ABSTRACT
Mapping spatially distributed brain activity has revolutionized our understanding of brain function (Corbetta and Shulman, 2002; Zhang and Raichle, 2010; Power et al., 2011; Yeo et al., 2011). Brain imaging via positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and, more recently, diffuse optical tomography (DOT) have illuminated many aspects of the biological basis of human behavior. Brain systems that support all aspects of cognition – from sensing the visual world, to generating language, to interacting socially, to daydreaming or sleeping – are accessible to quantitative investigation because of these techniques (Petersen et al., 1988; Corbetta and Shulman, 2002; Raichle, 2010). Further, brain imaging has proven useful in clinical investigations of brain function. Specifically, several neurological disorders manifest as measurable alterations in distributed brain networks, including degenerative diseases such as Alzheimer’s disease (Buckner et al., 2009), neurodevelopmental disorders such as autism spectrum disorder (ASD) (Kennedy and Courchesne, 2008; Eggebrecht et al., 2017; Marrus et al., 2017), or disorders due to an insult such as ischemic stroke (Carter et al., 2012; Baldassarre et al., 2016). While many clinical disorders are known to manifest in the brain, optimizing neuroimaging technologies as tools for understanding these disorders and tracking their progression presents significant challenges.
