Planning: aiNsect: A Digital Insect Brain

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.