NeuroImage
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Cognitive aging is accompanied by a range of structural and functional differences in the brain, even in the absence of neurodegenerative disease. Functional magnetic resonance imaging (fMRI) studies have reported increased bilateral activation during task performance in elderly participants compared to their younger counterparts, particularly in frontal regions. Alterations have also been observed in the functional architecture of the resting brain, suggesting that aging is associated with changes in the organization of the networks of the brain. ⋯ Furthermore, whereas the effects of age on the various RSNs were found independent of age-related decreases in gray matter volume, sex and subject motion, we report strong positive and widespread effects of estimated subject motion on the RSFC across RSNs. The results provide support for the notion of network-specific effects in aging, manifested as increased tonic activation of task-positive networks, supporting higher-order cognitive functions and cognitive control, along with reduced task-negative default mode network and sensory visual networks during rest. The present results also corroborate recent evidence of strong influence of subject motion on estimated functional connectivity measures and strongly suggest that studies using RSFC measures as imaging phenotypes should adjust for individual differences in in-scanner subject motion.
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Proton echo planar spectroscopic imaging (PEPSI) is a fast magnetic resonance spectroscopic imaging (MRSI) technique that allows mapping spatial metabolite distributions in the brain. Although the medial wall of the cortex is involved in a wide range of pathological conditions, previous MRSI studies have not focused on this region. To decide the magnitude of metabolic changes to be considered significant in this region, the reproducibility of the method needs to be established. ⋯ This comes in addition to the loss of sensitivity for other metabolites. Encouraging results were obtained with TE30 compared to other previously reported MRSI studies. The protocols implemented here are reliable and may be used to study disease progression and intervention mechanisms.
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Pain is known to comprise sensory, cognitive, and affective aspects. Despite numerous previous fMRI studies, however, it remains open which spatial distribution of activity is sufficient to encode whether a stimulus is perceived as painful or not. In this study, we analyzed fMRI data from a perceptual decision-making task in which participants were exposed to near-threshold laser pulses. ⋯ The most accurate prediction of pain perception from the stimulation period, however, was enabled by the combined activity in pain regions commonly referred to as the 'pain matrix'. Our results demonstrate that the neural representation of (near-threshold) pain is spatially distributed and can be best described at an intermediate spatial scale. In addition to its utility in establishing structure-function mappings, our approach affords trial-by-trial predictions and thus represents a step towards the goal of establishing an objective neuronal marker of pain perception.
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We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. ⋯ In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation.
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Spinal cord pathology can be functionally very important in neurological disease. Pathological studies have demonstrated the involvement of spinal cord grey matter (GM) and white matter (WM) in several diseases, although the clinical relevance of abnormalities detected histopathologically is difficult to assess without a reliable way to assess cord GM and WM in vivo. In this study, the feasibility of GM and WM segmentation was investigated in the upper cervical spinal cord of 10 healthy subjects, using high-resolution images acquired with a commercially available 3D gradient-echo pulse sequence at 3T. ⋯ The mean scan-rescan, intra- and inter-observer % coefficient of variation for measuring the TCA were 0.7%, 0.5% and 0.5% and for measuring the TGMA were 6.5%, 5.4% and 12.7%. The difference between WM-MTR and GM-MTR was found to be statistically significant (p=0.00006). This study has shown that GM and WM segmentation in the cervical cord is possible and the MR imaging protocol and analysis method presented here in healthy controls can be potentially extended to study the cervical cord in disease states, with the option to explore further quantitative measurements alongside MTR.