Planning: aiNsect: A Digital Insect Brain

昆虫的大脑相对简单，化学物质是影响它们行为的最强烈的外部刺激之一。对于昆虫来说，外部分子在很大程度上决定了它们的行为，比如吸引、排斥、改变方向或行动以及停止活动。预测昆虫对化学物质的反应行为对昆虫和神经行为科学至关重要，包括了解有机和传统杀虫剂的生产，寻找叮咬昆虫的天然驱虫剂，或分离信息素以吸引益虫。为了解决这些问题，该项目的长期目标是通过使用机器学习技术和果蝇大脑的神经生理图谱，开发一种名为aiNsect的人工昆虫大脑。规划赠款活动将是支持可行性研究和建立合作的重要的第一步。通过训练aiNsect来解释昆虫对化学物质的反应，它将揭示指导这些行为的模式和规则。这种跨学科的研究，结合人工智能不断扩大的进步，将为学习程序铺平道路，这些程序可以理解行为和相关神经元的细微变化。该项目的主要目标包括：(A)确定一种检测设计，可以捕获所有测试对象的最小运动；(B)促进传统黑人学院和大学、大型研究机构、非营利组织和商业组织、政府机构、r05、非营利组织、政府机构和商业组织之间的合作；(C)用公开的代码证明我们提出的人工智能的可行性。这项工作将为制定研究计划提供基础，从而全面提交给hbcu卓越研究计划。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Insects have relatively simple brains, and chemicals are one of the strongest external stimuli that affect their behaviors. For insects, external molecules largely dictate behaviors such as attraction, repellence, change of direction or action, and cessation of activity. Predicting insect behavior in response to chemicals is vital to insect and neurobehavioral sciences, including understanding production of organic and conventional insecticides, finding natural repellents for biting insects, or isolating pheromones to attract beneficial insects. To address these questions, the project long-term goal is to develop an artificial insect brain called aiNsect by using machine learning techniques and the neuro-physiological map of fruit fly brains. The planning grant activities will be an important first step by supporting feasibility studies and establishing collaborations. By training aiNsect to interpret how insects respond to chemicals, it will uncover the patterns and rules that guide those behaviors. This interdisciplinary research, combined with ever-expanding advancements in AI, will pave the way for learning programs that comprehend even subtle shifts in behavior and the neurons involved. The project's primary objectives include: (A) settling on an assay design that captures even the smallest movements of all test subjects; (B) fostering collaboration across our network of Historically Black Colleges and Universities, large research institution, non-profit and commercial organizations and government agencies, R01s, non-profits, government agencies, and commercial organizations; and (C) proving the feasibility of the AI we propose with published code. This work will provide a fundamental base to generate a research plan leading to a full submission to the HBCU-Excellence in Research Program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.