreased fractional anisotropy, but not increased diffusivities, was associated with poorer FC in widespread cingulo-parietal-frontal and temporo-occipital areas. In AD, rather than anisotropy, increased mean and axial diffusivities in anterior cingulate, callosum, and frontal areas associated with poorer FC. These findings suggest a severity gradient of white matter degradation across DTI metrics and AD stages that predict declining financial skill and knowledge.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".