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Record W4384939406 · doi:10.24985/kjss.2023.34.2.270

Effects of Eye Movement Exercise on Cognitive Function and Prefrontal Cortex Connectivity for the Elderly with Mild Cognitive Impairment: An fNIRS Study

2023· article· en· W4384939406 on OpenAlexaboutno aff
Miyoung Roh, Tai-Seok Chang

Bibliographic record

VenueKorean Journal of Sport Science · 2023
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsnot available
FundersNational Research Foundation of KoreaMinistry of Education
KeywordsEye movementCognitionPrefrontal cortexPsychologyStroop effectPhysical medicine and rehabilitationEffects of sleep deprivation on cognitive performanceMontreal Cognitive AssessmentAudiologyNeuroscienceCognitive impairmentMedicine

Abstract

fetched live from OpenAlex

PURPOSE 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 OFC - right 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.308
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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