Change Point Detection Methods for Locating Activations in Functional Neuronal Images

The most common analysis for fMRI images is activation detection, in which the purpose to find locations brain that respond specific functions, such as visual processing or motor functions by providing related stimuli tasks experiment. On other hand, it also important detect instance triggered. One of powerful techniques can analyze abnormal behavior any data change point (CP) analysis. We suggest CP detection algorithms be used locate activations functional magnetic resonance imaging (fMRI) sequences, well. Our paper presents a two-fold innovative study respect. First, we propose use signals state-of-art topic. Furthermore, and compare set methods, regression-based method (RBM), statistical (SM), mean difference double sliding windows (MDSW)) points. Second, apply these methods signals, are acquired from real subjects, while they were performing tasks. Proposed applied three different experiments with task, linguistic task. shows accordance established parametric maps (SPM). up 94 % results show proposed effectively times on time series.