A Wearable Optical Imaging System for Daily Monitoring of Prefrontal Activity in ADHD

项目总结 在过去的十年里，国家精神卫生研究所(NIMH)为 为寻找精神疾病的脑标记物而进行的大规模、多部位、功能磁共振(FMRI)队列研究 FMRI用于精神疾病诊断的临床翻译面临着许多挑战。其中首当其冲的 在个人层面上缺乏结果的重复性是由于以下因素的次优测量可靠性 短数量(&lt；10分钟)fMRI记录。研究表明，收集每小时而不是几分钟的数据 可能需要个别患者来实现功能神经成像的临床承诺，但成本问题， 接受测试的范例的依从性和生态有效性使得这种功能磁共振研究在患者中不可行 与精神疾病有关，并导致成像技术的临床应用存在巨大差距 心理健康。为了弥合功能神经成像在临床神经精神病学中的翻译差距，我们 提出了一种基于功能近红外的可穿戴成像系统的优化、测试和验证方案 光谱学(FNIR)是一种低成本、可访问、可靠的技术，可在家中用于收集高度的红外光谱。 用注意儿童额叶前部活动对精神疾病患者的脑活动进行采样 以缺陷多动障碍(ADHD)为模型疾病来测试这一创新范式的可行性。 与fMRI相比，fNIRS便宜、便携，对受试者的运动更耐受，允许 在自然环境中测量大脑活动。我们的中心假设是，收集高样本 个人数据将使我们能够检测大脑活动的模式，这些模式可以在个人身上可靠地复制 并能预测行为和临床症状。大量的功能磁共振成像和近红外光谱数据已经证明 (A)在执行功能任务期间，ADHD患者前额叶回路的持续低激活和(B) 注意缺陷多动障碍患者额叶前部活动不足与行为和临床症状的关系。我们 将收集关于30名ADHD儿童和30名典型ADHD儿童前额活动的高采样fNIRS数据 开发控件。数据将在三周内每天收集，同时受试者处于休息和/或表演状态 智能手机上的认知任务。我们的跨学科、多机构团队已经开发出非常 低成本(100英镑)可穿戴式无线fNIRS系统原型，用于监测前额叶皮质的活动 我们将通过这项提案来提炼(目标1)和部署(目标2)。目标1：优化可穿戴设备原型， 用于定期监测前额叶的无线、多通道、智能手机操作的光学成像系统 在家里活动。目标2：测试和验证所提出的系统，用于可靠地监测前额叶活动 患有多动症的儿童。成功完成这项首创的研究将有助于改变目前的范式 来自实验室内的小量神经成像，并为开发有效的生物标记物铺平了道路 临床上用于精神障碍的诊断和早期发现，监测治疗反应。

PROJECT SUMMARY Over the past decade, the National Institute of Mental Health (NIMH) has invested several billion dollars for large-scale, multi-site, functional MRI (fMRI) cohort studies in pursuit of brain markers for mental illness, yet clinical translation of fMRI for diagnosis of mental illness is plagued with many challenges. Chief among them is the lack of reproducibility of findings at the individual level due to the suboptimal measurement reliability of short-quantity (<10 min) fMRI recordings. Research suggests that collecting hours – not minutes – of data per individual patient may be needed to fulfill the clinical promise of functional neuroimaging, but issues of cost, compliance and the ecological validity of tested paradigms render such fMRI studies impractical in patients with psychiatric conditions and contribute to the huge gap in the clinical utility of imaging technologies for mental health. To bridge the gap in translation of functional neuroimaging in clinical neuropsychiatry, we propose to optimize, test and validate a wearable imaging system based on functional near infrared spectroscopy (fNIRS) that is low-cost, accessible, reliable, and can be used at home for collecting highly- sampled brain activity in patients with mental illness, using the prefrontal activity of children with Attention Deficit Hyperactivity Disorder (ADHD) as a model illness to test the feasibility of this innovative paradigm. Compared with fMRI, fNIRS is inexpensive, portable, and more tolerant to subject movement, allowing for measurement of brain activity in naturalistic situations. Our central hypothesis is that collecting highly-sampled individual data will allow us to detect patterns of brain activity that can be reliably replicated at the individual level and that predict behavioral and clinical symptoms. A wealth of fMRI and fNIRS data already demonstrate (a) consistent hypoactivation in the prefrontal circuit in ADHD during executive functioning tasks and (b) association between hypoactivity in the prefrontal circuit in ADHD and behavioral and clinical symptoms. We will collect highly-sampled fNIRS data on the prefrontal activity of 30 children with ADHD and 30 typically developing controls. Data will be collected daily over three weeks while subjects are at rest and/or performing cognitive tasks on a smart-phone. Our interdisciplinary, multi-institutional team has already developed a very low-cost (<$100) prototype wearable, wireless fNIRS system for monitoring activity of the prefrontal cortex that we will refine (Aim 1) and deploy (Aim 2) through this proposal. Aim 1: Optimize a prototype wearable, wireless, multi-channel, smart-phone operated optical imaging system for regular monitoring of prefrontal activity at home. Aim 2: Test and validate the proposed system for reliable monitoring of prefrontal activity in children with ADHD. Successful completion of this first-of-a-kind study will help shift the current paradigm away from in-lab, small-quantity neuroimaging and pave the way for developing effective biomarkers that can be used clinically for diagnosis and early detection of mental disorders, monitoring the response to treatment.