Neurometabolic correlates of posturography in normal aging and older adults with mild cognitive impairment: Evidence from a 1H-MRS study
Bibliographic record
Abstract
Proton magnetic resonance spectroscopy (1H-MRS) holds promise for revealing and understanding neurodegenerative processes associated with cognitive and functional impairments in aging. In the present study, we examined the neurometabolic correlates of balance performance in 42 cognitively intact older adults (healthy controls - HC) and 26 older individuals that were diagnosed with mild cognitive impairment (MCI). Neurometabolite ratios of total N-acetyl aspartate (tNAA), glutamate-glutamine complex (Glx), total choline (tCho) and myo-inositol (mIns) relative to total creatine (tCr) were assessed using single voxel 1H-MRS in four different brain regions. Regions of interest were the left hippocampus (HPC), dorsal posterior cingulate cortex (dPCC), left sensorimotor cortex (SM1), and right dorsolateral prefrontal cortex (dlPFC). Center-of-pressure velocity (Vcop) and dual task effect (DTE) were used as measures of balance performance. Results indicated no significant group differences in neurometabolite ratios and balance performance measures. However, our observations revealed that higher tCho/tCr and mIns/tCr in hippocampus and dPCC were generic predictors of worse balance performance, suggesting that neuroinflammatory processes in these regions might be a driving factor for impaired balance performance in aging. Further, we found that higher tNAA/tCr and mIns/tCr and lower Glx/tCr in left SM1 were predictors of better balance performance in MCI but not in HC. The latter observation hints at the possibility that individuals with MCI may upregulate balance control through recruitment of sensorimotor pathways.
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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 | 0.001 | 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".