Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/0DB3526A-E27B-4188-BEC5-1A4B01EA9CAD | ||
| Year | 2023 | ||
| Type of Item | Diploma Work | ||
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| Bibliographic Citation | Efstathia Poulea, "Whole brain parcellation via resting-state fMRI data analysis", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2023 https://doi.org/10.26233/heallink.tuc.98131 | ||
| Appears in Collections |
Functional magnetic resonance imaging (fMRI) is a non-invasive method that provides important information about brain functionality. It is a technique that maps brain activity by detecting changes related to blood flow. The most common form of fMRI measures the signal that reflects changes in blood flow to the brain and is used to understand how the brain works.Since brain activity is intrinsic, any brain region will exhibit spontaneous fluctuations in the BOLD signal. Thus, even at rest, the BOLD signal reflects systematic fluctuations associated with brain activity. It is widely believed that resting state networks are the cause of these fluctuations. So, there is a common, for many subjects compartmentalization of the brain, based on functionality.In this thesis, we study a method that computes a common, multi-subject, brain partition, without prior knowledge of the properties of the partition.First, we present a method which calculates the common spatial subspace through the Generalized Canonical Correlation Analysis (gCCA) method. We then apply this method to real data involving healthy and non-healthy subjects and compare the results.
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