Frequency dependent whole-brain coactivation patterns analysis in Alzheimer’s disease - Zhang, Si-Ping; Mao, Bi; Zhou, Tianlin; Su, Chun-Wang; Li, Chenxi; Jiang, Junjie; An, Simeng; Yao, Nan; Li, Youjun; Huang, Zi-Gang; , Alzheimer’s Disease Neuroimaging Initiative (Frontiers in Neuroscience, 2023)
Background: Brain in resting state has complex dynamic properties and shows frequency dependent characteristics. The frequency-dependent whole-brain dynamic changes of resting state across the scans have been ignored in Alzheimer’s disease (AD). Objective: Coactivation pattern (CAP) analysis can identify different brain states. This paper aimed to investigate the dynamic characteristics of frequency dependent whole-brain CAPs in AD. Methods: We utilized a multiband coactivation pattern (CAP) approach to model the state space and study brain dynamics in both AD and NC. The correlation between the dynamic characteristics and the subjects' clinical index was further analyzed. Results: The results showed similar CAP patterns at different frequency bands, but the occurrence of patterns was different. In addition, CAPs associated with the default mode network (DMN) and the ventral/dorsal visual network (dorsal/ventral VN) were altered significantly between the AD and NC groups. This study also found the correlation between the altered dynamic characteristics of frequency dependent CAPs and the patients’ clinical Mini-Mental State Examination assessment scale scores. Conclusion: This study revealed that while similar CAP spatial patterns appear in different frequency bands, their dynamic characteristics in subbands vary. In addition, delineating subbands was more helpful in distinguishing AD from NC in terms of CAP.