Abstract
Functional magnetic resonance imaging (fMRI) provides an opportunity to indirectly observe neural activity noninvasively in the human brain as it changes in near real time. Most fMRI experiments measure the blood oxygen-level dependent (BOLD) signal, which rises to a peak several seconds after a brain area becomes active. Several experimental designs are common in fMRI research. Block designs alternate periods in which subjects perform some task with periods of rest, whereas event-related designs present the subject with a set of discrete trials. After the fMRI experiment is complete, pre-processing analyses prepare the data for task-related analyses. The most popular task-related analysis uses the General Linear Model to correlate a predicted BOLD response with the observed activity in each brain region. Regions where this correlation is high are identified as task related. Connectivity analysis then tries to identify active regions that belong to the same functional network. In contrast, multivariate methods, such as independent component analysis and multi-voxel pattern analysis identify networks of event-related regions, rather than single regions, so they simultaneously address questions of functional connectivity.
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Acknowledgments
This research was supported in part by AFOSR grant FA9550-12-1-0355 and by the U.S. Army Research Office through the Institute for Collaborative Biotechnologies under grant W911NF-07-1-0072.
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Ashby, F. (2015). An Introduction to fMRI. In: Forstmann, B., Wagenmakers, EJ. (eds) An Introduction to Model-Based Cognitive Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2236-9_5
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