The neurophysiological basis of interindividual variability (IIV) in ADHD

ADHD 个体差异（IIV）的神经生理学基础

基本信息

批准号：
10660737
负责人：
Agatha Lenartowicz
金额：
$ 28.51万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-06-15 至 2026-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10660737
关键词：
Adult Attention Attention deficit hyperactivity disorder Back Behavioral Biological Characteristics Child Clinical Clinical Trials Cognition Data Data Analyses Data Set Development Diffusion Disease Dorsal Electroencephalography Frequencies Functional Magnetic Resonance Imaging Future Goals Hyperactivity Individual Individual Differences Interruption Life Link Measures Modeling Monitor Multimodal Imaging Nature Noise Outcome Pathway Analysis Performance Periodicals Phase Predictive Value of Tests Property Reaction Time Rest Sampling Signal Transduction Specificity Symptoms Task Performances Testing Time Treatment outcome Visit Visual Work behavior prediction behavioral outcome density functional magnetic resonance imaging/electroencephalography inattention indexing individual response individual variation innovation inter-individual variation interest neural neural correlate neuromechanism neurophysiology secondary analysis statistics sustained attention temporal measurement theories

项目摘要

PROJECT SUMMARY Increased intraindividual variability (IIV) in task performance is a robust symptom of attention deficit/hyperactivity disorder (ADHD). However, while theoretical frameworks suggest inefficient neural processing as a potential cause of IIV, evidence is limited because IIV is typically measured using summary statistics of behavioral outcomes, such as response time variability (RTV). Not only are such measures limited by sparse temporal sampling, but they also aggregate time, ignoring underlying dynamics, and limiting the specificity and thus the translational value of IIV in ADHD. In this project, we propose that neurophysiological measures of neural processing efficiency can be continuously derived from the oscillatory and signal properties of EEG, to track the contribution of top-down signals (low-frequency power), network efficiency (low-frequency oscillatory small-world index) and network interaction stability (signal complexity). These measures can be used as a continuous, within- subject neurophysiological index of neural processing efficiency, and one that bridges summary statistics derived from reaction times and underlying network dynamics. To test this idea, we revisit three existing datasets (n=514) that include children and adults, with and without ADHD, and that contain EEG and concurrent EEG and fMRI, collected during sustained attention tasks. In each dataset, we compute continuous measures of neural efficiency based on EEG signals to, in Aim 1, differentiate between alternate neurophysiological profiles and mechanisms of IIV in ADHD and test if these predict performance outcomes and individual differences in symptoms. In Aim 2, we additionally test if neural efficiency measures predict, within-subject, aberrant interactions between core attention networks and those previously associated with ADHD – namely fronto-parietal, default-mode, ventral/dorsal attention, visual and fronto-striatal. The goal of the present work is to establish the neurophysiological basis of IIV in ADHD, and thus speak to putative clinical targets of IIV, differentiate between current theories of IIV, as well as to validate EEG-based neural efficiency as an effective intermediate indicator of underlying network dynamics.

项目概要任务表现的个体差异（IIV）增加是注意力缺陷/多动的强烈症状然而，虽然理论框架表明低效的神经处理是一种潜在的障碍。 IIV 的原因，证据有限，因为 IIV 通常是使用行为的汇总统计来衡量的结果，例如响应时间变异性（RTV），此类测量不仅受到稀疏时间的限制。采样，但它们也会聚合时间，忽略潜在的动态，并限制特异性，从而限制 IIV 在 ADHD 中的转化价值在这个项目中，我们提出了神经生理学测量。处理效率可以从脑电图的振荡和信号特性中不断得出，以跟踪自上而下信号（低频功率）、网络效率（低频振荡小世界）的贡献指数）和网络交互稳定性（信号复杂性）这些措施可以用作连续的、内部的。神经处理效率的主题神经生理学指数，以及桥接汇总统计得出的指数来自反应时间和底层网络动态。为了测试这个想法，我们重新访问了三个现有数据集（n=514），其中包括儿童和成人，有或没有 ADHD 包含脑电图以及并发脑电图和功能磁共振成像，在每个持续注意力任务期间收集。数据集，我们根据脑电图信号计算神经效率的连续测量，以在目标 1 中区分比较 ADHD 中 IIV 的替代神经生理学特征和机制，并测试这些是否可以预测在目标 2 中，我们还测试了神经元的表现结果和个体差异。效率测量可预测主体内核心注意力网络和那些以前与多动症相关的——即额顶叶、默认模式、腹侧/背侧注意力、视觉目前工作的目标是建立 ADHD 中 IIV 的神经生理学基础，以及因此，讨论 IIV 的假定临床目标，区分当前的 IIV 理论，并验证基于脑电图的神经效率作为底层网络动态的有效中间指标。