EEG Resting-State Networks in Dementia with Lewy Bodies Associated with Clinical Symptoms.

BACKGROUND

Dementia with Lewy bodies (DLB) is characterized by progressive cognitive decline, fluctuating cognition, visual hallucinations, rapid eye movement sleep behavior disorder, and parkinsonism. DLB is the second most common type of degenerative dementia of all dementia cases. However, DLB, particularly in the early stage, is underdiagnosed and sometimes misdiagnosed with other types of dementia. Thus, it is of great interest investigating neurophysiological markers of DLB.

METHOD

We introduced exact low-resolution brain electromagnetic tomography (eLORETA)-independent component analysis (ICA) to assess activities of 5 electroencephalography (EEG) resting-state networks (RSNs) in 41 drug-free DLB patients.

RESULTS

Compared to 80 healthy controls, DLB patients had significantly decreased activities in occipital visual and sensorimotor networks, where DLB patients and healthy controls showed no age dependences in all EEG-RSN activities. Also, we found correlations between all EEG-RSN activities and DLB symptoms. Specifically, decreased occipital α activity showed correlations with worse brain functions related to attention/concentration, visuospatial discrimination, and global cognition. Enhanced visual perception network activity correlated with milder levels of depression and anxiety. Enhanced self-referential network activity correlated with milder levels of depression. Enhanced memory perception network activity correlated with better semantic memory, visuospatial discrimination function, and global cognitive function as well as with severer visual hallucination. In addition, decreased sensorimotor network activity correlated with a better semantic memory.

CONCLUSION

These results indicate that eLORETA-ICA can detect EEG-RSN activity alterations in DLB related to symptoms. Therefore, eLORETA-ICA with EEG data can be a useful noninvasive tool for sensitive detection of EEG-RSN activity changes characteristic of DLB and for understanding the neurophysiological mechanisms underlying this disease.