Determinants of EEG Peak Alpha Frequency in the Elderly

Authors

  • Tisa Pavlovčič University of Ljubljana

Abstract

Introduction

Dementia is one of the greatest health and societal burdens of our time. Early detection of this disease may critically delay the onset of symptoms and thus improve the quality of life for patients and their caretakers. Besides genetic, biochemical, and neuroimaging biomarkers to screen for dementia, the value of EEG biomarkers is being increasingly recognized [1]. The so-called “brain slowing” is a well-established phenomenon in patients with dementia where the EEG power spectrum shifts toward lower frequencies. In particular, the peak alpha frequency (PAF), which is thought to represent a robust EEG correlate of general cognitive performance, is known to decrease in dementia patients [2]. However, PAF may be affected by other (demographic) factors apart from a patient’s cognitive status. Reducing the variability of PAF by accounting for these confounding factors might increase the usefulness of EEG as a method for cognitive assessment. 

Methods

300 elderly participants (60-95 years old) will be included in the study. Five psychometric tests (Montreal Cognitive Assessment, Alzheimer’s Disease Assessment Scale - Cognitive, Addenbrooke Cognitive Assessments, Phototest, and Eurotest) as well as 8-minute resting state EEG measurement will be performed on three different occasions (each session will include 1-3 psychometric tests and an EEG measurement). EEG data will be pre-processed to exclude common artifacts and the PAF calculated for each subject. Multiple regression with the following factors will be performed: age, education years, head size, gender, and cognitive performance. 

Expected Results

We expect a negative moderate yet significant relation between PAF and factors of age and education. We do not expect significant relationships between gender and head size. Strongest relations between PAF and cognitive status (as assessed by psychometric tests) are expected, indicating that cognitive status predicts PAF better than age, education years, head size, or gender.

Discussion

Should any demographic factors show a highly significant and independent correlation with PAF, this would need to be corrected for in further assessments of EEG biomarkers for early dementia screening. Correction factors may increase specificity and sensitivity of such EEG tests, thus increasing chances of correctly separating pathological from healthy brain oscillations. 

References

[1] L. Sanchez-Reyes, J. Rodriguez-Resendiz, G. Avecilla-Ramirez, M. Garcia-Gomar and J. Robles-Ocampo, "Impact of EEG Parameters Detecting Dementia Diseases: A Systematic Review", IEEE Access, vol. 9, pp. 78060-78074, 2021. Available: 10.1109/access.2021.3083519.

[2] W. Klimesch, "EEG-alpha rhythms and memory processes", International Journal of Psychophysiology, vol. 26, no. 1-3, pp. 319-340, 1997. Available: 10.1016/s0167-8760(97)00773-3.

Published

2022-06-23