Dissociable species-specific impact of Aβ on static and dynamic functional connectomes

Temporal dynamics in functional connectomes provide a physiologically grounded signature of 'hidden' pathologies during preclinical stages of Alzheimer's disease (AD). We evaluated the effect of beta-amyloid (A{beta}) on dynamic functional connectomes in transgenic mice and human subjects. Functional magnetic resonance images (fMRI) were collected in two strains of A{beta} mice. fMRI-derived connectomes were segmented into discrete states using a hidden Markov model, and network strength, efficiency, and transitivity were analyzed per state. Human fMRI-derived connectome measures were analyzed across 3 states. Static network measures were significantly different between A{beta} mice and controls, the former having high values for strength, efficiency and clustering coefficient in anterior cingulate, hippocampus, and retrosplenium. Dynamic network measures were stable within-states in A{beta} mice. Similarly, human subjects with high A{beta} had high node strength in precuneus and temporoparietal areas compared to low A{beta}. Conversely, high A{beta} was associated with high switch rates, high fractional occupancy, and state dwell times. Also, global strength, efficiency, and transitivity were less stable within states in the high A{beta} group. Our results indicate that static, but not dynamic, connectome strength, efficiency, and network integration are increased in A{beta} mice, while dynamic network states appear less stable in human functional connectomes. This data supports a dissociable, species-specific impact of A{beta}, with dynamic network alterations present in humans but not in A{beta} mouse models, suggesting additional non-A{beta}-driven influences on dynamic functional connectivity in preclinical AD.