Probabilistic Analysis of Nucleus Accumbens Signal Alterations in Rs-fMRI

Rs-fmri provides to establish the default mode network that comprises the connections of the neural networks of the brain and the relations of these connections with each other in the state of rest. However, unexpected signal alterations and changes may also occur in fmri signals in areas outside the default network. In this study, the magnitude and probability of random fluctuations in these signals were estimated by Bayesian-based change point analysis in Nucleus Accumbens signals that are not expected to be activated in resting state. The data set was acquired from 23 healthy and voluntary university students using 3T MRI scanners. With the proposed method, signals containing unexpected activation from rs-fmri signals can be estimated in linear time.