NeuroImage
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Decreased cerebral blood volume/flow (CBV/CBF) contributes to negative blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) signals. But it is still strongly debated whether these negative BOLD or CBV/CBF signals are indicative of decreased or increased neuronal activity. The fidelity of Ca(2+) signals in reflecting neuronal excitation is well documented. ⋯ This suggests the importance of input activity other than output in triggering the negative CBV signals. These findings indicate that the striatal negative CBV fMRI signals are associated with Ca(2+) increases and Ca(2+)-dependent signaling along the nigrostriatal pathway. The obtained data reveal a new brain road map in response to nociceptive stimulation of hemodynamic changes in association with Ca(2+) signals within the dopaminergic system.
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Connectivity analyses based on both resting-state (rs-)fMRI and diffusion weighted imaging studies suggest that the human brain contains regions that act as hubs for the entire brain, and that elements of the Default Mode Network (DMN) play a pivotal role in this network. In the present study, the detailed functional and structural connectivity of the DMN was investigated. Resting state fMRI (35 minute duration) and Diffusion Weighted Imaging (DWI) data (256 directions) were acquired from forty-seven healthy subjects at 3 T. ⋯ Hubs with high betweenness centrality were frequently found in association areas of the brain. This approach makes it possible to distinguish the hubs in the DMN as belonging to different anatomical association systems. The start and end points of the fibre tracts coincide with hubs found using the resting state analysis.
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Comparative Study
Quantitative comparison of cortical surface reconstructions from MP2RAGE and multi-echo MPRAGE data at 3 and 7 T.
The Magnetization-Prepared 2 Rapid Acquisition Gradient Echo (MP2RAGE) method achieves spatially uniform contrast across the entire brain between gray matter and surrounding white matter tissue and cerebrospinal fluid by rapidly acquiring data at two points during an inversion recovery, and then combining the two volumes so as to cancel out sources of intensity and contrast bias, making it useful for neuroimaging studies at ultrahigh field strengths (≥7T). To quantify the effectiveness of the MP2RAGE method for quantitative morphometric neuroimaging, we performed tissue segmentation and cerebral cortical surface reconstruction of the MP2RAGE data and compared the results with those generated from conventional multi-echo MPRAGE (MEMPRAGE) data across a group of healthy subjects. To do so, we developed a preprocessing scheme for the MP2RAGE image data to allow for automatic cortical segmentation and surface reconstruction using FreeSurfer and analysis methods to compare the positioning of the surface meshes. ⋯ We also found that the thickness estimates were systematically smaller in the MP2RAGE data, and that both the interior and exterior cortical boundaries estimated from the MP2RAGE data were consistently positioned within the corresponding boundaries estimated from the MEMPRAGE data. Therefore several measureable differences exist in the appearance of cortical gray matter and its effect on automatic segmentation methods that must be considered when choosing an acquisition or segmentation method for studies requiring cortical surface reconstructions. We propose potential extensions to the MP2RAGE method that may help to reduce or eliminate these discrepancies.
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Pain perception is thought to emerge from the integrated activity of a distributed brain system, but the relative contribution of the different network nodes is still incompletely understood. In the present functional magnetic resonance imaging (fMRI) study, we aimed to identify the more relevant brain regions to explain the time profile of the perceived pain intensity in healthy volunteers, during noxious chemical stimulation (ascorbic acid injection) of the left hand. To this end, we performed multi-way partial least squares regression of fMRI data from twenty-two a-priori defined brain regions of interest (ROI) in each hemisphere, to build a model that could efficiently reproduce the psychophysical pain profiles in the same individuals; moreover, we applied a novel three-way extension of the variable importance in projection (VIP) method to summarize each ROI contribution to the model. ⋯ Most of these regions, with the exception of medial thalamus, were also identified by a statistical analysis on mean ROI beta values estimated using the time course of the psychophysical rating as a regressor at the voxel level. Our results provide the first rank-ordering of brain regions involved in coding the perceived level of pain. These findings in a model of acute prolonged pain confirm and extend previous data, suggesting that a bilateral array of cortical areas and subcortical structures is involved in pain perception.
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For practical brain-machine interfaces (BMIs), electroencephalography (EEG) and near-infrared spectroscopy (NIRS) are the only current methods that are non-invasive and available in non-laboratory environments. However, the use of EEG and NIRS involves certain inherent problems. EEG signals are generally a mixture of neural activity from broad areas, some of which may not be related to the task targeted by BMI, hence impairing BMI performance. ⋯ Applying our methodology to a spatial attention task, we found our EEG-NIRS-based decoder exhibited significant performance improvement over decoding methods based on EEG sensor signals alone. The advancement of our methodology, decoding from current sources sparsely isolated on the cortex, was also supported by neuroscientific considerations; intraparietal sulcus, a region known to be involved in spatial attention, was a key responsible region in our task. These results suggest that our methodology is not only a practical option for EEG-NIRS-based BMI applications, but also a potential tool to investigate brain activity in non-laboratory and naturalistic environments.