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Functional magnetic resonance imaging (fMRI) provides a noninvasive window into the ongoing activity of the human brain, allowing activity localization and connectivity assessment. From fMRI data, a functional connectome (a map of functional brain connections) can be derived and network analysis methods and graph theory applied to better understand the brain. However, getting to the point of inferring a functional connectome requires understanding of the physics and biology underpinning the hemodynamic signal; the parameters to select when establishing an MRI scanner protocol; how to preprocess the data that comes from the scanner so that it is of suitable quality for further analyses; and finally, how to derive the functional network matrix. In this chapter, these fundamental topics are covered providing the necessary foundational knowledge for conducting functional connectomic studies.

Original publication





Book title

Connectome Analysis: Characterization, Methods, and Analysis

Publication Date



45 - 69