Modeling Change in the Brain: methods for cross-sectional and longitudinal data

Philip T. Reiss; Ciprian M. Crainiceanu; Wesley K. Thompson; Lan Huo

doi:https://doi.org/10.1201/9781315373652-19

Modeling Change in the Brain: methods for cross-sectional and longitudinal data

Philip T. Reiss, Ciprian M. Crainiceanu, Wesley K. Thompson, Lan Huo

Department of Statistics

University of Haifa

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Change in the human brain takes many forms, which are studied in various biomedical fields including neurology, psychiatry, developmental psychology and radiology. Imaging studies, in particular using magnetic resonance imaging (MRI), have helped to characterize the typical course of brain development in early life (e.g., 30), and of brain aging in later life (e.g., 21). With regard to abnormalities of cognition, behavior, and brain health, the focus has depended on the age group being studied: research on disorders of the young has sought to pinpoint anomalies in neurodevelopmental trajectories (e.g., 86), whereas studies of adult disorders have emphasized modeling disease-related brain changes (e.g., 44).

Original language	American English
Title of host publication	Handbook of Neuroimaging Data Analysis
Editors	Hernando Ombao, Martin Lindquist, Wesley Thompson, John Aston
Pages	467-494
Number of pages	28
ISBN (Electronic)	9781315373652
DOIs	https://doi.org/10.1201/9781315373652-19
State	Published - 2016

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title = "Modeling Change in the Brain: methods for cross-sectional and longitudinal data",

abstract = "Change in the human brain takes many forms, which are studied in various biomedical fields including neurology, psychiatry, developmental psychology and radiology. Imaging studies, in particular using magnetic resonance imaging (MRI), have helped to characterize the typical course of brain development in early life (e.g., 30), and of brain aging in later life (e.g., 21). With regard to abnormalities of cognition, behavior, and brain health, the focus has depended on the age group being studied: research on disorders of the young has sought to pinpoint anomalies in neurodevelopmental trajectories (e.g., 86), whereas studies of adult disorders have emphasized modeling disease-related brain changes (e.g., 44).",

author = "Reiss, {Philip T.} and Crainiceanu, {Ciprian M.} and Thompson, {Wesley K.} and Lan Huo",

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doi = "https://doi.org/10.1201/9781315373652-19",

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AU - Thompson, Wesley K.

AU - Huo, Lan

PY - 2016

Y1 - 2016

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AB - Change in the human brain takes many forms, which are studied in various biomedical fields including neurology, psychiatry, developmental psychology and radiology. Imaging studies, in particular using magnetic resonance imaging (MRI), have helped to characterize the typical course of brain development in early life (e.g., 30), and of brain aging in later life (e.g., 21). With regard to abnormalities of cognition, behavior, and brain health, the focus has depended on the age group being studied: research on disorders of the young has sought to pinpoint anomalies in neurodevelopmental trajectories (e.g., 86), whereas studies of adult disorders have emphasized modeling disease-related brain changes (e.g., 44).

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DO - https://doi.org/10.1201/9781315373652-19

M3 - Chapter

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BT - Handbook of Neuroimaging Data Analysis

A2 - Ombao, Hernando

A2 - Lindquist, Martin

A2 - Thompson, Wesley

A2 - Aston, John

ER -

Modeling Change in the Brain: methods for cross-sectional and longitudinal data

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