Corpus Callosum Functional Activities in Children with Cerebral Palsy.

Background: Since cerebral palsy (CP) is a corollary to brain damage, persistent treatment should accompany an alteration in brain functional activity in line with clinical improvements. In this regard, the corpus callosum (CC), as a connecting bridge between the two hemispheres, plays an essential role. Objective: This study aimed to investigate the therapeutic effects of occupational therapy (OT) on CC functional activity and walking capacity in children with cerebral palsy. Material and Methods: In this clinical trial study, 4 children with CP (8.25±1.71 years) received 45 min OT sessions 3 times weekly for 8 weeks. Functional magnetic resonance imaging (fMRI) was acquired while conducting passive motor tasks to quantify CC activation. The pre-post activation changes in CC following therapy were quantified in terms of activated voxels. Walking capacity was evaluated using the timed-up-and-go (TUG), 6-minute walk test (6 MWT), and 10-meter walk test (10 MWT) in pre-and post-treatment. Results: The number of activated voxels in CC indicated significant improvement in participants. Post-treatment activated voxels substantially exceeded pre-treatment active voxels. Clinical measures, including TUG, 6 MWT, and 10 MWT are improved by 11.9%, 12.6%, and 25.4%, respectively. Conclusion: Passive task-based fMRI can detect the effects of OT on CC functional activity in children with CP. According to the results, OT improves CC functional activity in addition to gait and balance performance.

The Relationship between Structure of the Corticoreticular Tract and Walking Capacity in Children with Cerebral Palsy.

Background: Disruption in the descending pathways may lead to gait impairments in Cerebral Palsy (CP) children. Though, the mechanisms behind walking problems have not been completely understood. Objective: We aimed to define the relationship between the structure of the corticoreticular tract (CRT) and walking capacity in children with CP. Material and Methods: This is a retrospective, observational, and cross-sectional study. Twenty-six children with CP between 4 to 15 years old participated. Also, we used existed data of healthy children aged 4 to 15 years old. CRT structure was characterized using diffusion tensor imaging (DTI). The DTI parameters extracted to quantify CRT structure included: fractional anisotropy (FA), mean (MD), axial (AD), and radial (RD) diffusivity. Balance and walking capacity was evaluated using popular clinical measures, including the Berg balance scale (BBS), Timed-Up-and-Go (TUG; balance and mobility), six-minute walk test (6 MWT; gait endurance), and 10-meter walk Test (10 MWT; gait speed). Results: There are significant differences between MD, AD, and RD in CP and healthy groups. Brain injury leads to various patterns of the CRT structure in children with CP. In the CP group with abnormal CRT patterns, DTI parameters of the more affected CRT are significantly correlated with walking balance, speed, and endurance measures. Conclusion: Considering the high inter-subject variability, the variability of CRT patterns is vital for determining the nature of changes in CRT structure, their relationship with gait impairment, and understanding the underlying mechanisms of movement disorders. This information is also important for the development or prescription of an effective rehabilitation target for individualizing treatment.

Neutron spectrum unfolding using radial basis function neural networks.

Neutron energy spectrum unfolding has been the subject of research for several years. The Bayesian theory, Monte Carlo simulation, and iterative methods are some of the methods that have been used for neutron spectrum unfolding. In this study, the radial basis function (RBF), multilayer perceptron, and artificial neural networks (ANNs) were used for the unfolding of neutron spectrum, and a comparison was made between the networks' results. Both neural network architectures were trained and tested using the same data set for neutron spectrum unfolding from the response of LiI detectors with Eu impurity. Advantages of each ANN method in the unfolding of neutron energy spectrum were investigated, and the performance of the networks was compared. The results obtained showed that RBF neural network can be applied as an effective method for unfolding neutron spectrum, especially when the main target is the neutron dosimetry.