Correlation Between Static Balance And Brain Activation During Standing In Older Adults With Mild Cognitive Impairment.
Bibliographic record
Abstract
PURPOSE: The aim of this study was to investigate the correlation between static balance and prefrontal cortex activation levels during standing in old adults with mild cognitive impairment (MCI). METHODS: Twenty old adults with MCI (MCI group) and twenty old adults with normal cognition (Control group) were asked to stand bipedally for 30 seconds (age 71.0 ± 3.8 years vs 68.4 ± 4.8 years, height 159.71 ± 7.29 cm vs 163.53 ± 6.63 cm, years of education 5.2 ± 2.2 years vs 6.0 ± 2.9 years). A force platform was applied to measure the displacement trajectory of the center of pressure (COP) to assess balance and a functional near-infrared spectroscopy (fNIRS) was applied to measure the activation level of the prefrontal lobe. The prefrontal cortex was divided into the extreme prefrontal cortex (FPC), dorsolateral prefrontal cortex (DLPFC), lateral prefrontal cortex (VLPFC), and orbital prefrontal cortex (OFC) according to the Montreal Neurological Institute (MNI) channel location information and Brodmann area (BA) criteria. Correlation analysis of balance and brain activation data was conducted using SPSS 26.0 software. RESULTS: In the control group, the swing path of COP was significantly and positively correlated with extreme prefrontal cortex (FPC) (r = 0.639, P = 0.003), but not in the MCI group. In the MCI group, both the maximal displacement of COP in the mediolateral direction (r = -0.468, P = 0.032) and the root mean square distance of COP (r = -0.485, P = 0.026) were significantly negatively correlated with the lateral prefrontal cortex (VLPFC), but not in the control group. CONCLUSION: The older adults with mild cognitive impairment might require more lateral prefrontal cortex activation (VLPFC) to compensate for maintaining static balance.
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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".