NeuroImage
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Recent research has shown that intrinsic brain activity as observed by functional magnetic resonance imaging (fMRI) manifest itself as coherent signal changes in networks encompassing brain regions that span long-range neuronal pathways. One of these networks, the so called default mode network, has become the primary target in recent investigations to link intrinsic activity to cognition and how intrinsic signal changes may be altered in disease. ⋯ Additionally, we found support for strong interactions between the precuneus/posterior cingulate cortex and the left inferior parietal lobe as well as between the dorsal and ventral sections of the medial prefrontal cortex. The suggested pivotal role of the precuneus/posterior cingulate cortex in the default mode network is discussed.
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Comparative Study
Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images.
The evaluation of atrophy quantification methods based on magnetic resonance imaging have been usually hindered by the lack of realistic gold standard data against which to judge these methods or to help refine them. Recently [Camara, O., Schweiger, M., Scahill, R., Crum, W., Sneller, B., Schnabel, J., Ridgway, G., Cash, D., Hill, D., Fox, N., 2006. Phenomenological model of diffuse global and regional atrophy using finite-element methods. ⋯ Results obtained in our experiments with realistic simulated data confirm previously published estimates of accuracy for both evaluated global techniques. Regarding Jacobian Integration methods, the FFD-based one demonstrated promising results and potential for being used in clinical studies alongside (or in place of) the more common global methods. The generated gold standard data has also allowed us to identify some stages and sets of parameters in the evaluated techniques--the brain extraction step in the global techniques and the number of multi-resolution levels and the stopping criteria in the registration-based methods--that are critical for their accuracy.
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Using functional imaging, we recently investigated how repeated painful stimulation over several days is processed, perceived and modulated in the healthy human brain. Considering that activation-dependent brain plasticity in humans on a structural level has already been demonstrated in adults, we were interested in whether repeated painful stimulation may lead to structural changes of the brain. 14 healthy subjects were stimulated daily with a 20 min pain paradigm for 8 consecutive days, using structural MRI performed on days 1, 8, 22 and again after 1 year. ⋯ These changes are stimulation dependent, i.e. they recede after the regular nociceptive input is stopped. This data raises some interesting questions regarding structural plasticity of the brain concerning the experience of both acute and chronic pain.
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Traumatic brain injury (TBI) is associated with brain volume loss, but there is little information on the regional gray matter (GM) and white matter (WM) changes that contribute to overall loss. Since axonal injury is a common occurrence in TBI, imaging methods that are sensitive to WM damage such as diffusion-tensor imaging (DTI) may be useful for characterizing microstructural brain injury contributing to regional WM loss in TBI. High-resolution T1-weighted imaging and DTI were used to evaluate regional changes in TBI patients compared to matched controls. ⋯ Cross-sectional comparisons of the DTI measures indicated that patients have decreased FA and increased MD compared to controls over large regions of the brain. TBI affected virtually all of the major fiber bundles in the brain including the corpus callosum, cingulum, the superior and inferior longitudinal fascicules, the uncinate fasciculus, and brain stem fiber tracts. The results indicate that both GM and WM degeneration are significant contributors to brain volume loss in the months following brain injury, and also suggest that DTI measures may be more useful than high-resolution anatomical images in assessment of group differences.
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In this paper we introduce a new method to characterize the intravoxel anisotropy based on diffusion-weighted imaging (DWI). The proposed solution, under a fully Bayesian formalism, deals with the problem of joint Bayesian Model selection and parameter estimation to reconstruct the principal diffusion profiles or primary fiber orientations in a voxel. We develop an efficient stochastic algorithm based on the reversible jump Markov chain Monte Carlo (RJMCMC) method in order to perform the Bayesian computation. ⋯ It also gives an empirical posterior distribution of the number of primary nerve fiber orientations given the DWI data. Different probability maps can be assessed using this methodology: 1) the intravoxel fiber orientation map (or orientational distribution function) that gives the probability of finding a fiber in a particular spatial orientation; 2) a three-dimensional map of the probability of finding a particular number of fibers in each voxel; 3) a three-dimensional MaxPro (maximum probability) map that provides the most probable number of fibers for each voxel. In order to study the performance and reliability of the presented approach, we tested it on synthetic data; an ex-vivo phantom of intersecting capillaries; and DWI data from a human subject.