Prefrontal GABA Levels Correlate with Memory in Older Adults at High Risk for Alzheimer’s Disease
Bibliographic record
Abstract
Abstract γ-Aminobutyric acid (GABA), a primary inhibitory neurotransmitter in the brain, plays a significant role in aging and in neurodegenerative disorders, including Alzheimer’s disease (AD). We investigated the relationship between GABA levels in the dorsomedial/dorsoanterolateral prefrontal cortex (DM/DA-PFC) and memory in high-AD risk participants. Thirty-eight participants (14 Cognitively Normal [CN], 11 with Subjective Cognitive Decline (SCD), and 13 Mild Cognitive Impairment [MCI]) underwent magnetic resonance spectroscopy at 3 Tesla. SCD and MCI participants were grouped together to form a single high-AD risk group (N = 24) for the purposes of statistical analyses. Partial correlations of GABA+/Cr level with verbal memory, assessed on California Verbal Learning Test-II, and nonverbal memory, assessed on Brief Visuospatial Memory Test and Rey-Osterrieth test, were examined separately within the high-AD risk and CN groups. GABA+/Cr levels were positively correlated with long-delayed verbal memory (r = 0.69, P = 0.009) and immediate nonverbal memory (r = 0.97, P = 0.03) in high-AD risk, but not in CN participants. These results remained significant after controlling for depression. These preliminary findings, which require replication due to the limited sample sizes, are the first report of an association between GABA+/Cr levels within the DM/DA-PFC and memory performance in high-AD risk individuals.
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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) | 0.001 | 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".