Phase aligned EEG source space features for distinguishing Alzheimer’s disease from frontotemporal dementia

Electroencephalography (EEG), as a non-invasive, cost-effective and easy-to-use tool that reflects brain activity in real time, provides potential support for differentiating AD and FTD. We propose a source-space feature method based on EEG phase alignment, where dynamic time warping (DTW) enhances inter-trial phase synchrony in the θ, α, β, and γ bands, sLORETA extracts brain region energy features, and a random forest classifier performs classification. In a dataset comprising 36 AD cases, 23 FTD cases, and 29 CN, the classification accuracies for AD vs.

CN reached 94.21% and 90.63%, respectively. Abnormalities in the AD group were primarily observed in the θ and γ bands, involving multiple cognition-related regions, whereas the FTD group exhibited β-band abnormalities predominantly affecting the parietal lobe and default mode network. These findings suggest that source-space features based on phase alignment can effectively distinguish the neural signatures of AD and FTD.

We thank all participants who participated in our study. School of Computer Science, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China Jiaqi Lin, Jinhua Sheng, Zhaozhe Gong, Rong Zhang, Zhongyuan Sun, Yuhan Cheng & Xinrui Zhu Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of China, Hangzhou, 310018, Zhejiang, China Jiaqi Lin, Jinhua Sheng, Rong Zhang, Zhongyuan Sun, Yuhan Cheng & Xinrui Zhu The authors declare no competing interests. Patient consent was waived due to the anonymization of all sensitive information in the collected data.

This study was approved by the institutional review board (IRB) at Hangzhou Dianzi University (IRB-2020001) and the ethics committee at Beijing Hospital (2022BJYYEC-375-01). Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Below is the link to the electronic supplementary material.

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