Change point estimation in multi subject social support fMRI studies

In many experimental fMRI studies, timing of the stimulus and activation duration of the subjects is assumed to be known a priori. However, in emotional mood change experiments, the timing of activation may differ for each subject. Besides these, common approaches for activation detection do not intrinsically support the question of whether there is a significant change in the fMRI time series and late-onset activations in such experiments. In scope of thesis, a Social Support fMRI task which triggers the change of the emotional situations of the subjects has been designed for the first time. The locations of the point where the subjects felt that their social support was lost and other significant changes, which are referred as change points, are estimated on the fMRI signals of the fMRI task. For this purpose, change point analysis is used which is an influential way to locate the abrupt changes and unexpected behavior in the data. With this, it is also aimed to eliminate the limitations of the approaches which detects the activation areas. Three different change point estimation methods are proposed to discover the change points in the fMRI sequences. The analysis shows that, the methods are able to locate the instance and location of the activations and changes. Detected activation points are compatible with the expected activations. The change pattern between moods in the regions associated with social support was modelled for the first time by working on real fMRI data. Besides, a new categorization methodology is also proposed for the change point problem.