Realtime Neural Monitor for Drug Abuse Research

描述（由申请人提供）：鉴于经常发生司机因吸毒而能力受损的事故，滥用毒品如何影响驾驶和其他潜在危险活动期间的大脑功能的问题是一个主要的公共卫生问题。该项目旨在开发一种使能技术，以加速这一领域的研究。它将建立在监测计算机工作人员大脑功能的最新进展的基础上，开发一种高度自动化的负担得起的系统，用于研究滥用药物对调节复杂任务表现的大脑机制的影响。该系统将积累的关于脑电图信号分析的专业知识整合到自动化软件中，这将大大减少从中提取有用信息所需的劳动和知识，使从事药物滥用研究的科学家能够成功地记录和分析研究对象操作驾驶模拟器或执行其他自然任务的脑电图信号，这些科学家可能缺乏定量神经生理学方面的专业知识。第一阶段的项目将在大麻中毒的受试者操作汽车驾驶模拟器的背景下确定这一概念的可行性。如果该项目达到第二阶段，该系统将得到充分执行，并单独或结合其他滥用药物进行试验。这个被提议的系统将使第一个具有成本效益的大规模研究成为可能，研究药物是如何影响神经信号的，这些信号与驾驶等复杂任务的集中和保持注意力有关。由于同样的基础技术可以用于临床试验，以评估可能损害认知能力的药物副作用，因此这种技术可能会有很大的市场。

DESCRIPTION (provided by applicant): Given the frequent occurrence of accidents in which the driver's ability was impaired by drugs, the issue of how drugs of abuse affect brain function during driving and other potentially dangerous activities is a major public health concern. This project aims to develop an enabling technology that will accelerate research in this area. It will build on recent progress in monitoring brain function of people working at computers to develop a highly-automated affordable system for studying the effects of drugs of abuse on brain mechanisms mediating complex task performance. The system will embody accumulated expertise about the analysis of EEC signals into automated software that will vastly reduce the labor and knowledge required to extract useful information from them, enabling scientists conducting drug abuse research who may lack specific expertise in quantitative neurophysiology to successfully record and analyze EEC signals from research subjects operating driving simulators or performing other naturalistic tasks. The Phase I project will determine the feasibility of this concept in the context of marijuana-intoxicated subjects operating an automobile driving simulator. If the project reaches Phase II, the system would be fully implemented and tested with other drugs of abuse, alone and in combination. The proposed system would enable the first cost-effective large-scale research studies of how drugs affect neural signals related to focusing and maintaining attention during performance of complex tasks such as driving. Because the same underlying technology could be used in clinical trials to evaluate drug side-effects that might impair cognitive abilities, there is likely to be a significant market for such technology.