NeuroImage
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Together with a detailed behavioral analysis, simultaneous measurement of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) permits a better elucidation of cortical pain processing. We applied painful electrical stimulation to 6 healthy subjects and acquired fMRI simultaneously with an EEG measurement. The subjects rated various stimulus properties and the individual affective state. ⋯ The BOLD signal change in ACC was positively correlated to the individual dipole strength of the source in ACC thus revealing a close relationship of BOLD signal and possibly underlying neuronal electrical activity in SI and the ACC. The BOLD signal change decreased in SI over time. Dipole strength of the ACC source decreased over the experiment and increased during the stimulation block suggesting sensitization and habituation effects in these areas.
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Alpha-chloralose is commonly used during animal fMRI studies for anesthesia, however, recovery of animals is difficult, limiting experimental design. The use of a less invasive anesthetic would enable chronic experiments. The present study compares functional activity in the spinal cord of the alpha-chloralose and halothane-anesthetized rat. ⋯ The regions and amount of fMRI activity observed were similar for both anesthetics. Functional magnetic resonance imaging of the spinal cord can be achieved using both alpha-chloralose and halothane anesthesia in rats. We therefore suggest that halothane may be used as an anesthetic agent for chronic fMRI studies of the spinal cord.
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Brain nuclei directly receiving retinal projections are readily labeled in magnetic resonance images following intraocular injection of manganese (Mn). To assess whether Mn in retinal ganglion cell axons can be transsynaptically delivered to visual cortex, mice that had previously received intraocular Mn injection were anesthetized with isoflurane, and T1-weighted data sets were acquired of the eyes and brain using a 7-T magnetic resonance imaging machine. Image intensity within contralateral brain structures was evaluated by assessing 1) signal-to-noise ratios, 2) mean image intensity, and 3) mean image intensity normalized to facial muscle intensity. ⋯ Power analysis of the different evaluation methods yielded evidence of superior sensitivity using the normalization method. Reconstruction of the visual system based upon threshold analysis allowed simultaneous visualization of all portions of the major retinal projections to the brain. These results support use of high magnetic field MRI imaging and data normalization for in vivo quantitative analysis of the mouse brain visual system including visual cortex.
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An automated algorithm has been developed to segment stripped (non-brain tissue excluded) T1-weighted MRI brain volumes into left and right cerebral hemispheres and cerebellum+brainstem. The algorithm, which uses the Graph Cuts technique, performs a fully automated segmentation in approximately 30 s following pre-processing. It is robust and accurate and has been tested on datasets from two scanners using different field strengths and pulse sequences. We describe the Graph Cuts algorithm and compare the results of Graph Cuts segmentations against "gold standard" manual segmentations and segmentations produced by three popular software packages used by neuroimagers: BrainVisa, CLASP, and SurfRelax.
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We describe a new algorithm for the automated segmentation of the hippocampus (Hc) and the amygdala (Am) in clinical Magnetic Resonance Imaging (MRI) scans. Based on homotopically deforming regions, our iterative approach allows the simultaneous extraction of both structures, by means of dual competitive growth. One of the most original features of our approach is the deformation constraint based on prior knowledge of anatomical features that are automatically retrieved from the MRI data. ⋯ For 16 young healthy subjects, accuracy is characterised by mean relative volume error/overlap/maximal boundary distance of 7%/84%/4.5 mm for Hc and 12%/81%/3.9 mm for Am; for 8 Alzheimer's disease patients, it is 9%/84%/6.5 mm for Hc and 15%/76%/4.5 mm for Am. We conclude that the performance of this new approach in data from healthy and diseased subjects in terms of segmentation quality, reproducibility and time efficiency compares favourably with that of previously published manual and automated segmentation methods. The proposed approach provides a new framework for further developments in quantitative analyses of the pathological hippocampus and amygdala in MRI scans.