P1‐391: EVIDENCE FOR A QUADRATIC RELATION BETWEEN ACTIVATION AND NEURODEGENERATION IN THE PRODROMAL PHASE OF ALZHEIMER'S DISEASE
Bibliographic record
Abstract
It has been proposed that neuronal activation follows an inverse U-shape trajectory during the prodromal phase of Alzheimer's disease (AD). Hyperactivation, i.e., larger activation in patients than in cognitively unimpaired controls (CU), would be observed in the early phase of the prodrome when neurodegeneration is mild, then followed by hypoactivation as structural damage increases with disease progression. This was tested by comparing linear and quadratic models to examine the function that best characterizes the relationship between neurodegeneration and activation in prodromal AD. The study included 59 CU subjects and 54 considered at-risk of AD based on either meeting criteria for mild cognitive impairment (MCI) or because they presented with complaint and worry about their memory although they were cognitively unimpaired, as well as a smaller hippocampal volume and/or were ApoE4 positive (subjective cognitive decline+, SCD). Functional MRI activation was measured while subjects memorized 78 pictures and their location in a four-position grid. Significance of R change between linear and quadratic models was assessed to determine which model best fits the relationship between neurodegeneration (hippocampal volume/cortical thickness) and activation in the hippocampus and cortical regions vulnerable to AD. This was done separately for the at-risk and CU groups. In the presence of a significant model, follow-up ANOVAs were used to assess activation differences between SCD, MCI and CUs groups. A quadratic model was significant between mean cortical thickness and activation in the left superior parietal lobule and a linear negative model was significant between left hippocampal volume and activation in the left hippocampus and in the right inferior temporal lobe in the at-risk group but not in CUs. ANOVAs indicated larger levels of activation in SCD than CU in the left superior parietal lobule, left hippocampus and right inferior temporal lobe and lower levels of activation in MCI than in CU in the left superior parietal lobule. Parietal activation follows an inverse U-shape as a function of neurodegeneration in prodromal AD, with hyperactivation in SCD and hypoactivation in MCI. Our data suggests that task-related hyperactivation might represent an early biomarker of AD and could help identify individuals in its prodromal phase.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".