Characterization of executive function dimensions across pediatric psychiatric disorders

儿科精神疾病执行功能维度的表征

基本信息

批准号：
9471432
负责人：
LAUREN KENWORTHY
金额：
$ 38.55万
依托单位：
GEORGETOWN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-07-19 至 2021-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9471432
关键词：
13 year old Accounting Address Amygdaloid structure Anxiety Disorders Arousal Attention deficit hyperactivity disorder Back Behavior Behavior Therapy Behavioral Brain Categories Child Child Behavior Checklist Childhood Classification Clinic Clinical Communities Comorbidity Corpus striatum structure Data Detection Diagnosis Diagnostic Dimensions Disease Disruptive Behavior Disorder Dorsal Emotional Equipment and supply inventories Executive Dysfunction Factor Analysis Failure Functional Magnetic Resonance Imaging Generations Gilles de la Tourette syndrome Goals Heterogeneity Hyperactive behavior Impairment Impulsive Behavior Impulsivity Intervention Lateral Learning Disabilities Life Link Machine Learning Measures Mediating Medical Medical center Mental disorders Methods Mood Disorders Nature Neurobiology Neuropsychology Outcome Outpatients Parents Parietal Pathway interactions Patient Self-Report Pattern Phenotype Population Process Property Psychiatric Diagnosis Quality of life Reporting Research Domain Criteria Rest Risk Services Short-Term Memory Symptoms System Testing Thinking Tic disorder Training Work associated symptom autism spectrum disorder base clinical practice clinically significant cognitive control cognitive system cohort comparison group dimensional analysis disease classification emotion regulation executive function falls flexibility graph theory inattention neural circuit novel personalized approach recruit response skills social success teacher treatment effect

项目摘要

PROJECT SUMMARY The proposal responds to RFA-MH-16-510 by focusing on the domain of “Cognitive Systems” and constructs “cognitive control” and “working memory” and integrating units of analysis “brain circuit” and “behavior”. These constructs are subsumed under executive function (EF), the ability to voluntarily constrain thoughts and actions in the service of goals. Among pediatric psychiatric categories, EF deficits define Attention Deficit Hyperactivity Disorder (ADHD) and are comorbid with a variety disorders, including Autism Spectrum Disorders, disruptive behavior disorders, mood and anxiety disorders, Tourette's/tics, and learning disabilities. Across these disorders, EF deficits limit adaptive functioning and success of behavioral intervention. Ameliorating EF deficits is a challenge, however, because current EF nosology falls short of capturing heterogeneity within and across disorders. The primary challenge then is identifying the dimensions of EF that capture the specific nature of impairment across disorders. Most past approaches utilize dimension- reducing methods that are sensitive to shared variance, but exclude unique variance. Here, we address this challenge through novel data-driven generation of behavioral profile-based EF dimensions derived from graph theory community-detection (following [1, 2]), applied to common clinical parent-report measures (ADHD Rating scale, inattention, hyperactivity/impulsivity, 8 Behavior Rating Inventory of Executive Function subdomains, Child Behavior Checklist internalizing, and externalizing). Community-detection applied to N=322 (8-13 yrs; IQ>70; no “medical” diagnosis) presenting at Children's National Medical Center neuropsychology clinics identified three EF profiles distinguished by deficits and relative strengths: 1) poor working memory; good flexibility and inhibition; 2) poor inhibition; good working memory; 3) poor flexibility and emotion regulation; good working memory. We will recruit from this growing cohort to examine: Aim 1 – seek replication by testing a new larger cohort with support vector machine classification trained on preliminary data. Aim 2 - characterize functional networks distinguishing the 3 profiles, by group comparison and dimensional analysis. Task-based functional connectivity will test hypothesis about specific circuits distinguishing the novel EF dimensions using fMRI during: 1) N-back working memory; 2) Response inhibition; and 3) Adaptive socio-emotional cognitive control. Task-free resting-state fMRI will test hypothesis about large-scale network interaction differences between EF dimensions. Aim 3 - test the hypothesis that the novel EF dimensions are associated with specific domains of adaptive function, mediated by specific functional networks. Results will: 1) provide neurobiologically validated EF dimensions for re- conceptualizing pediatric psychiatric nosology, and 2) identify treatment targets and increase precision in measuring treatment effects – i.e., who should receive what treatment and how to best measure response and outcome, both of which are essential to the success of a personalized approach to clinical practice.

项目概要该提案通过关注“认知系统”领域来回应 RFA-MH-16-510，并构建 “认知控制”和“工作记忆”以及集成分析单元“脑回路”和“行为”。结构包含在执行功能（EF）下，即自愿约束思想和行动的能力在儿科精神病学类别中，EF 缺陷定义为注意力缺陷多动症。障碍（ADHD）并与多种疾病共存，包括自闭症谱系障碍、破坏性行为障碍、情绪和焦虑障碍、妥瑞氏症/抽动症和学习障碍。 EF 缺陷限制了适应性功能和行为干预的成功。然而，缺陷是一个挑战，因为当前的 EF 疾病分类学无法捕捉异质性那么，主要的挑战是确定 EF 的维度。过去的大多数方法都利用维度来捕捉各种障碍的具体性质。减少对共享方差敏感但排除独特方差的方法。通过新颖的数据驱动生成基于行为档案的 EF 维度来应对这一挑战图论社区检测（以下 [1, 2]），应用于常见的临床家长报告测量（ADHD 评定量表，注意力不集中，多动/冲动，执行功能8项行为评定量表子域、儿童行为检查表内化和外化）。（8-13 岁；智商>70；无“医学”诊断）在国家儿童医疗中心神经心理学就诊诊所根据缺陷和相对优势确定了三种 EF 特征：1）工作记忆差；灵活性和抑制性好；2）抑制性差；3）灵活性和情绪差；我们将从这个不断增长的群体中招募人员来检查：目标 1 – 寻求。通过测试一个新的更大的队列来进行复制，并使用支持向量机分类进行训练目标 2 - 按组描述区分 3 个配置文件的功能网络。基于任务的功能连接将检验有关特定假设的比较和维度分析。在以下过程中使用 fMRI 区分新的 EF 维度的电路：1) N-back 工作记忆；2) 响应抑制；3）适应性社会情绪认知控制，无任务静息态功能磁共振成像将检验假设。关于 EF 维度之间的大规模网络交互差异目标 3 - 检验假设新的 EF 维度与适应性功能的特定领域相关，由结果将：1）为重新提供神经生物学验证的 EF 维度。概念化儿科精神疾病分类学，以及 2) 确定治疗目标并提高治疗的精确度衡量治疗效果——即谁应该接受什么治疗以及如何最好地衡量反应和结果，这两者对于临床实践的个性化方法的成功至关重要。