scholarly journals Multiple-echo diffusion tensor acquisition technique (MEDITATE) on a 3T clinical scanner

2013 ◽  
Vol 26 (11) ◽  
pp. 1471-1483 ◽  
Author(s):  
Steven H. Baete ◽  
Gene Cho ◽  
Eric E. Sigmund
2016 ◽  
Vol 76 (5) ◽  
pp. 1354-1363 ◽  
Author(s):  
Christopher Nguyen ◽  
Zhaoyang Fan ◽  
Yibin Xie ◽  
Jianing Pang ◽  
Peter Speier ◽  
...  

2005 ◽  
Vol 360 (1457) ◽  
pp. 881-891 ◽  
Author(s):  
Muriel Perrin ◽  
Cyril Poupon ◽  
Bernard Rieul ◽  
Patrick Leroux ◽  
André Constantinesco ◽  
...  

Magnetic resonance (MR) diffusion imaging provides a valuable tool used for inferring structural anisotropy of brain white matter connectivity from diffusion tensor imaging. Recently, several high angular resolution diffusion models were introduced in order to overcome the inadequacy of the tensor model for describing fibre crossing within a single voxel. Among them, q -ball imaging (QBI), inherited from the q -space method, relies on a spherical Radon transform providing a direct relationship between the diffusion-weighted MR signal and the orientation distribution function (ODF). Experimental validation of these methods in a model system is necessary to determine the accuracy of the methods and to optimize them. A diffusion phantom made up of two textile rayon fibre (comparable in diameter to axons) bundles, crossing at 90°, was designed and dedicated to ex vivo q -ball validation on a clinical scanner. Normalized ODFs were calculated inside regions of interest corresponding to monomodal and bimodal configurations of underlying structures. Three-dimensional renderings of ODFs revealed monomodal shapes for voxels containing single-fibre population and bimodal patterns for voxels located within the crossing area. Principal orientations were estimated from ODFs and were compared with a priori structural fibre directions, validating efficiency of QBI for depicting fibre crossing. In the homogeneous regions, QBI detected the fibre angle with an accuracy of 19° and in the fibre-crossing region with an accuracy of 30°.


2006 ◽  
Vol 24 (1) ◽  
pp. 7-18 ◽  
Author(s):  
Eric E. Sigmund ◽  
Yi-Qiao Song

2006 ◽  
Vol 24 (9) ◽  
pp. 605-609 ◽  
Author(s):  
Makoto Watanabe ◽  
Shigeki Aoki ◽  
Yoshitaka Masutani ◽  
Osamu Abe ◽  
Naoto Hayashi ◽  
...  

2020 ◽  
Vol 29 (4) ◽  
pp. 1783-1797
Author(s):  
Kelly L. Coburn ◽  
Diane L. Williams

Purpose Neurodevelopmental processes that begin during gestation and continue throughout childhood typically support language development. Understanding these processes can help us to understand the disruptions to language that occur in neurodevelopmental conditions, such as autism spectrum disorder (ASD). Method For this tutorial, we conducted a focused literature review on typical postnatal brain development and structural and functional magnetic resonance imaging, diffusion tensor imaging, magnetoencephalography, and electroencephalography studies of the neurodevelopmental differences that occur in ASD. We then integrated this knowledge with the literature on evidence-based speech-language intervention practices for autistic children. Results In ASD, structural differences include altered patterns of cortical growth and myelination. Functional differences occur at all brain levels, from lateralization of cortical functions to the rhythmic activations of single neurons. Neuronal oscillations, in particular, could help explain disrupted language development by elucidating the timing differences that contribute to altered functional connectivity, complex information processing, and speech parsing. Findings related to implicit statistical learning, explicit task learning, multisensory integration, and reinforcement in ASD are also discussed. Conclusions Consideration of the neural differences in autistic children provides additional scientific support for current recommended language intervention practices. Recommendations consistent with these neurological findings include the use of short, simple utterances; repetition of syntactic structures using varied vocabulary; pause time; visual supports; and individualized sensory modifications.


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