A Fiber Tractography Study of Social-Emotional Related Fiber Tracts in Children and Adolescents with Autism Spectrum Disorder

The symptoms of autism spectrum disorder（ASD） have been hypothesized to be caused by changes in brain connectivity. From the clinical perspective, the‘‘disconnectivity＇＇ hypothesis has been used to explain characteristic impairments in ‘‘socio-emotional＇＇ function.Therefore, in this study we compared the facial emotional recognition（FER） feature and the integrity of socialemotional-related white-matter tracts between children and adolescents with high-functioning ASD（HFA） and their typically developing（TD） counterparts. The correlation between the two factors was explored to find out if impairment of the white-matter tracts is the neural basis of social-emotional disorders. Compared with the TD group,FER was significantly impaired and the fractional anisotropy value of the right cingulate fasciculus was increased in the HFA group（P ／ 0.01）. In conclusion, the FER function of children and adolescents with HFA was impaired and the microstructure of the cingulate fasciculus had abnormalities.

A new computational approach for modeling diffusion tractography in the brain

Computational models provide additional tools for studying the brain,however,many techniques are currently disconnected from each other.There is a need for new computational approaches that span the range of physics operating in the brain.In this review paper,we offer some new perspectives on how the embedded element method can fill this gap and has the potential to connect a myriad of modeling genre.The embedded element method is a mesh superposition technique used within finite element analysis.This method allows for the incorporation of axonal fiber tracts to be explicitly represented.Here,we explore the use of the approach beyond its original goal of predicting axonal strain in brain injury.We explore the potential application of the embedded element method in areas of electrophysiology,neurodegeneration,neuropharmacology and mechanobiology.We conclude that this method has the potential to provide us with an integrated computational framework that can assist in developing improved diagnostic tools and regeneration technologies.

Feasibility of 3.0 T diffusion-weighted nuclear magnetic resonance imaging in the evaluation of functional recovery of rats with complete spinal cord injury

Diffusion tensor imaging is a sensitive way to reflect axonal necrosis and degeneration, glial cell regeneration and demyelination following spinal cord injury, and to display microstructure changes in the spinal cord in vivo. Diffusion tensor imaging technology is a sensitive method to diagnose spinal cord injury; fiber tractography visualizes the white matter fibers, and directly displays the structural integrity and resultant damage of the fiber bundle. At present, diffusion tensor imaging is restricted to brain examinations, and is rarely applied in the evaluation of spinal cord injury. This study aimed to explore the fractional anisotropy and apparent diffusion coefficient of diffusion tensor magnetic resonance imaging and the feasibility of diffusion tensor tractography in the evaluation of complete spinal cord injury in rats. The results showed that the average combined scores were obviously decreased after spinal cord transection in rats, and then began to increase over time. The fractional anisotropy scores after spinal cord transection in rats were significantly lower than those in normal rats （P 〈 0.05）; the apparent diffusion coefficient was significantly increased compared with the normal group （P 〈 0.05）. Following spinal cord transection, fractional anisotropy scores were negatively correlated with apparent diffusion coefficient values （r = -0.856, P 〈 0.01）, and positively correlated with the average combined scores （r = 0.943, P 〈 0.01）, while apparent diffusion coefficient values had a negative correlation with the average combined scores （r = -0.949, P 〈 0.01）. Experimental findings suggest that, as a non-invasive examination, diffusion tensor magnetic resonance imaging can provide qualita- tive and quantitative information about spinal cord injury. The fractional anisotropy score and apparent diffusion coefficient have a good correlation with the average combined scores, which reflect functional recovery after spinal cord injury.