Disruptive resting state networks characterizing depressive comorbidity in Alzheimer's disease and mild cognitive impairment

Background Depressive comorbidity in neurodegeneration has been shown to predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD). However, its pathophysiology is not completely understood. Objective Here, we characterize aberrant functional resting state networks (RSNs) characterizing depressive comorbidity in both AD and MCI. Methods We conducted a systematic literature review on Scopus, PubMed, and Web of Science to extract experiments that compared resting state scans of depressed and non-depressed MCI or AD patients. We employed Activation Likelihood Estimation (ALE) meta-analysis on eligible studies resulting from the search, to describe regions of significant co-activation across studies. Results The systematic search resulted in 17 experiments, with 303 participants in total. The ALE yielded 10 clusters of significant co-activation distributed in the five major RSNs and across cortico-basal ganglia-thalamic circuits. Conclusions Depressive comorbidity in neurodegeneration presents signature aberrant resting-state fluctuations. Understanding these within- and between-network alterations may be useful for future diagnostic and therapeutic applications.