The purpose of this study was to detect effective connectivity (EC) changes in the default mode network and hippocampus network in 20 patients with Alzheimer's disease (AD) and 20 cognitively normal (CN) subjects, using multivariate Granger causality. The authors used the maximum coefficients in the multivariate autoregression model to quantitatively measure the different EC strength levels between the CN and AD groups. It was demonstrated that the EC strength difference can classify AD from CN subjects. Further, the right parahippocampal gyrus (PHP_R) showed imbalanced bidirectional EC connections. The PHP_R received weaker input connections from the neocortices, but its output connections were significantly increased in AD. These findings may provide neural physiological mechanisms for interpreting AD subjects' memory deficits during the encoding processes.
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