Charles E. Kaufman Foundation

2021 New Initiative Grant

Eva-Maria Collins, Ph.D. (PI) Associate Professor, Biology Department, Swarthmore College

Ameet Soni, Ph.D. (Co-PI) Associate Professor, Computer Science, Swarthmore College

Inferring Brain Function via Quantitative Behavioral Phenotyping in Free-Moving Planarians


Abstract

How the brain works is a key question in biology and medicine. Because behavior is an accessible readout of brain function, it can be used as a gateway to understand how the brain works. While this sounds like a straightforward approach, its realization is intrinsically difficult. First, the experimental system must be amenable to automated quantification of behavior and pharmacological and/or genetic manipulations to connect the behavior to neuronal pathways. Second, we need to take an unbiased approach to classify behavior, otherwise we confine ourselves to a small, pre-defined behavioral space. These pre-defined spaces limit our ability to differentiate normal biological variability from abnormal behavior in different environmental contexts or during development, aging and disease. We propose that we can connect behavior to brain function by using an unbiased quantitative characterization of the free behaviors of the asexual freshwater planarian Dugesia japonica. This planarian is ideally suited for quantitative and mechanistic studies of behavior because: Its brain is of intermediate complexity and shares key neuronal genes and neurotransmitters with humans; it is amenable to high-throughput automated quantitative behavioral studies; and we can unravel the neuronal pathways controlling specific behaviors using genetic and chemical perturbations. This project will reveal the natural behavioral realm of this freshwater planarian using a novel behavioral classification system that can be used to predict which neuronal functions are affected by genetic or chemical perturbations. If successful, this project will yield new insights into the neuronal control of behavior that are relevant to more complex organisms, including humans.

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