Autism
Conditions
Keywords
autism, Brain Plasticity, Behavioral Intervention, Magnetic Resonance Imaging
Brief summary
Autism is a well-recognized neurodevelopmental disorder severely affecting the health of children. While the unclear neurobiological basis of autism and the lack of effective medication, the most commonly used approach for treatment is behavioral intervention. However, the pathophysiological mechanisms underlying the intervention therapy remains incompletely understood. The current project aims to explore the impacts of different early behavioral intervention methods on brain plasticity of autism using multimodal MRI technique and provide guidelines for the intervention and treatment of autism by evaluating the efficiency of these methods.
Detailed description
Autism is a well-recognized neurodevelopmental disorder severely affecting the health of children. While the unclear neurobiological basis of autism and the lack of effective medication, the most commonly used approach for treatment is behavioral intervention. However, the pathophysiological mechanisms underlying the intervention therapy remains incompletely understood. The current project aims to explore the impacts of different early behavioral intervention methods on brain plasticity of autism using multimodal MRI technique and provide guidelines for the intervention and treatment of autism by evaluating the efficiency of these methods. Investigators collect participants' brain imaging data, eye movement data, stool samples and clinical scale score before and after intervention. Investigators first investigate longitudinal effect of behavioral intervention on brain structure and function in children with autism. In addition, investigators provide new biological indexes upon multimodal large-scale brain connectomes to evaluate the curative effect of intervention. Finally, investigators propose a prediction model of intervention effect based on multimodal multivariate pattern analysis methods. Furthermore, investigators expect to map the state-of-the-art biomarkers on multi-modal networks to provide a new interpretation of pathophysiological mechanisms of autism.
Interventions
BEHAVIORALBehavior modification
Each group has 30 subjects and experiences six months' training.
BEHAVIORALBehavior modification and sensory integration training
Each group has 30 subjects and experiences six months' training.
BEHAVIORALBehavior modification and applied behavioral analysis
Each group has 30 subjects and experiences six months' training.
BEHAVIORALBehavior modification and TEACCH
Each group has 30 subjects and experiences six months' training.
Sponsors
University of Electronic Science and Technology of China
Study design
Allocation
RANDOMIZED
Intervention model
FACTORIAL
Primary purpose
BASIC_SCIENCE
Masking
TRIPLE (Subject, Caregiver, Investigator)
Eligibility
Sex/Gender
ALL
Age
2 Years to 8 Years
Healthy volunteers
Yes
Inclusion criteria
* Age range from 2 to 8 years old. * Clinical DSM-IV diagnosis of autism.
Exclusion criteria
* Subjects with other neurodevelopmental diseases. * Subjects with contraindications to MRI.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Brain structural and functional change under behavioral intervention at 6 months in children with autism | through study completion, an average of 1 year | Longitudinal effect of behavioral intervention on brain structure and function in children with autism will be assessed by Voxel-based morphometry analysis for structural changes, as well as Regional homogeneity, Amplitude of low-frequency fluctuation, etc, for functional changes. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Prediction model of intervention effect based on multimodal multivariate pattern analysis methods | through study completion, an average of 1 year | First, classify autism individuals into effective treatment group and ineffective treatment group according to the intervention effect at 6 months. Second, conduct feature selection with Sparse optimization algorithms and cluster analysis on MRI data. Third, design optimized classifiers integrated support vector machines and Gaussian Naive Bayes classifiers. |
Countries
China
Contacts
Primary ContactHuafu Chen
Outcome results
None listed