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Updated: Aug 15, 2026
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Predictive model for assessing cognitive impairment by quantitative electroencephalography
Joji Onishi1, Yusuke Suzuki, Kenichi Yoshiko
1Department of Geriatrics, Nagoya University Graduate School of Medicine, Nagoya, Aichi, 466-8550, Japan. j-onishi@med.nagoya-u.ac.jp
Objective:
To assess the utility of quantitative electroencephalographic analysis as an indicator of cognitive impairment, we examined the correlation between Mini-Mental State Examination (MMSE) scores and quantitative electroencephalographic (QEEG) power values in elderly patients and constructed a regression model to predict MMSE scores.
Background:
Because of the growing number of elderly individuals with cognitive deficits, there is an increasing need for simple and objective methods with which to evaluate cognitive function. Although QEEG is reportedly a useful method for this purpose, few researchers have constructed a QEEG-based model for predicting the degree of cognitive impairment in clinical settings.
Method:
We evaluated brain function using QEEG in 44 elderly patients with memory complaints and compared the results with their MMSE scores.
Results:
In the correlation analysis, no significant correlation was found between MMSE scores and QEEG power values. However, a regression model created using relative QEEG and gender for predicting MMSE scores had an adjusted R2 of 0.471.
Conclusions:
This finding suggests that QEEG analysis may be a useful indicator of cognitive decline in patients with memory complaints.
