Extracting Reproducible Time-Resolved Resting State Networks Using Dynamic Mode Decomposition.

Resting state networks (RSNs) extracted from functional magnetic resonance imaging (fMRI) scans are believed to reflect the intrinsic organization and network structure of brain regions. Most traditional methods for computing RSNs typically assume these functional networks are static throughout the duration of a scan lasting 5-15 min. However, they are known to vary on timescales ranging from seconds to years; in addition, the dynamic properties of RSNs are affected in a wide variety of neurological disorders. Recently, there has been a proliferation of methods for characterizing RSN dynamics, yet it remains a challenge to extract reproducible time-resolved networks. In this paper, we develop a novel method based on dynamic mode decomposition (DMD) to extract networks from short windows of noisy, high-dimensional fMRI data, allowing RSNs from single scans to be resolved robustly at a temporal resolution of seconds. After validating the method on a synthetic dataset, we analyze data from 120 individuals from the Human Connectome Project and show that unsupervised clustering of DMD modes discovers RSNs at both the group (gDMD) and the single subject (sDMD) levels. The gDMD modes closely resemble canonical RSNs. Compared to established methods, sDMD modes capture individualized RSN structure that both better resembles the population RSN and better captures subject-level variation. We further leverage this time-resolved sDMD analysis to infer occupancy and transitions among RSNs with high reproducibility. This automated DMD-based method is a powerful tool to characterize spatial and temporal structures of RSNs in individual subjects.

Using Make for Reproducible and Parallel Neuroimaging Workflow and Quality-Assurance.

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.

Measurement of T1 of human arterial and venous blood at 7T.

Techniques for measuring cerebral perfusion require accurate longitudinal relaxation (T1) of blood, an MRI parameter that is field dependent. T1 of arterial and venous human blood was measured at 7T using three different sources - pathology laboratory, blood bank and in vivo. The T1 of venous blood was measured from sealed samples from a pathology lab and in vivo. Samples from a blood bank were oxygenated and mixed to obtain different physiological concentrations of hematocrit and oxygenation. T1 relaxation times were estimated using a three-point fit to a simple inversion recovery equation. At 37°C, the T1 of blood at arterial pO2 was 2.29±0.1s and 2.07±0.12 at venous pO2. The in vivo T1 of venous blood, in three subjects, was slightly longer at 2.45±0.11s. T1 of arterial and venous blood at 7T was measured and found to be significantly different. The T1 values were longer in vivo than in vitro. While the exact cause for the discrepancy is unknown, the additives in the blood samples, degradation during experiment, oxygenation differences, and the non-stagnant nature of blood in vivo could be potential contributors to the lower values of T1 in the venous samples.