NeuroImage
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A powerful, non-invasive technique for estimating and visualizing white matter tracts in the human brain in vivo is white matter fiber tractography that uses magnetic resonance diffusion tensor imaging. The success of this method depends strongly on the capability of the applied tracking algorithm and the quality of the underlying data set. However, DTI-based fiber tractography still lacks standardized validation. ⋯ Second, fMRI-guided DTI fiber tracking was performed to generate DTI-based somatotopic maps, using a standard line propagation and an advanced fast marching algorithm. The results show that the fiber connections reconstructed by the advanced fast marching algorithm are in good agreement with known anatomy, and that the DTI-revealed somatotopy is similar to the fMRI somatotopy. Furthermore, the study illustrates that the combination of fMRI with DTI can supply additional information in order to choose reasonable seed regions for generating functionally relevant networks and to validate reconstructed fibers.
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Q-ball imaging has the ability to discriminate multiple intravoxel fiber populations within regions of complex white matter architecture. This information can be used for fiber tracking; however, diffusion MR is susceptible to noise and multiple other sources of uncertainty affecting the measured orientation of fiber bundles. The proposed residual bootstrap method utilizes a spherical harmonic representation for high angular resolution diffusion imaging (HARDI) data in order to estimate the uncertainty in multimodal q-ball reconstructions. ⋯ The residual bootstrap method was then used in combination with q-ball imaging to construct a probabilistic streamline fiber tracking algorithm. The residual bootstrap q-ball fiber tracking algorithm is capable of following the corticospinal tract and corpus callosum through regions of crossing white matter tracts in the centrum semiovale. This fiber tracking algorithm is an improvement upon prior diffusion tensor methods and the q-ball data can be acquired in a clinically feasible time frame.
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Pain requires the integration of sensory, cognitive, and affective information. The use of placebo is a common methodological ploy in many fields, including pain. Neuroimaging studies of pain and placebo analgesia (PA) have yet to identify a mechanism of action. ⋯ Deviations from the B1 model in the PA and PM conditions correspond to our manipulation of expectation for pain. The dynamic changes in inter-regional influence across conditions are interpreted in the context of a self-reinforcing feedback loop involved in the induction and maintenance of PA. Although it is likely that placebo analgesia results partly from afferent inhibition of a nociceptive signal, the mechanisms likely involve the interaction of a cognitive-affective network with input from both hemispheres.
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Many techniques to study early functional brain development lack the whole-brain spatial resolution that is available with fMRI. We utilized a relatively novel method in which fMRI data were collected from children during natural sleep. Stimulus-evoked responses to auditory and visual stimuli as well as stimulus-independent functional networks were examined in typically developing 2-4-year-old children. ⋯ In sum, 2-4 year olds showed a differential fMRI response both between stimulus modalities and between stimuli in the auditory modality. Furthermore, superior temporal regions showed functional connectivity with numerous higher-order regions during sleep. We conclude that the use of sleep fMRI may be a valuable tool for examining functional brain organization in young children.
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This paper describes DARTEL, which is an algorithm for diffeomorphic image registration. It is implemented for both 2D and 3D image registration and has been formulated to include an option for estimating inverse consistent deformations. ⋯ A constant Eulerian velocity framework is used, which allows a rapid scaling and squaring method to be used in the computations. DARTEL has been applied to intersubject registration of 471 whole brain images, and the resulting deformations were evaluated in terms of how well they encode the shape information necessary to separate male and female subjects and to predict the ages of the subjects.