NeuroImage
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Disruption of cortical connectivity likely contributes to loss of consciousness (LOC) during both sleep and general anesthesia, but the degree of overlap in the underlying mechanisms is unclear. Both sleep and anesthesia comprise states of varying levels of arousal and consciousness, including states of largely maintained conscious experience (sleep: N1, REM; anesthesia: sedated but responsive) as well as states of substantially reduced conscious experience (sleep: N2/N3; anesthesia: unresponsive). Here, we tested the hypotheses that (1) cortical connectivity will exhibit clear changes when transitioning into states of reduced consciousness, and (2) these changes will be similar for arousal states of comparable levels of consciousness during sleep and anesthesia. ⋯ Secondary analyses indicated similarities in reorganization of cortical connectivity in sleep and anesthesia. Shifts from temporal to frontal cortical connectivity may reflect impaired sensory processing in states of reduced consciousness. The data indicate that functional connectivity can serve as a biomarker of arousal state and suggest common mechanisms of LOC in sleep and anesthesia.
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Many factors can contribute to the reliability and robustness of MRI-derived metrics. In this study, we assessed the reliability and reproducibility of three MRI modalities after an MRI scanner was relocated to a new hospital facility. ⋯ Cortical gray matter perfusion was the most variable metric investigated (necessitating large sample sizes to identify group differences), with other metrics showing substantially less variability. Scanner relocation appeared to have a negligible effect on variability of the global MRI metrics tested. This manuscript reports within-site test-retest variability to act as a tool for calculating sample size in future investigations. Our results suggest that when all other parameters are held constant (e.g., sequence parameters and MRI processing), the effect of scanner relocation is indistinguishable from within-site variability, but may need to be considered depending on the question being investigated.
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Visualizing gradual changes in neuromelanin distribution within the substantia nigra is an important metric used to monitor the progression of Parkinsonism. This study aimed to identify the origin of the mismatch region between magnetic resonance transverse relaxation times (T2 and T2*) in the substantia nigra and investigate its feasibility and implications for in vivo detection of neuromelanin as a clinical biomarker. The relationships between neuromelanin distribution assessed by histological staining and the area of T2 and T2* mismatch determined by high- and low-resolution magnetic resonance relaxometry at 7T were directly compared in two normal and one depigmented substantia nigra collected at postmortem. ⋯ In preliminary in vivo studies, a similar, linear T2 and T2* mismatch region was observed in the dorsal area of the substantia nigra in eight normal subjects; this mismatch was significantly obscured in eight Parkinson's disease patients. The length of the dorsal linear mismatch line based on the T2*-T2 mask was significantly shorter in the Parkinson's disease patients compared to normal controls; this result was corroborated by reduced striatal uptake of [18F] FP-CIT dopamine transporters assessed by positron emission tomography scans. In conclusion, the measurement of T2 and T2* mismatch could serve as a complementary imaging biomarker to visualize the dorsal region of the substantia nigra pars compacta, which contains large amounts of neuromelanin.
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Based on a deep learning neural network (NN) algorithm, a super fast and easy to implement data analysis method was proposed for myelin water imaging (MWI) to calculate the myelin water fraction (MWF). ⋯ The time for accurate MWF calculation can be dramatically reduced to less than 1 min by the proposed NN, addressing one of the barriers facing future clinical feasibility of MWI.
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A proposed mechanism of chronic pain is dysregulation between the main inhibitory (GABA) and excitatory (glutamate) neurometabolites of the central nervous system. The level of these neurometabolites appears to differ in individual studies of people with pain compared to pain-free controls across different pain conditions. However, this has yet to be systematically investigated. ⋯ These results support the theory that underlying neurometabolite levels may be unique in different pain conditions and therefore representative of biomarkers for specific pain conditions.