Choosing a regression model to predict cognition from a connectivity analysis of the brain
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2018-08-20
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en
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The human brain has been of great interest to researchers for a very long time,
as the source of our cognitive abilities and our behavior. The advances made in
neuroimaging in the second part of the previous century, enabling us to visualize
the brain in vivo [Ogawa et al. 1990] instead of during surgery or post mortum,
resulted in an increase in knowledge of brain functioning. Different brain regions
have different functions, which is especially apparent if there is a lesion in the
brain, e.g. ischemia caused by a cerebrovascular accident (stroke), hemorrhaging
or tumors, presenting with different symptoms depending on the region (e.g.
slurred speech, lethargy, personality changes) [Kase and Caplan 1994; Keschner,
Bender, and Strauss 1938; McCormick and Rosenfield 1973; Little et al. 1979;
Uribe 1986].
More recently, technological advances in neuroscience and neuroimaging made it
possible to look at the whole brain as a network, e.g. functional MRI. The network
perspective has become increasingly important in neurology and neuroscience. Although
the notion that the brain is a network is not new, the discipline of studying
the relationship between broken connections and diseases (neurodegenerative disorders)
has sped up in the last decades due to those technological advances.
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Faculteit der Sociale Wetenschappen