NeuroImage
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The intra- and inter-scanner variability of an automated method for MRI-based volumetry was investigated. Using SPM5 algorithms and predefined masks derived from a probabilistic whole-brain atlas, this method allows to determine the volumes of various brain structures (e.g., hemispheres, lobes, cerebellum, basal ganglia, grey and white matter etc.) in single subjects in an observer-independent fashion. A healthy volunteer was scanned three times at six different MRI scanners (including different vendors and field strengths) to calculate intra- and inter-scanner volumetric coefficients of variation (CV). ⋯ Furthermore, the minimum percentage volume difference for detecting a significant volume change between two volume measurements in the same subject was calculated for each substructure. For example, for the total brain volume, mean intra-scanner, inter-scanner, and overall CV results were 0.50%, 3.78%, and 3.80%, respectively, and the cut-offs for significant volume changes between two measurements in the same subject amounted to 1.4% for measurements on the same scanner and 10.5% on different scanners. These findings may be useful for planning and assessing volumetric studies in neurological diseases, for the differentiation of certain patterns of atrophy, or for longitudinal studies monitoring the course of a disease and potential therapeutic effects.
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Pain and somatosensory processing involves an interaction of multiple neuronal networks. One result of these complex interactions is the presence of differential responses across brain regions that may be incompletely modeled by a straightforward application of standard general linear model (GLM) approaches based solely on the applied stimulus. We examined temporal blood oxygenation-level dependent (BOLD) signatures elicited by two stimulation paradigms (brush and heat) providing innocuous and noxious stimuli. ⋯ The 2EV GLM analysis enabled a more detailed characterization of the elicited BOLD responses, particularly during pain processing. This was confirmed by application of the model to a second, independent cohort[AU1]. Furthermore, the delayed component of the biphasic response was strongly associated with the noxious heat stimuli, suggesting that this may represent a sensitive fMRI link of pain processing.
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Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain. The underlying structural basis of this functional connectivity pattern is still widely unexplored. We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure underlying default mode connectivity. ⋯ In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data. Our findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based on distinct pattern of anatomical connectivity within the cerebral white matter.
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Healthy aging is associated with brain volume reductions that involve the frontal cortex, but also affect other brain regions. We sought to identify an age-related network pattern of MRI gray matter using a multivariate statistical model of regional covariance, the Scaled Subprofile Model (SSM) with voxel based morphometry (VBM) in 29 healthy adults, 23-84 years of age (Group 1). In addition, we evaluated the reproducibility of the age-related gray matter pattern derived from a prior SSM VBM study of 26 healthy adults, 22-77 years of age (Group 2; Alexander et al., 2006) in relation to the current sample and tested the ability of the network analysis to extract an age-related pattern from both cohorts combined. ⋯ The results suggest that healthy aging is associated with a regionally distributed pattern of gray matter atrophy that has reproducible regional features. Whereas the network patterns of atrophy included parietal, temporal, and subcortical regions, involvement of the frontal brain regions showed the most consistently extensive and reliable reductions across samples. Network analysis with SSM VBM can help detect reproducible age-related MRI patterns, assisting efforts in the study of healthy and pathological aging.
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Human functional magnetic resonance imaging (fMRI) evidence suggests the hippocampus is associated with context memory to a greater degree than item memory (where only context memory requires item-in-context binding). A separate line of fMRI research suggests the hippocampus is associated with "remember" responses to a greater degree than "know" or familiarity based responses (where only remembering reflects the subjective experience of specific detail). Previous studies, however, have confounded context memory with remembering and item memory with knowing. ⋯ The analogous pattern of activity that would have supported the remembering hypothesis was never observed in the hippocampus. However, a targeted analysis revealed remembering specific activity in the left inferior parietal cortex. The present results suggest parietal cortex may be associated with subjective remembering while the hippocampus mediates binding.