A Network Approach to Study Brain Plasticity in Children with Cognitive Training

研究认知训练儿童大脑可塑性的网络方法

基本信息

批准号：
9017711
负责人：
Olga Tymofiyeva
金额：
$ 19.81万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-12-07 至 2017-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9017711
关键词：
18 year old Address Adolescent Anxiety Disorders Atlases Attention Attention deficit hyperactivity disorder Base of the Brain Behavioral Brain Brain region Child Clinical Treatment Communication Computers Data Set Development Diffusion Magnetic Resonance Imaging Disease Ensure Free Will Goals Graph Health Human Intervention Knowledge Longitudinal Studies Magnetic Resonance Imaging Maps Measures Mental Depression Mental Health Methods Mission Modeling Monitor Network-based Non-Invasive Cancer Detection Outcome Pathway interactions Population Process Property Public Health Reliability of Results Research Research Design Seasons Statistical Data Interpretation Structure Testing Therapeutic Intervention Time Training Training Programs Work Youth age group base behavior measurement cognitive function cognitive training design disability emotion regulation experience falls functional plasticity mindfulness meditation reconstruction relating to nervous system skills therapy design therapy development

项目摘要

There is a fundamental gap in understanding of the functional and structural reorganization of the brain that takes place as a result of therapeutic interventions. Continued existence of this gap represents an important problem in mental health research because, until it is filled, design of more effective and efficient interventions will remin largely unguided. Our long-term goal is to use non-invasive detection and monitoring of brain reorganization to guide the development and implementation of therapies. The objective in this particular application is to develop a reliable and sensitive MR imaging indicator of brain network plasticity and apply it to study the remodeling of structural brain networks in children with cognitive training. The rationale for the proposed network approach is that brain changes resulting from therapies are not confined to a specific brain region but usually involve communication pathways and this is directly addressed by diffusion MRI connectomics that treats the brain as a network of structural connections between brain regions. The central hypothesis is that diffusion MRI-based brain networks and their graph-analytic properties can serve as a reliable and sensitive indicator of plasticity in children with cognitive training. We wll study brain network changes in 10-18 year-old youths who undergo a 12-week mindfulness meditation-based training of attention and emotion regulation and correlate the results with the behavioral changes according to the computer-based Attention Network Test (ANT). The proposed research is significant, because it is expected to provide a method for monitoring the efficacy of therapeutic interventions, guide the development of new interventions, and advance our understanding of how the brain reorganizes as a function of intensive practice of specific cognitive functions. Ultimately, such knowledge has the potential to inform the development of treatment for clinical populations, such as children and adolescents with attention deficit hyperactivity disorder (ADHD), depression and anxiety disorders.

理解由于治疗干预措施而发生的大脑的功能和结构重组存在根本差距。这种差距的持续存在代表了心理健康研究中的一个重要问题，因为在填补之前，更有效和有效的干预措施的设计将在很大程度上不受指导。我们的长期目标是使用非侵入性检测和监测脑重组的监测来指导疗法的开发和实施。在此特定应用中的目的是开发一个可靠且敏感的MR成像指标的大脑网络可塑性指标，并将其应用于认知训练儿童中结构性脑网络的重塑。提出的网络方法的理由是，疗法导致的大脑变化不仅限于特定的大脑区域，而是涉及通信途径，这是通过扩散的MRI连接素学直接解决的，它将大脑视为大脑区域之间的结构连接网络。中心假设是，基于MRI的扩散脑网络及其图形分析特性可以作为认知训练儿童的可靠且敏感的可塑性指标。根据基于计算机的注意力网络测试（ANT），我们研究了10-18岁的年轻人的大脑网络变化，他们接受了12周的正念冥想培训，并将结果与行为变化相关联。拟议的研究非常重要，因为预计它将提供一种监测治疗干预效率，指导新干预措施的效率，并促进我们对大脑如何重新组织的理解，以指定特定认知功能的密集实践的函数。最终，这种知识有可能告知临床人群治疗的发展，例如儿童和患有注意力缺陷多动障碍（ADHD），抑郁症和动画障碍的青少年。