Current methods and limitations for longitudinal fMRI analysis across development. (October 2018)

• Record Type: Journal Article
• Authors: Madhyastha, Tara; Peverill, Matthew; Koh, Natalie; McCabe, Connor; Flournoy, John; Mills, Kate; King, Kevin; Pfeifer, Jennifer; McLaughlin, Katie A.
• Is Part Of: Developmental cognitive neuroscience. Volume 33(2018)
• Page Start: 118
• Page End: 128
• Publication Date: 2018-10
• Subjects: Longitudinal modeling -- Functional magnetic resonance imaging (fMRI) -- General Linear Model -- Structural Equation Modeling -- Developmental change; Cognitive neuroscience -- Periodicals; Developmental neurobiology -- Periodicals; Neuropsychology -- Periodicals; Neuropsychiatry -- Periodicals; 612.8233
• DOI: 10.1016/j.dcn.2017.11.006
• Languages: English
• ISSNs: 1878-9293

Abstract

Abstract: The human brain is remarkably plastic. The brain changes dramatically across development, with ongoing functional development continuing well into the third decade of life and substantial changes occurring again in older age. Dynamic changes in brain function are thought to underlie the innumerable changes in cognition, emotion, and behavior that occur across development. The brain also changes in response to experience, which raises important questions about how the environment influences the developing brain. Longitudinal functional magnetic resonance imaging (fMRI) studies are an essential means of understanding these developmental changes and their cognitive, emotional, and behavioral correlates. This paper provides an overview of common statistical models of longitudinal change applicable to developmental cognitive neuroscience, and a review of the functionality provided by major software packages for longitudinal fMRI analysis. We demonstrate that there are important developmental questions that cannot be answered using available software. We propose alternative approaches for addressing problems that are commonly faced in modeling developmental change with fMRI data.