The effect of aperiodic components in distinguishing Alzheimer's disease from frontotemporal dementia

Abstract Background: Distinguishing Alzheimer's disease (AD) from frontotemporal dementia (FTD) poses a clinical challenge, and to address this, inexpensive and accessible techniques, such as electroencephalography (EEG), are increasingly being employed. However, current studies on electrophysiology have not adequately separated aperiodic activity from spectral analysis and have instead evaluated the combination of periodic oscillatory components and aperiodic components. As the understanding of aperiodic activity has evolved, its potential physiological significance in these disorders has become an area of growing interest. The objective of our study is to determine the differences in aperiodic activity between these two dementia-related diseases and to evaluate their effect in distinguishing between them. Methods: A total of 88 participants, including 36 patients with AD, 23 patients with FTD, and 29 healthy controls (CN), were enrolled for cognitive assessment and scalp EEG acquisition. The spectrum was decomposed using a method of parameterizing neuronal power spectra, comparing group differences in different components, and a support vector machine was used to determine the effect of aperiodic parameters in the differential diagnosis. Results: The AD and FTD groups showed varying degrees of EEG rhythm slowing compared to CN group. Theta periodic power and aperiodic parameters were higher in the AD group compared to the FTD group at the channel level. The inclusion of the aperiodic parameters led to better performance for differential diagnosis. Conclusions: Our study indicates that aperiodic activity shows differences in patients with AD and FTD, and has the potential to distinguish between these disorders. These results underscore the physiological significance of aperiodic components in dementia-related diseases.