title: PARAMETRIC REGRESSION SCHEME FOR DISTRIBUTIONS: ANALYSIS OF DTI FIBER TRACT DIFFUSION CHANGES IN EARLY BRAIN DEVELOPMENT.
abstract: Temporal modeling frameworks often operate on scalar variables by summarizing data at initial stages as statistical summaries of the underlying distributions. For instance, DTI analysis often employs summary statistics, like mean, for regions of interest and properties along fiber tracts for population studies and hypothesis testing. This reduction via discarding of variability information may introduce significant errors which propagate through the procedures. We propose a novel framework which uses distribution-valued variables to retain and utilize the local variability information. Classic linear regression is adapted to employ these variables for model estimation. The increased stability and reliability of our proposed method when compared with regression using single-valued statistical summaries, is demonstrated in a validation experiment with synthetic data. Our driving application is the modeling of age-related changes along DTI white matter tracts. Results are shown for the spatiotemporal population trajectory of genu tract estimated from 45 healthy infants and compared with a Krabbe's patient.
authors.affiliation: School of Computing, SCI Institute, University of Utah, Salt Lake City, UT, USA.
authors.forename: Anuja
authors.initials: A
authors.lastname: Sharma
authors.affiliation: School of Computing, SCI Institute, University of Utah, Salt Lake City, UT, USA.
authors.forename: P Thomas
authors.initials: PT
authors.lastname: Fletcher
authors.affiliation: Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
authors.forename: John H
authors.initials: JH
authors.lastname: Gilmore
authors.affiliation: Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Maria L
authors.initials: ML
authors.lastname: Escolar
authors.affiliation: Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA ; Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Aditya
authors.initials: A
authors.lastname: Gupta
authors.affiliation: Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
authors.forename: Martin
authors.initials: M
authors.lastname: Styner
authors.affiliation: School of Computing, SCI Institute, University of Utah, Salt Lake City, UT, USA.
authors.forename: Guido
authors.initials: G
authors.lastname: Gerig
keywords: DTI; distribution-valued data; early neurodevelopment; linear regression; spatiotemporal growth trajectory