Abstract
Abstract Background As humans age, brain networks supporting cognition show alterations in functional connectivity patterns consistent with network dedifferentiation. Here we examined the extent to which Alzheimer’s disease (AD)‐related β‐amyloid (Aβ) pathology exacerbates functional dedifferentiation in aging and is associated with reduced probabilistic reward‐based learning. Method 27 young and 47 cognitively normal older adults underwent 3T functional magnetic resonance imaging (MRI) while performing a novel probabilistic learning task. The task required participants to learn the identity of real‐estate agents as “winning,” “losing,” or “break‐even” based on their success in selling houses for a profit. We used graph theoretical analysis and applied 400 regions of interest to identify age‐related changes in functional brain networks during early and late learning phases in the task. Older adults were characterized as Aβ‐ (n = 34) or Aβ+ (n = 13) using [ 11 C]Pittsburgh Compound‐B positron emission tomography. Analyses focused on the two graph theory measures commonly linked to dedifferentiation (i.e. loss of segregation): clustering coefficient and modularity. Results Young adults showed better learning performance, followed by Aβ‐ older adults and then Aβ+ older adults, but there was no significant age difference between young and Aβ‐ older adults (Fig. 1). Young adults also showed a higher clustering coefficient, which indicates greater network segregation, followed by Aβ‐ older adults and then Aβ+ older adults (Fig. 2A and 2B). Considering the learning phase, we found differences between the young and both Aβ‐ and Aβ+ older adults in the early learning phase (Fig. 2A), and differences between young and only Aβ+ older adults in the late learning phase (Fig. 2B). Analyses of modularity showed similar patterns of results, though the main effect of group was not significant (Fig. 2C and 2D). There was an interaction between network segregation and group to predict learning performance. Only Aβ‐ older adults with higher network segregation exhibited better learning performance (Fig. 3). Conclusion These findings indicate Aβ is associated with functional network dedifferentiation and poorer learning performance. For Aβ‐ older adults, successful maintenance of brain network segregation may underlie the preservation of “youth‐like” cognitive performance.