Underlying mechanisms, clinical manifestation, and methodological considerations of functional connectivity in Dementia with Lewy Bodies

Abstract

AbstractBackgroundFunctional connectivity disturbances are potential disease mechanisms related to observable symptoms in Dementia with Lewy Bodies (DLB). Despite several existing theories, the exact relationship between functional connectivity, underlying mechanisms of the DLB, and symptomatology is yet not clear. The present review addresses this gap by summarising research findings of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) research while considering the impact of different methodological choices causing mixed findings.MethodWe performed a systematic literature review of resting‐state functional connectivity in DLB following PRISMA. We searched multiple databases from January 2000 to November 2022. Keywords included “DLB”, “connectivity”, “EEG”, and “fMRI”, their synonyms and acronyms, and related terms of network analysis. The final sample contained 6 EEG and 14 fMRI studies.ResultThe main methodological choices of fMRI articles included a data‐driven approach (i.e., Independent Component Analysis or Graph Theory; 43%), seed‐based or regions of interest (50%), or their combination (7%) with most studies focusing on large‐scale resting‐state networks (71%). The overall trend of connectivity findings showed a decrease, yet more subtle changes in the directionality of connectivity were observed when using a hypothesis‐driven approach (Fig 1A). The Default Mode Network (DMN) was the most studied network with 75% of relevant articles reporting decreased connectivity. Other networks with a consistent decrease in connectivity included Executive and Sensorimotor Networks (80% and 100% of relevant studies respectively). The inter‐network connectivity revealed the mixed relationship between the DMN, executive, attentional and visual networks (VN; Fig 1B). EEG studies showed a consistent decrease in connectivity on alpha and beta bands (100% and 66% of relevant studies respectively) and disorganisation in graph properties in regions overlapping with findings from large‐scale networks.ConclusionDysfunctions in large‐scale networks likely contribute to progressive degenerative mechanisms and are consistent with visual attention and perception processing theories of psychotic symptoms in the DLB. Hence, connectivity measures can capture brain disturbances in the DLB and remain crucial in uncovering underlying relationships between the networks’ disorganisation and disease mechanisms resulting in psychotic, motor, and cognitive symptoms in DLB. The choice of analytical approach might contribute to the directionality and mixed findings in the literature.