Enhanced neural activation with blueberry supplementation in mild cognitive impairment
Bibliographic record
Abstract
OBJECTIVES: Preclinical studies have shown that blueberry supplementation can improve cognitive performance and neural function in aged animals and have identified associations between anthocyanins and such benefits. Preliminary human trials also suggest cognitive improvement in older adults, although direct evidence of enhancement of brain function has not been demonstrated. In this study, we investigated the effect of blueberry supplementation on regional brain activation in older adults at risk for dementia. METHODS: In a randomized, double-blind, placebo-controlled trial we performed pre- and post-intervention functional magnetic resonance imaging during a working memory (WM) task to assess the effect of blueberry supplementation on blood oxygen level-dependent (BOLD) signal in older adults with mild cognitive impairment, a risk condition for dementia. RESULTS: Following daily supplementation for 16 weeks, blueberry-treated participants exhibited increased BOLD activation in the left pre-central gyrus, left middle frontal gyrus, and left inferior parietal lobe during WM load conditions (corrected P < 0.01). There was no clear indication of WM enhancement associated with blueberry supplementation. Diet records indicated no between-group difference in anthocyanin consumption external to the intervention. DISCUSSION: These data demonstrate, for the first time, enhanced neural response during WM challenge in blueberry-treated older adults with cognitive decline and are consistent with prior trials showing neurocognitive benefit with blueberry supplementation in this at-risk population.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".