BCI-based feedback system to promote cognitive control of craving

描述（由申请人提供）：药物成瘾的核心是大脑奖励系统的损伤，其中对药物相关刺激的超敏反应是以归因于所有其他非药物相关刺激的显著性不足为代价的。这种对药物相关刺激的超敏反应使可卡因使用障碍（CUD）患者特别容易产生渴望（和药物使用），特别是当出现药物相关线索时。然而，在实验室环境中，当被指示自愿抑制线索诱导的渴望时，一些CUD报告了较低的渴望，并显示出处理奖励激励价值的大脑区域（包括药物相关线索）（眶额皮层）的活动减少，从而保留了药物相关线索。 对药物相关线索反应的某种程度的控制。我们建议利用这种渴望的意志控制，使用脑电图（EEG）和随后确定的事件相关电位（ERP）技术，结合基于脑机接口（BCI）的实时反馈系统，以帮助支持药物成瘾的认知控制。在目前的建议，我们的目标是测试的假设，当被要求自愿重新评价药物刺激，CUD将能够调制功能显着的药物线索诱导的皮层电标记。我们还假设，提供一个自己的药物线索反应的EEG/ERP神经元标记的实时反馈（由先进的信号处理算法的BCI平台生成）将与寻求治疗的CUD减少药物寻求和渴望和增强抑制控制。鉴于基于EEG和ERP的BCI系统是非侵入性的，可移动的和负担得起的，该提议具有重要的临床意义。特别是，一旦测试和验证，该系统可以在治疗中心实施，以减少药物线索反应/药物寻求/渴望和增强自我控制。由于基于BCI的真实的时间反馈系统结合了每个患者自己的大脑疾病特征，因此可以用于设计个性化的治疗方案以防止复发。因此，鉴于我的生物医学工程背景和EEG数据采集、信号处理、数据分析方面的研究生研究经验，以及申办者和共同申办者的支持、专业知识和广泛监督，我相信我正处于一个独特的时刻，正在进行这项多学科和技术前沿的研究提案。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相结合，将有助于我发展成为一名独立的科学家，在实施工程原理以推进临床和介入神经科学方面具有优势。 公共卫生相关性：理论上，渴求是对药物相关刺激的条件性心理生理反应的表现，是可卡因依赖中复发和强迫性药物使用的关键因素，减少这种渴求是关键的治疗目标和结果措施。最近，研究表明，一些成瘾者对他们的渴望保持一定的认知控制。我们建议扩展这些发现，并加强对渴望的认知控制，并实时反馈自己的神经信号的药物线索反应。特别是，我们测试了一个新的假设，即CUD可以被有效地训练，以使用他们自己的大脑疾病信号的实时反馈来自愿地控制他们的药物线索反应，并且这种训练将导致这些个体减少药物寻求。

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. PUBLIC HEALTH RELEVANCE: Craving is theorized to be a manifestation of conditioned psychophysiological response to drug-related stimuli, a key contributor for relapse and compulsive drug use in cocaine dependence and reduction of such craving is a critical treatment target and outcome measure. Recently, it was shown that some addicted individuals retain some cognitive control over their craving. We propose to extend these finding and reinforce cognitive control over craving with real-time feedback of one's own neural signature of drug-cue reactivity. In particular, we test the novel hypothesis that CUD can be trained efficiently to volitionally control their drug-cue reactivity using real-time feedback of their own brain signatur of illness, and that this training will result in reduced drug- seeking in these individuals.