Effects of Eye Movement Exercise on Cognitive Function and Prefrontal Cortex Connectivity for the Elderly with Mild Cognitive Impairment: An fNIRS Study
Bibliographic record
Abstract
The purpose of this study was to examine the effects of an eye movement exercise intervention on cognitive function and prefrontal cortex connectivity in the elderly with mild cognitive impairment.METHODS Ten older adults with mild cognitive impairment participated in eye movement exercise consisting of saccadic eye movement, pursuit eye movement, vestibular-ocular eye movement, and vergence eye movement for 4 weeks.Cognitive function (MoCA-K), reaction time during stroop task, and prefrontal cortex connectivity were measured using the functional near-infrared spectrometric analyzer (fNIRS) before and after the intervention.RESULTS First, cognitive function of the elderly with mild cognitive impairment showed significant improvement after the eye movement exercise (p < .05).Second, reaction time decreased significantly from 1.16 to 0.91 ms after eye movement exercise.Third, the strength of prefrontal cortex connectivity (left OFCright FPC, right OFC -right FPC) increased after the intervention in the older adults with mild cognitive impairment.CONCLUSIONS The results of this study suggest that eye movement exercise is an effective intervention for improving cognitive function through improvement of brain functional connection in the elderly patients with mild cognitive impairment. 서론 서론경도인지장애(mild cognitive impairment, MCI)는 치매와 정상 노인의 중간단계로 기억력을 비롯한 여러 인지기능 장애를 보이며 일상생활을 영위하는 데 불편함이 없는 상태를 말하지만(Petersen, 2004), 치매로 진행될 확률이 매우 높은 치매 고위험군이다.특히, 한국의 경우 2010년부터 고령화 문제가 심각해지면서 경도인지장 애 환자 수도 매년 가파르게 상승하여 이후 5년간 4.3배 증가하였 으며(National Health Insurance Service, 2015) 정상 노인의 경 우 매년 1~2%가 치매(Petersen et al., 2001) 에 걸리는 반면, 경 도인지장애 환자는 10~15%가 치매(Busse et al., 2003)로 진행된 다고 보고되고 있다.따라서 최근 들어 치매 고위험군인 경도인지 장애를 대상으로 한 연구는 치매의 위험요인을 사전에 차단하고 조 기 발견하여 예방하는 차원에서 주목받고 있다.이에 인지 학습과
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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) | 0.000 | 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) | 0.000 | 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".