NeuroImage
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Although often ignored in fMRI studies, moment-to-moment variability of blood oxygenation level dependent (BOLD) signals reveals important information about brain function. Indeed, higher brain signal variability has been associated with better cognitive performance in young adults compared to children and elderly adults. Functional connectivity, a very common approach in resting-state fMRI analysis, is scaled for variance. ⋯ Positive connectivity of the PCC within the default mode network as well as negative connectivity towards the frontoparietal network were weaker in patients with 22q11.2DS. We furthermore showed that lower functional connectivity of the PCC was not driven by higher BOLD signal variability. Our results confirm the strong implication of BOLD variance in aging and give an initial insight in its relationship with functional connectivity in the DMN.
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Comparative Study
Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state.
Age-related differences in cognitive agility vary greatly between individuals and cognitive functions. This heterogeneity is partly mirrored in individual differences in brain network connectivity as revealed using resting-state functional magnetic resonance imaging (fMRI), suggesting potential imaging biomarkers for age-related cognitive decline. However, although convenient in its simplicity, the resting state is essentially an unconstrained paradigm with minimal experimental control. ⋯ Further, machine learning revealed stronger differentiation between rest and task in young compared to older individuals, supporting the notion of network dedifferentiation in cognitive aging. Task-modulation in edgewise FC was primarily observed between attention- and sensorimotor networks; with decreased negative correlations between attention- and default mode networks in older adults. These results demonstrate that the magnitude and configuration of age-related differences in brain functional connectivity are partly dependent on cognitive context and load, which emphasizes the importance of assessing brain connectivity differences across a range of cognitive contexts beyond the resting-state.
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Anesthesia-induced changes in functional connectivity and cerebral blow flow (CBF) in large-scale brain networks have emerged as key markers of reduced consciousness. However, studies of functional connectivity disagree on which large-scale networks are altered or preserved during anesthesia, making it difficult to find a consensus amount studies. Additionally, pharmacological alterations in CBF could amplify or occlude changes in connectivity due to the shared variance between CBF and connectivity. ⋯ Nevertheless changes in connectivity and CBF between the awake and deep sedation condition were only significantly correlated in a subsystem of the DMN, suggesting that, while there is significant shared variance between the modalities, changes due to propofol are relatively unique. Similar, but less significant, results were observed in the CBF-adjusted ICD analysis, providing additional evidence that connectivity differences were not fully explained by CBF. In conclusion, these results provide further evidence of alterations in large-scale brain networks are associated with reduced consciousness and suggest that different modalities capture unique aspects of these large scale changes.
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High-resolution diffusion-weighted imaging (DWI) has great potential to provide unique information about tissue microstructure in-vivo. Although single-shot echo-planar imaging (EPI) is a most popular tool for DWI, its application for high-resolution DWI is limited due to T2* blurring and susceptibility- and eddy-current-induced geometric distortions, especially at ultra-high field (UHF) such as 7T. In this study, we adapt a hybrid spin-warp and echo-planar encoding strategy inspired by point spread function (PSF) mapping and optimize it for high-resolution and distortion-free diffusion imaging applications. ⋯ In addition, variable k-space spacing was applied in the PSF dimension and combined with parallel imaging in the EPI-PE dimension to further accelerate the PSF acquisition. The results demonstrate that this method can yield isotropic submillimeter resolution without T2* blurring and geometric distortions at 7T and enables a clear and detailed delineation of human brain structures in-vivo with the diffusion contrasts. In addition, results of the proposed approach for high-resolution diffusion imaging at 3T are presented.
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Alzheimer disease (AD) affects at least 5 million individuals in the USA alone stimulating an intense search for disease prevention and treatment therapies as well as for diagnostic techniques allowing early identification of AD during a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals. ⋯ We have demonstrated that GEPCI provides a new approach for the in vivo evaluation of AD-related tissue pathology in the preclinical and early symptomatic stages of AD. Since MRI is a widely available technology, the GEPCI surrogate markers of AD pathology have a potential for improving the quality of AD diagnostic, and the evaluation of new disease-modifying therapies.