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Small-world networks, according to Watts and Strogatz, are a class of networks that are ''highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.'' These characteristics result in networks with unique properties of regional specialization with efficient information transfer. Social networks are intuitive examples of this organization, in which cliques or clusters of friends being interconnected but each person is really only five or six people away from anyone else. Although this qualitative definition has prevailed in network science theory, in application, the standard quantitative application is to compare path length (a surrogate measure of distributed processing) and clustering (a surrogate measure of regional specialization) to an equivalent random network. It is demonstrated here that comparing network clustering to that of a random network can result in aberrant findings and that networks once thought to exhibit small-world properties may not. We propose a new small-world metric, x (omega), which compares network clustering to an equivalent lattice network and path length to a random network, as Watts and Strogatz originally described. Example networks are presented that would be interpreted as small-world when clustering is compared to a random network but are not small-world according to x. These findings have important implications in network science because small-world networks have unique topological properties, and it is critical to accurately distinguish them from networks without simultaneous high clustering and short path length.

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis.

Visual and auditory cortices traditionally have been considered to be "modality-specific." Thus, their activity has been thought to be unchanged by information in other sensory modalities. However, using functional magnetic resonance imaging (fMRI), the present experiments revealed that ongoing activity in the visual cortex could be modulated by auditory information and ongoing activity in the auditory cortex could be modulated by visual information. In both cases, this cross-modal modulation of activity took the form of deactivation. Yet, the deactivation response was not evident in either cortical area during the paired presentation of visual and auditory stimuli. These data suggest that cross-modal inhibitory processes operate within traditional modality-specific cortices and that these processes can be switched on or off in different circumstances.

Literature has shown that exercise is beneficial for cognitive function in older adults and that aerobic fitness is associated with increased hippocampal tissue and blood volumes. The current study used novel network science methods to shed light on the neurophysiological implications of exercise-induced changes in the hippocampus of older adults. Participants represented a volunteer subgroup of older adults that were part of either the exercise training (ET) or healthy aging educational control (HAC) treatment arms from the Seniors Health and Activity Research Program Pilot (SHARP-P) trial. Following the 4-month interventions, MRI measures of resting brain blood flow and connectivity were performed. The ET group's hippocampal cerebral blood flow (CBF) exhibited statistically significant increases compared to the HAC group. Novel whole-brain network connectivity analyses showed greater connectivity in the hippocampi of the ET participants compared to HAC. Furthermore, the hippocampus was consistently shown to be within the same network neighborhood (module) as the anterior cingulate cortex only within the ET group. Thus, within the ET group, the hippocampus and anterior cingulate were highly interconnected and localized to the same network neighborhood. This project shows the power of network science to investigate potential mechanisms for exercise-induced benefits to the brain in older adults. We show a link between neurological network features and CBF, and it is possible that this alteration of functional brain networks may lead to the known improvement in cognitive function among older adults following exercise.

SUMMARY:The routine use of arterial spin-labeling (ASL) in a clinical population has led to the depiction of diverse brain pathologic features. Unique challenges in the acquisition, postprocessing, and analysis of cerebral blood flow (CBF) maps are encountered in such a population, and high-quality ASL CBF maps can be generated consistently with attention to quality control and with the use of a dedicated postprocessing pipeline. Familiarity with commonly encountered artifacts can help avoid pitfalls in the interpretation of CBF maps. The purpose of this review was to describe our experience with a heterogeneous collection of ASL perfusion cases with an emphasis on methodology and common artifacts encountered with the technique. In a period of 1 year, more than 3000 pulsed ASL cases were performed as a component of routine clinical brain MR evaluation at both 1.5 and 3T. These ASL studies were analyzed with respect to overall image quality and patterns of perfusion on final gray-scale DICOM images and color Joint Photographic Experts Group (JPEG) CBF maps, and common artifacts and their impact on final image quality were categorized.