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Statistical Issues in fMRI for Brain Imaging
Authors:Nicole A. Lazar  William F. Eddy  Christopher R. Genovese  Joel Welling
Affiliation:Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA;Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA;Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA;Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA and Pittsburgh Supercomputing Center, Pittsburgh, PA 15213, USA
Abstract:Functional magnetic resonance imaging is a technique developed in the last decade and used in the fields of cognitive psychology and neuroscience, among others, to study the processes underlying the working of the human brain. In this paper we examine some of the statistical issues in functional magnetic resonance imaging for brain research. We start by giving a brief introduction to the physics of magnetic resonance imaging. Using a psychological experiment as a case study, we then describe questions of design and statistical analysis. The data obtained from functional magnetic resonance imaging studies are of a highly complex nature, displaying both spatial and temporal correlation, as well as high levels of noise from different sources. Given this, the scope for statistics is vast, and is not limited to simple analysis of the data, once collected.
Keywords:Correlated data    Functional neuroimaging    Human brain mapping
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