Cognitive Functional Evaluation by Asymmetry of Spontaneous Electroencephalogram During Sustained Attention to Response Task

ABE, Hiroyuki; TANAKA, Hisaya; TSUGAWA, Akito; SATO, Tomohiko; FUKASAWA, Raita; SHIMIZU, Soichiro · 2023 · Crossref

DOI: 10.5057/isase.2023-c000014

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Summary

This study addresses the critical need for early dementia detection, a growing social issue given the projected increase in dementia patients globally. Early diagnosis is essential for slowing symptom progression, yet significant delays often occur between the onset of symptoms and clinical diagnosis due to patient hesitation and the complexity of standard neuropsychological examinations. To facilitate earlier and easier screening, the authors propose using a P300-based Spelling-brain-computer interface (Spelling-BCI) not as an input device, but as a visual stimulus presentation tool for a sustained attention task. The research investigates whether asymmetry in spontaneous electroencephalogram (EEG) frequency components can serve as a reliable indicator of cognitive function decline, potentially allowing for the estimation of neuropsychological test results without specialist administration. The experimental design involved 101 dementia patients aged 60 to 90 who visited the Department of Geriatrics at Tokyo Medical University between 2017 and 2022. Participants were categorized into five groups based on their Mini-Mental State Examination (MMSE) scores: questionably significant (L0), mild (L1), moderate 1 (L2), moderate 2 (L3), and severe (L4). During the experiment, subjects performed a sustained attention task using the Spelling-BCI, where they gazed at specific characters on a Japanese dial while rows and columns blinked randomly. EEG data was recorded using active electrodes placed at eight locations in the extended 10–20 system, with specific focus on the parietal–posterior–temporal region (PO7 and PO8). The researchers analyzed the asymmetry of power spectrum components for θ (4–8 Hz), α1 (8–10 Hz), α2 (10–13 Hz), and β (13–30 Hz) waves using MATLAB. The results demonstrated that as cognitive function declined, the asymmetry of θ, α1, and α2 wave components decreased. Statistical analysis using the Kruskal-Wallis test revealed significant main effects for both θ (p = 0.0415) and α1 (p = 0.0039) wave asymmetries. Steel-Dwass multiple comparisons indicated significant differences between the non-dementia group (L0) and the moderate 1 group (L2) for both θ (p = 0.0373) and α1 (p = 0.0154) components. In contrast, no significant main effects were found for α2 (p = 0.1530) or β (p = 0.2859) wave asymmetries, rendering them unsuitable as indicators. The decrease in θ and α1 asymmetry is attributed to increased functional connectivity between PO7 and PO8 during sustained attention tasks as cognitive function declines. The study concludes that the asymmetry of α1 and θ wave components during a sustained attention response task is a reliable and effective indicator for distinguishing between dementia and non-dementia groups. These findings support the development of an inexpensive, simple BCI-based screening tool that can estimate cognitive function decline levels. By leveraging these specific EEG markers, future models can improve the accuracy of cognitive function classification, facilitating earlier diagnosis and intervention for dementia patients.

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• neuro workload indices