NeuroImage
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Multimodal imaging improves the accuracy of the localization and the quantification of brain activation when measuring different manifestations of the hemodynamic response associated with cerebral activity. In this study, we incorporated cerebral blood flow (CBF) changes measured with arterial spin labeling (ASL), Diffuse Optical Tomography (DOT) and blood oxygen level-dependent (BOLD) recordings to reconstruct changes in oxy- (ΔHbO(2)) and deoxyhemoglobin (ΔHbR). Using the Grubb relation between relative changes in CBF and cerebral blood volume (CBV), we incorporated the ASL measurement as a prior to the total hemoglobin concentration change (ΔHbT). ⋯ Moreover, our approach allows the computation of baseline total hemoglobin concentration (HbT(0)) as well as of the BOLD calibration factor M on a single subject basis. We obtained an average HbT(0) of 71 μM, an average M value of 0.18 and an average increase of 13% in cerebral metabolic rate of oxygen (CMRO(2)), all of which are in agreement with values previously reported in the literature. Our method yields an independent measurement of M, which provides an alternative measurement to validate the hypercapnic calibration of the BOLD signal.
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This paper presents a method for automatic segmentation of white matter fiber bundles from massive dMRI tractography datasets. The method is based on a multi-subject bundle atlas derived from a two-level intra-subject and inter-subject clustering strategy. This atlas is a model of the brain white matter organization, computed for a group of subjects, made up of a set of generic fiber bundles that can be detected in most of the population. ⋯ An atlas bundle is represented by the multi-subject list of the centroids of all intra-subject clusters in order to get a good sampling of the shape and localization variability. The atlas, composed of 36 known deep white matter bundles and 47 superficial white matter bundles in each hemisphere, was inferred from a first database of 12 brains. It was successfully used to segment the deep white matter bundles in a second database of 20 brains and most of the superficial white matter bundles in 10 subjects of the same database.
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The perception of airways irritation is represented in a distributed brain network. However, the functional roles of sub-regions of this network are yet to be determined. The aim of this study was to measure brain activation in healthy participants as they inhaled two doses of capsaicin to identify dose-dependent and dose-independent responses. ⋯ Activation in the somatosensory and mid-cingulate cortices correlated with ratings of urge-to-cough. In the brainstem, capsaicin produced dose-dependent activations in respiratory-related regions of the dorsal pons and lateral medulla. These data show dissociable response patterns to capsaicin inhalation that may represent different regional processes involved in monitoring and assessing stimulus intensity, determining the spatial localization of the stimulus and suppressing motor responses.
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Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild (and some moderate) TBI can be difficult to diagnose because the injuries are often not detectable on conventional MRI or CT. Injured brain tissues in TBI patients generate abnormal low-frequency magnetic activity (ALFMA, peaked at 1-4 Hz) that can be measured and localized by magnetoencephalography (MEG). ⋯ Among 96 cortical regions, the likelihood of abnormal slow-wave generation was less in the mild TBI patients with blast than in the mild non-blast TBI patients, suggesting possible protective effects due to the military helmet and armor. Finally, the number of cortical regions that generated abnormal slow-waves correlated significantly with the total post-concussive symptom scores in TBI patients. This study provides a foundation for using MEG low-frequency source imaging to support the clinical diagnosis of TBI.
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To improve the sensitivity and specificity of simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) it is prudent to devise modelling strategies explaining the residual variance. The purpose of this study is to investigate the potential value of including additional regressors for physiological activities, derived from video-EEG, in the modelling of haemodynamic patterns linked to interictal epileptiform discharges (IEDs) using simultaneously recorded video-EEG-fMRI. ⋯ BOLD changes relating to physiological activities were generally seen in expected brain areas. In patients with focal epilepsy, the extent and Z-score of the IED-related global maximum BOLD clusters increased in 4/6 patients and additional IED-related BOLD clusters were observed in 3/6 patients for GLM2. Also, the degree of concordance of IED-related maps with irritative zone improved for one patient for GLM2 and was unchanged for the other cases. In patients with IGE, the size and statistical significance for global maximum and other BOLD clusters increased in 2/4 patients. We conclude that the inclusion of additional regressors, derived from video based information, in the design matrix explains a greater amount of variance and can reveal additional IED-related BOLD clusters which may be part of the epileptic networks.