Abstract
Background. Alzheimer’s disease (AD) and frontotemporal dementia (FTD) are the two main types of dementia. We aim to investigate the difference between AD and FTD by use of multimodal EEG analyses. Additionally, the difference in correlations between EEG and clinical data was also investigated.Methods. Thirty-one patients diagnosed with AD and 15 patients with FTD were recruited (2008.1-2020.2), along with 24 healthy controls. Clinical data were reviewed. EEG microstate analysis, spectral analyses, and connectivity analysis were performed. Results. Microstate duration was increased in AD for microstate B and increased in FTD for microstate A compared to controls. Correspondingly, microstate C occurrence was decreased in both dementia groups, compared to control group. After divided into early onset and late onset AD, increased mean duration and reduced mean occurrence were observed in early onset AD, compared to late onset AD, with no significant difference in visual EEG score. CSF Aβ42 was correlated to microstate B coverage in AD (r = -0.833, P = 0.010), and microstate D occurrence in FTD (r = 0.786, P = 0.021). ADL and MMSE were also related to visual EEG score and microstate, but for different variables in the two dementia groups. Spectral analysis revealed decreased power in 8-30 Hz and increased power in delta band in both dementia. AD had higher spectral power in the temporal region, compared to FTD. Reduced alpha and beta coherences were demonstrated in AD in bilateral frontal, fronto-temporal, and fronto-occipital connections, and in FTD in the right frontal and fronto-temporal connections. Conclusions. Multimodal EEG analyses show different results between AD and FTD. Reduced coherence is across more brain areas in AD, including intra-anterior and anterior-posterior regions, compared to FTD, which only had frontal-temporal connectivity involved. Spectral analysis revealed a general EEG slowing. Increased microstate duration and decreased occurrence may be attributed to EEG slowing, for different classes in different types of dementia. Microstate may be more sensitive than visual EEG inspection. The correlations with clinical severity and biomarkers indicate that EEG is a potential biomarker for diagnosis and disease assessment.
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