B - 31 Association of Hippocampal Volume with Subjective and Objective Cognitive Functioning in a Diverse Sample
Bibliographic record
Abstract
Abstract Objective Individuals with subjective cognitive complaints (SCCs) and reduced hippocampal volumes (HV) may be at increased risk of future cognitive decline, though findings regarding the relationship between SCCs and HV have been mixed. The current study explores the association of HV with SCCs and objective cognitive performance in a diverse sample. Method Participants in a population-based cardiovascular risk study (N = 1754; MAge = 58.8, 59% Female, 50% Black, 10% Hispanic) responded to three subjective cognitive functioning questions prior to completing the Montreal Cognitive Assessment (MoCA): 1) Do you have consistent memory problems, 2) If YES, do they interfere with everyday activities, and 3) do you have trouble figuring things out/solving problems. HV were derived from a 3-tesla MRI and normalized using total intracranial volume. Partial correlations examined associations between HV, MoCA scores, and SCCs, while one-way ANCOVA compared HV by SCC endorsement pattern, controlling for demographics. Results Findings revealed smaller HV in those who endorsed all SCC questions (n = 27; MHV =0.34) compared to those without any SCC (n = 631, MHV = 0.36, p = 0.001), though effect size was small (η2 = 0.015). HV were not correlated with SCCs (r = −0.06, p = 0.10) or cognitive performance (r = 0.01, p = 0.75), and SCCs had a small correlation with MoCA scores (r = −0.18, p < 0.001). Conclusions Subjective cognitive functioning was minimally associated with HV and cognitive performance in this sample, and as a result the clinical significance of these findings is unclear. Further research is needed to understand the possible neuroanatomical correlates of SCC, along with the predictive utility of SCCs in the early identification of cognitive decline.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".