No 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.

Cerebrovascular disease, especially small vessel pathology, is the leading comorbidity in degenerative disorders. We applied arterial spin labeling and cerebrovascular reserve (CVR) imaging to quantify small vessel disease and study its effect on cognitive symptoms in nondemented older adults from a community-based cohort. We evaluated baseline cerebral blood flow (CBF) using arterial spin labeling and percent signal change as a marker of CVR using blood-oxygen level-dependent imaging following a breath-hold stimulus. Measurements were performed in and near white matter hyperintensities, which are currently the standard to assess severity of vascular pathology. We show that similar to other studies (1) CBF and CVR are markedly reduced in the hyperintensities as well as in the tissue surrounding them, indicating susceptibility to infarction; (2) low CBF and CVR are significantly correlated with poor cognitive performance; and (3) in addition, compared to a 58.4% reduction in CBF, larger exhaustion (79.3%) of CVR was observed in the hyperintensities with a faster, nonlinear rate of decline. We conclude that CVR may be a more sensitive biomarker of small vessel disease than CBF.

The contribution of this paper is to describe how we can program neuroimaging workflow using Make, a software development tool designed for describing how to build executables from source files. A makefile (or a file of instructions for Make) consists of a set of rules that create or update target files if they have not been modified since their dependencies were last modified. These rules are processed to create a directed acyclic dependency graph that allows multiple entry points from which to execute the workflow. We show that using Make we can achieve many of the features of more sophisticated neuroimaging pipeline systems, including reproducibility, parallelization, fault tolerance, and quality assurance reports. We suggest that Make permits a large step toward these features with only a modest increase in programming demands over shell scripts. This approach reduces the technical skill and time required to write, debug, and maintain neuroimaging workflows in a dynamic environment, where pipelines are often modified to accommodate new best practices or to study the effect of alternative preprocessing steps, and where the underlying packages change frequently. This paper has a comprehensive accompanying manual with lab practicals and examples (see Supplemental Materials) and all data, scripts, and makefiles necessary to run the practicals and examples are available in the “makepipelines” project at NITRC.

No abstract