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Brain Connectivity Analysis Using Multiple Partial Least Square on fMRI Signals

Hosseini Naghavi, Nader | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52699 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Fatemizadeh, Emad
  7. Abstract:
  8. Nowadays studying the brain's function in different Mental States like Resting-State or performing cognitive tasks is a very important component of research areas such as Biomedical Engineering, Neuroscience and Cognitive Sciences. The applications of studying the brain's function can be divided into two principal groups. In the first group of applications, the goal is understanding how the brain processes and response to external stimuli (like visual or audio stimuli) and internal states (like emotions). In these kinds of applications, particularly healthy subjects participate since the goal of these studies is finding healthy brain function in different states and stimuli. However, in the second group of applications, the goal is finding how different mental (like Depression) or brain (like Epilepsy) disorders alter the brain's function. In these kinds of studies, the researchers compare the function of healthy and patient's brains in the same conditions in order to find the difference between their brain's function. The results of such researches could be useful for finding the Biomarkers of mental or brain disorders and monitoring the effectiveness of treatment strategies. Functional MRI is one of the best modalities used for analyzing the brain's function because it can map the function of different brain areas with fairly good resolution. In this project, we used fMRI modality for analyzing the brain's function and we pursued two different goals. First of all, we wanted to find the effects of emotional states on patterns of Spatio-Temporal activities and Functional Connectivity. Secondly, we wanted to study the effect of Depression in the ways that the brain handles emotional states. For achieving our goals, we used a public dataset which was comprised of a healthy control group and a group of patients with Major Depression Disorder. Subjects in both groups were listening to Positive and Negative Emotional Kinds of music and also a non-music audio stimulus. Our goal was to analyzing the fMRI data of these two groups of subjects to find the effects of positive and negative emotions on the patterns of brian activation and functional connectivity and also compare these patterns among two groups. In this project, for analyzing the Spatio-temporal activation patterns within the brain we used Spatio-Temporal PLS, for analyzing the patterns of functional connectivity we used Seed-pls and finally, with by the means of Multiple Correlation method we analyzed the patterns of clusters formed between brain regions in different states and groups.Our results showed that in the contrast between listening to music (positive or negative) and to non-music stimuli primary areas of Auditory Cortex get activated and patterns of activation are not significantly different between two groups. However, by analyzing the patterns of functional connectivity, we realized that the connectivity patterns of Default Mode Network's primary areas (like Frontal areas) and Amygdala and also the internal connectivity patterns of the DMN network are significantly different in two groups particularly in the states of processing negative emotions
  9. Keywords:
  10. Functional Connectivity ; Cognitive Science ; Major Depressive ; Partial Least Squares (PLS) ; Functional Magnetic Resonance Imaging (FMRI) ; Brain Networks ; Mental Disorder ; Spatio-Temporal Activities

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