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.

项目摘要 在深圳进行了数十年的前认知研究后，FDA批准的前认知药物尚未确定。 然而，自下而上的有针对性的认知训练(TCT)被发现在改善认知和 SZ患者的功能结局。尽管如此，TCT是时间和劳动力密集型的、昂贵的且仅 对大约一半的患者有益。这强调了确定TCT的预测性生物标记物的必要性 敏感度。在最近的一份报告中，失配负波(MMN)，一种基于脑电(EEG)的测量方法 早期听觉信息处理(EAIP)预测治疗难治性SZ患者的TCT反应， 尽管威力不大。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治疗后认知和功能改善的“生物标记物”？ EAIP测量，MMN和听觉稳态反应(ASSR)，被认为是测量 在复杂的现实生活环境中的信息处理能力。在日常生活中，复杂的声音刺激 是在感知它们的上下文中被处理的。然而，所有测量MMN和ASSR的方法 利用了孤立的声音片段(滴答声、铃声)，从任何环境环境中移除 实验室测试椅。使用与上下文相关的自然主义声音产生的脑电测量是可能的 刺激可能是TCT敏感性的更好的预测因子。然而，MMN和ASSR措施需要毫秒- 在结构化测试过程中进行水平刺激控制--这在自然主义环境中不容易实现。 虚拟现实(VR)技术既提供了自然环境，又提供了所需的严格实验控制 生成和评估EAIP的更多信息性指标。 这一应用向开发生态有效的基于VR的脑电范式迈出了关键的一步 通过使用熟悉的VR中呈现的自然声音刺激(例如脚步、杰克·哈默)来测量EAIP- 交付的环境(例如，从A点步行到B点，建筑工地)。VR-EEG任务将在#年开发 在0-4个月期间与计算机科学系合作。效度、信度和生物标志物 基于VR的MMN和ASSR的潜力将在健康人(HS)和SZ患者(N=40， HS：SZ=20：20)项目5-20个月。经过仔细筛选，符合条件的研究参与者将完成 全面的神经认知和功能评估、实验室和基于虚拟现实的脑电任务 在随机、顺序平衡的单一测试日研究中，经过一小时的TCT治疗。发现 将检验以下假设：1)基于VR的MMN和ASSR是EAIP缺陷的可靠和有效的测量方法 SZ，2)基于VR的脑电测量将在TCT会话1小时后预测听觉知觉学习 3)基于VR的脑电测量将预测深圳的认知和功能状态。证据表明生态环境 这些基于VR的EAIP生物标志物的有效性将为未来VR-EEG引导下的靶向研究提供基础 前瞻认知疗法。