Insular and Hippocampal Connectivity Is Associated With Perceived Financial Exploitation in Older Adults
Bibliographic record
Abstract
Abstract Little is known about the neural correlates of financial exploitation (FE) in older adults. Cognitively-intact older adults who self-reported a history of FE (N=19; M age=69.84, SD=13.06) and demographically-matched non-FE older adults (N=16; M age=65.13, SD=8.48) underwent resting-state fMRI. Predefined regions of interest were prescribed using the Harvard-Oxford atlas for their involvement in tasks of economic decision making: insula, hippocampus, and the medial prefrontal cortex (mPFC). Analyses adjusted for age, education, sex, and MoCA scores; groups did not differ on these factors. Clusters were FDR-corrected with a threshold of p<0.05 (voxel threshold p<0.005), two-tailed. Compared to the non-FE group, the FE group exhibited greater functional connectivity (FC) between the right insula and left temporal lobe regions (t(29)= -4.81), and between the left insula and right temporal lobe regions (t(29)= -5.78). The FE group showed less FC between the left insula and two clusters in the right lateral occipital cortex (t(29)= 5.18) and left cerebellum (t(29)= 4.68). Additionally, FE was associated with greater FC between the right hippocampus and five clusters spanning the right temporal lobe, parietal lobe, and frontal pole (ts(29)= -4.11 to -4.51), and less FC between the right hippocampus and three clusters spanning the bilateral caudate and the left intracalcarine cortex (ts(29)= 4.76-6.03). Groups did not differ in FC patterns with the mPFC. Results suggest that FE is associated with whole-brain FC differences involving the insula and hippocampus among cognitively-intact older adults.
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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 | 0.000 | 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) | 0.002 | 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".