Developing an ecologically valid virtual reality-EEG paradigm for biomarker assessment of procognitive treatment sensitivity in schizophrenia

开发生态有效的虚拟现实脑电图范式，用于精神分裂症认知治疗敏感性的生物标志物评估

• 批准号: 10038925
• 负责人: Savita G Bhakta
• 金额: $ 43.36万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10038925
• 关键词: Auditory; Biological Markers; California; Clinical; Cognition; Cognitive; Cognitive Therapy; Collaborations; Complex; Consensus; Early treatment; Electroencephalogram; Environment; Exposure to; FDA approved; Frequencies; Funding; Future; Health Insurance; Hour; Laboratories; Laughter; Learning; Life; Link; Measures; Methods; Nature; Neurocognitive; Participant; Patients; Perceptual learning; Performance; Pharmaceutical Preparations; Process; Publishing; Randomized; Refractory; Reporting; Research; Schizophrenia; Site; Stimulus; Structure; Symptoms; Technology; Testing; Therapeutic; Time; Training; Universities; Validity and Reliability; Variant; Verbal Learning; Walking; auditory processing; auditory stimulus; base; brain electrical activity; cognitive training; computer science; daily functioning; early detection biomarkers; functional gain; functional outcomes; improved; improved functioning; information processing; millisecond; neurophysiology; novel; potential biomarker; predictive marker; processing speed; psychosocial; response; sensitivity training; skills; sound; targeted biomarker; treatment response; virtual reality

Project Summary After decades of procognitive research in SZ, an FDA approved procognitive drug is yet to be identified. However, a bottom-up targeted cognitive training (TCT) is found to be effective in improving cognition and functional outcome in SZ patients. Nonetheless, TCT is time and labor-intensive, expensive, and only beneficial to about half of the patients. This underscores the need to identify predictive biomarkers of TCT sensitivity. In a recent report, mismatch negativity (MMN), an electroencephalogram (EEG)- based measure of early auditory information processing (EAIP) predicted TCT response in treatment-refractory SZ patients, albeit, with modest power. To this end, an important question is, can we enhance the ability of EAIP “biomarkers” to predict cognitive and functional gains from TCT in SZ patients? EAIP measures, MMN and auditory steady state response (ASSR), are presumably measuring information processing capacity within complex, real-life environments. In everyday life, complex sound stimuli are processed in the context in which they are perceived. However, all methods to measure MMN and ASSR have utilized isolated sound fragments (clicks, tones), removed from any environmental context beyond a laboratory test chair. It is possible that EEG measures generated using contextually relevant naturalistic sound stimuli might be better predictors of TCT sensitivity. However, MMN and ASSR measures require millisecond- level stimulus control within a structured test session – that is not easily achieved in a naturalistic setting. Virtual reality (VR) technology provides both the naturalistic context and tight experimental control needed to generate and assess more informative measures of EAIP. This application takes the critical step toward developing an ecologically valid VR-based EEG paradigm to measure EAIP by using naturalistic sound stimuli (e.g. footsteps, jack hammer) presented in familiar VR- delivered contexts (e.g. walking from point A to B, construction site). The VR-EEG task will be developed in collaboration with the Computer Sciences Department during months 0-4. The validity, reliability and biomarker potential of the VR-based MMN and ASSR will be determined in healthy subjects (HS) and SZ patients (N=40, HS:SZ= 20:20) during project months 5-20. Carefully screened, eligible study participants will complete a comprehensive neurocognitive and functional assessment, laboratory- and VR- based EEG tasks before and after a one-hour “sound sweeps” TCT session in a randomized, order-balanced, single test day study. Findings will test the hypotheses that: 1) VR-based MMN and ASSR are reliable and valid measures of EAIP deficits in SZ, 2) the VR-based EEG measures will predict auditory perceptual learning after 1-hour of TCT session and 3) VR-based EEG measures will predict cognitive and functional state in SZ. Evidence suggesting ecological validity of these VR-based biomarkers of EAIP will provide basis for future VR-EEG guided studies of targeted procognitive therapeutics.

项目概要 经过深圳数十年的促认知研究，FDA 批准的促认知药物尚未确定。 然而，自下而上的有针对性的认知训练（TCT）被发现可以有效地提高认知能力和能力。 然而，TCT 是一种耗时、费力、昂贵且唯一的方法。 这对大约一半的患者有益，这强调了识别 TCT 预测生物标志物的必要性。 在最近的一份报告中，失配负性（MMN）是一种基于脑电图（EEG）的测量方法。 早期听觉信息处理（EAIP）预测难治性 SZ 患者的 TCT 反应， 虽然，为此，一个重要的问题是，我们能否增强EAIP的能力。 预测 SZ 患者 TCT 认知和功能增益的“生物标志物”？ EAIP 测量、MMN 和听觉稳态响应 (ASSR) 可能正在测量 在复杂的现实生活环境中的信息处理能力。 然而，所有测量 MMN 和 ASSR 的方法都是在它们被感知的环境中进行处理的。 使用了孤立的声音片段（滴答声、音调），将其从任何环境背景中移除 实验室测试椅可能使用上下文相关的自然声音生成脑电图测量。 刺激可能是 TCT 敏感性的更好预测因子，但是 MMN 和 ASSR 测量需要毫秒。 结构化测试会话中的水平刺激控制——这在自然环境中不容易实现。 虚拟现实 (VR) 技术提供了所需的自然环境和严格的实验控制 生成和评估更具信息性的 EAIP 衡量标准。 该应用程序朝着开发生态有效的基于 VR 的脑电图范式迈出了关键一步 通过使用熟悉的 VR 中呈现的自然声音刺激（例如脚步声、凿岩锤）来测量 EAIP VR-EEG 任务将在以下时间开发： 第 0-4 个月与计算机科学系合作的有效性、可靠性和生物标志物。 基于 VR 的 MMN 和 ASSR 的潜力将在健康受试者 (HS) 和 SZ 患者 (N=40， HS:SZ= 20:20) 在项目第 5-20 个月期间，经过仔细筛选，合格的研究参与者将完成一份报告。 全面的神经认知和功能评估、基于实验室和 VR 的脑电图任务之前和 在一项随机、顺序平衡、单一测试日研究中进行一小时“声音扫描”TCT 课程后。 将测试以下假设： 1) 基于 VR 的 MMN 和 ASSR 是 EAIP 赤字的可靠且有效的衡量标准 SZ，2) 基于 VR 的脑电图测量将预测 1 小时 TCT 课程后的听觉感知学习，以及 3) 基于 VR 的脑电图测量将预测 SZ 的认知和功能状态。 这些基于 VR 的 EAIP 生物标志物的有效性将为未来 VR-EEG 引导的靶向研究提供基础 认知疗法。