Most studies involving spontaneous fluctuations in the BOLD signal extract connectivity patterns that show relationships between brain areas that are maintained over the length of the scanning session. In this study, however, we examine the spatiotemporal dynamics of the BOLD fluctuations to identify common patterns of propagation within a scan. A novel pattern finding algorithm was developed for detecting repeated spatiotemporal patterns in BOLD fMRI data. The algorithm was applied to high temporal resolution T2*-weighted multislice images obtained from rats and humans in the absence of any task or stimulation. In rats, the primary pattern consisted of waves of high signal intensity, propagating in a lateral to medial direction across the cortex, replicating our previous findings (Majeed et al., 2009a). These waves were observed primarily in sensorimotor cortex, but also extended to visual and parietal association areas. A secondary pattern, confined to subcortical regions consisted of an initial increase and subsequent decrease in signal intensity in the caudate-putamen. In humans, the most common spatiotemporal pattern consisted of an alteration between activation of areas comprising the "default-mode" (e.g., posterior cingulate and anterior medial prefrontal cortices) and the "task-positive" (e.g., superior parietal and premotor cortices) networks. Signal propagation from focal starting points was also observed. The pattern finding algorithm was shown to be reasonably insensitive to the variation in user-defined parameters, and the results were consistent within and between subjects. This novel approach for probing the spontaneous network activity of the brain has implications for the interpretation of conventional functional connectivity studies, and may increase the amount of information that can be obtained from neuroimaging data.

A better understanding of how behavioral performance emerges from interacting brain systems may come from analysis of functional networks using functional magnetic resonance imaging. Recent studies comparing such networks with human behavior have begun to identify these relationships, but few have used a time scale small enough to relate their findings to variation within a single individual's behavior. In the present experiment we examined the relationship between a psychomotor vigilance task and the interacting default mode and task positive networks. Two time-localized comparative metrics were calculated: difference between the two networks' signals at various time points around each instance of the stimulus (peristimulus times) and correlation within a 12.3-s window centered at each peristimulus time. Correlation between networks was also calculated within entire resting-state functional imaging runs from the same individuals. These metrics were compared with response speed on both an intraindividual and an interindividual basis. In most cases, a greater difference or more anticorrelation between networks was significantly related to faster performance. While interindividual analysis showed this result generally, using intraindividual analysis it was isolated to peristimulus times 4 to 8 s before the detected target. Within that peristimulus time span, the effect was stronger for individuals who tended to have faster response times. These results suggest that the relationship between functional networks and behavior can be better understood by using shorter time windows and also by considering both intraindividual and interindividual variability.

We examined the sequential modulation of congruency effects using a task in which the irrelevant information shares the same stimulus dimensions as the relevant information but is presented at an earlier time. In Experiment 1, sequential modulations were observed within a stimulus modality but not between stimulus modalities. In Experiment 2, sequential modulations were observed across two sets of visual stimuli, even though the two sets involved distinct stimulus dimensions. Experiment 3 used the same stimuli as Experiment 2, but required different responses for the two sets of stimuli. In this case, sequential modulations were specific to the stimulus set. In Experiment 4, two stimulus sets were presented along two stimulus modalities, and sequential modulations crossed both set and modality boundaries. These results suggest that control processes obey flexible boundaries defined by task constraints.

Structural and functional imaging studies have been among converging lines of evidence demonstrating the importance of the hippocampus in successful memory performance. The advent of a novel neuroimaging technique – magnetic resonance elastography (MRE) – now makes it possible for us to investigate the relationship between the microstructural integrity of hippocampal tissue and successful memory processing. Mechanical properties of brain tissue estimated with MRE provide a measure of the integrity of the underlying tissue microstructure and have proven to be sensitive measures of tissue health in neurodegeneration. However, until recently, MRE methods lacked sufficient resolution necessary to accurately examine specific neuroanatomical structures in the brain, and thus could not contribute to examination of specific structure-function relationships. In this study, we took advantage of recent developments in MRE spatial resolution and mechanical inversion techniques to measure the viscoelastic properties of the human hippocampus in vivo, and investigated how these properties reflect hippocampal function. Our data reveal a strong relationship between relative elastic/viscous behavior of the hippocampus and relational memory performance (N = 20). This is the first report linking the mechanical properties of brain tissue with functional performance.

The positive relationship between hippocampal structure, aerobic fitness, and memory performance is often observed among children and older adults; but evidence of this relationship among young adults, for whom the hippocampus is neither developing nor atrophying, is less consistent. Studies have typically relied on hippocampal volumetry (a gross proxy of tissue composition) to assess individual differences in hippocampal structure. While volume is not specific to microstructural tissue characteristics, microstructural differences in hippocampal integrity may exist even among healthy young adults when volumetric differences are not diagnostic of tissue health or cognitive function. Magnetic resonance elastography (MRE) is an emerging noninvasive imaging technique for measuring viscoelastic tissue properties and provides quantitative measures of tissue integrity. We have previously demonstrated that individual differences in hippocampal viscoelasticity are related to performance on a relational memory task; however, little is known about health correlates to this novel measure. In the current study, we investigated the relationship between hippocampal viscoelasticity and cardiovascular health, and their mutual effect on relational memory in a group of healthy young adults (N=51). We replicated our previous finding that hippocampal viscoelasticity correlates with relational memory performance. We extend this work by demonstrating that better aerobic fitness, as measured by VO2max, was associated with hippocampal viscoelasticity that mediated the benefits of fitness on memory function. Hippocampal volume, however, did not account for individual differences in memory. Therefore, these data suggest that hippocampal viscoelasticity may provide a more sensitive measure to microstructural tissue organization and its consequences to cognition among healthy young adults.