Improved functional connectivity after a 6‐month ketogenic supplementation in mild cognitive impairment
Bibliographic record
Abstract
Abstract Background Ketones, the brain’s alternative fuel to glucose, bypass the brain glucose deficit in mild cognitive impairment (MCI). The BENEFIC trial conducted in MCI showed improved measures of cognition in multiple domains after a 6‐month ketogenic intervention [Fortier et al. 2019]. Functional connectivity in the dorsal‐attention network (DAN) deteriorates early in MCI, and prior to changes in the ventral‐attention network [Zhang et al. 2015]. We aimed to assess whether improved cognitive outcomes in the BENEFIC Trial were linked to improved brain functional connectivity. Method Participants in this 6‐month intervention were randomized to a placebo (n= 15) or ketogenic medium chain triglyceride (kMCT; n= 17) drink. A neurocognitive battery and brain imaging were performed pre‐ and post‐intervention. Functional connectivity was computed from resting‐state functional magnetic resonance images. Independent component analysis (FSL Melodic) was used to segment seven major resting‐state networks (DAN, ventral‐attention, frontoparietal, limbic, somatomotor, default‐mode and visual) [Yeo et al. 2011]. Regional cortical ketone (11C‐acetoacetate) and glucose (18F‐fluorodeoxyglucose) metabolic rates were also quantified using positron emission tomography (PET). Result Changes (post ‐ pre) in DAN functional connectivity was significantly higher in the kMCT group vs placebo (P= 0.024). After correction for age, sex, education, ApoE status and intracranial volume, the significant difference between groups was still present, with a large effect size (partial h2= 0.16; P= 0.043; Figure 1). Connectivity in no other networks was significantly different between groups. Changes in attention and processing speed composite Z‐score (r= 0.42; P= 0.021) and specific tests targeting attention (Trail Making visual scanning and number sequencing conditions) were significantly associated with the increased DAN functional connectivity. Change in ketone uptake specifically in DAN cortical regions (Figure 2C) was significantly higher in the kMCT vs placebo group (P= 0.001) and was directly associated with the improved DAN functional connectivity, with a large effect size (r= 0.69; P= 0.002; Figure 3). Conclusion We show that a 6‐month ketogenic intervention improves DAN functional connectivity in MCI, an improvement that is directly linked to increased energy (ketone) supply to the DAN. The beneficial effect of ketones on cognition in MCI may be linked to improved DAN connectivity.
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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) | 0.001 | 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".