BCI-based feedback system to promote cognitive control of craving

描述(申请人提供)：吸毒成瘾的核心是大脑奖励系统的损害，其中对毒品相关刺激的过敏是以所有其他非毒品相关增强剂的突显不足为代价的。这种药物相关刺激的过敏性使患有可卡因使用障碍(CUD)的人特别容易受到渴望(和药物使用)的影响，特别是在出现与药物有关的线索时。然而，在实验室环境中，当被指示有意抑制线索诱导的渴望时，一些CUD报告说欲望降低，大脑处理奖赏激励价值的区域(包括与药物相关的线索(眶前皮质))的活动减少，从而保持 在一定程度上控制了他们与药物相关的线索反应。我们建议利用这种对欲望的意志控制，使用脑电(EEG)和随后确定的事件相关电位(ERP)技术，再加上基于脑机接口(BCI)的实时反馈系统，来帮助支持药物成瘾的这种认知控制。在目前的提案中，我们的目标是检验这样一个假设，即当被要求自愿重新评估药物刺激时，CUD将能够调节功能显著的药物线索诱导的皮层标志物。我们还假设，提供自己的药物线索反应性的脑电/ERP神经元标记物的实时反馈(由BCI平台产生)将与减少寻求药物和渴望以及增强寻求治疗CUD的抑制控制有关。鉴于基于EEG和ERP的脑机接口系统是非侵入性的、可移动的和负担得起的，这项建议具有重要的临床意义。特别是，一旦经过测试和验证，该系统可以在治疗中心实施，以减少药物线索反应性/寻找药物/渴求和增强自我控制。由于基于脑-机接口的实时反馈系统结合了每个患者自己的疾病大脑信号，它可以用来设计一个个性化的治疗方案，以防止复发。因此，鉴于我在生物医学工程方面的背景，以及在脑电数据采集、信号处理、数据分析方面的研究生研究经验，以及赞助商和共同赞助商的支持、专业知识和广泛的监督，我相信我正处于承担这项跨学科和技术尖端研究提案的独特时刻。因此，获得NRSA的支持，将我的课程工作、研究经验与拟议的研究培训计划结合起来，将有助于我作为一名独立科学家的发展，在实施工程原理以促进临床和介入神经科学方面具有独特的地位。

DESCRIPTION (provided by applicant): At the core of drug addiction is impairment in the brain's reward system where hypersensitivity to drug- related stimuli comes at the expense of insufficient salience attributed to all other non-drug-related reinforcers. This hypersensitivity t drug-related stimuli renders individuals with cocaine use disorder (CUD) particularly vulnerable to craving (and drug use), especially when presented with drug-related cues. Nevertheless, when instructed to volitionally inhibit cue-induced craving in a laboratory environment, some CUD reported lower craving and showed decreased activity in the brain regions that process the motivational value of rewards including drug-related cues (orbitofrontal cortex), thereby retaining some level of control over their drug- related cue reactivity. We propose to capitalize on this willed control of craving, using electroencephalogram (EEG) and subsequently ascertained event-related potentials (ERP) techniques, coupled with a Brain- Computer Interface (BCI) based real-time feedback system, to help bolster such cognitive control in drug addiction. In the current proposal, we aim to test the hypothesis that, when asked to volitionally reappraise drug stimuli, CUD will be able to modulate functionally significant drug-cue-induced electrocortical markers. We also hypothesize that providing a real-time feedback (generated by a BCI platform with advanced signal processing algorithms) of one's own EEG/ERP neuronal markers of drug-cue reactivity will be associated with reduced drug-seeking and craving and enhanced inhibitory control in treatment-seeking CUD. Given that EEG- and ERP-based BCI systems are non-invasive, ambulatory and affordable, this proposal has important clinical implications. In particular, once tested and validated, this system could be implemented in treatment centers for reducing drug-cue reactivity/drug-seeking/craving and enhancing self-control. Because a BCI-based real- time feedback system incorporates each patient's own brain signature of illness, it could be used to design an individually tailored treatment program to prevent relapse. Thus, given my background in biomedical engineering and graduate research experience in EEG data acquisition, signal processing, data analysis and the support, expertise and extensive supervision of the sponsor and the co-sponsors, I believe I am at a unique juncture in undertaking this multidisciplinary and technologically cutting-edge research proposal. Therefore, obtaining NRSA support to integrate my course work, research experience with the proposed research training plan will help me develop as an independent scientist, with a niche in implementing engineering principles to advance clinical and interventional neuroscience.