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

• 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
• 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

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.

对于由于治疗干预而发生的大脑功能和结构重组的理解存在着根本性的差距。这一差距的持续存在代表了心理健康研究中的一个重要问题，因为在填补这一差距之前，更有效和高效的干预措施的设计将在很大程度上不受指导。我们的长期目标是利用非侵入性检测和监测大脑重组来指导治疗的开发和实施。这一特定应用的目标是开发一种可靠且灵敏的大脑网络可塑性磁共振成像指标，并将其应用于研究接受认知训练的儿童的结构性大脑网络的重塑。所提出的网络方法的基本原理是，治疗引起的大脑变化并不局限于特定的大脑区域，而是通常涉及通信路径，这可以通过扩散 MRI 连接组学直接解决，该连接组学将大脑视为大脑区域之间的结构连接网络。中心假设是，基于扩散 MRI 的大脑网络及其图形分析特性可以作为接受认知训练的儿童可塑性的可靠且敏感的指标。我们将研究 10-18 岁青少年的大脑网络变化，这些青少年接受了为期 12 周的基于正念冥想的注意力和情绪调节训练，并根据基于计算机的注意力网络测试 (ANT) 将结果与行为变化相关联。拟议的研究意义重大，因为它有望提供一种监测治疗干预效果的方法，指导新干预措施的开发，并增进我们对大脑如何根据特定认知功能的强化练习进行重组的理解。最终，这些知识有可能为临床人群的治疗发展提供信息，例如患有注意力缺陷多动障碍（ADHD）、抑郁症和焦虑症的儿童和青少年。