NDLI: Statistical analysis of high density diffuse optical tomography

Content Provider	PubMed Central
Author	Hassanpour, Mahlega S. White, Brian R. Eggebrecht, Adam T. Ferradal, Silvina L. Snyder, Abraham Z. Culver, Joseph P.
Abstract	High density diffuse optical tomography (HD-DOT) is a noninvasive neuroimaging modality with moderate spatial resolution and localization accuracy. Due to portability and wear-ability advantages, HD-DOT has the potential to be used in populations that are not amenable to functional magnetic resonance imaging (fMRI), such as hospitalized patients and young children. However, whereas the use of event-related stimuli designs, general linear model (GLM) analysis, and imaging statistics are standardized and routine with fMRI, such tools are not yet common practice in HD-DOT. In this paper we adapt and optimize fundamental elements of fMRI analysis for application to HD-DOT. We show the use of event-related protocols and GLM de-convolution analysis in un-mixing multi-stimuli event-related HD-DOT data. Statistical parametric mapping (SPM) in the framework of a general linear model is developed considering the temporal and spatial characteristics of HD- DOT data. The statistical analysis utilizes a random field noise model that incorporates estimates of the local temporal and spatial correlations of the GLM residuals. The multiple-comparison problem is addressed using a cluster analysis based on non-stationary Gaussian random field theory. These analysis tools provide access to a wide range of experimental designs necessary for the study of the complex brain functions. In addition, they provide a foundation for understanding and interpreting HD-DOT results with quantitative estimates for the statistical significance of detected activation foci.
Related Links	http://dx.doi.org/10.1016/j.neuroimage.2013.05.105
Ending Page	116
Page Count	13
Starting Page	104
File Format	PDF
ISSN	10538119
e-ISSN	10959572
Journal	NeuroImage
Issue Number	0 1
Volume Number	85
Language	English
Publisher Date	2014-01-01
Access Restriction	Open
Subject Keyword	Cognitive Neuroscience Neurology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Neurology Cognitive Neuroscience

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