Robyn L. Miller

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Recent years have witnessed a rapid growth of interest in moving functional magnetic resonance imaging (fMRI) beyond simple scan-length averages and into approaches that capture time-varying properties of connectivity. In this Perspective we use the term "chronnectome" to describe metrics that allow a dynamic view of coupling. In the chronnectome, coupling(More)
The association between cognitive performance and general functioning in depression is controversial. The present study evaluated the association between cognitive dysfunction and major depressive disorder (MDD, N=70) as compared with age- and gender-matched healthy controls (n=206) and its relationship to general functioning (physical and mental health(More)
Brain lateralization is a widely studied topic, however there has been little work focused on lateralization of intrinsic networks (regions showing similar patterns of covariation among voxels) in the resting brain. In this study, we evaluate resting state network lateralization in an age and gender-balanced functional magnetic resonance imaging (fMRI)(More)
Many approaches for estimating functional connectivity among brain regions or networks in fMRI have been considered in the literature. More recently, studies have shown that connectivity which is usually estimated by calculating correlation between time series or by estimating coherence as a function of frequency has a dynamic nature, during both task and(More)
Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity(More)
Graph theory-based analysis has been widely employed in brain imaging studies, and altered topological properties of brain connectivity have emerged as important features of mental diseases such as schizophrenia. However, most previous studies have focused on graph metrics of stationary brain graphs, ignoring that brain connectivity exhibits fluctuations(More)
Independent component analysis (ICA) is a widely applied technique to derive functionally connected brain networks from fMRI data. Group ICA (GICA) and Independent Vector Analysis (IVA) are extensions of ICA that enable users to perform group fMRI analyses; however a full comparison of the performance limits of GICA and IVA has not been investigated. Recent(More)
A high-resolution structure of a ligand-bound, soluble form of human monoglyceride lipase (MGL) is presented. The structure highlights a novel conformation of the regulatory lid-domain present in the lipase family as well as the binding mode of a pharmaceutically relevant reversible inhibitor. Analysis of the structure lacking the inhibitor indicates that(More)
A fine-structure study of the hamster fungiform, foliate and vallate taste buds was undertaken for comparative purposes. All three taste bud types shared in common composition of the dark cells, light cells, basal cells, nerve fibers and nerve endings and undifferentiated peripheral cells, but morphological difference existed among them. The foliate and(More)