No abstract

Balance and movement are impaired in a wide variety of neurological disorders. Recent advances in behavioral monitoring provide unprecedented access to posture and locomotor kinematics, but without the throughput and scalability necessary to screen candidate genes / potential therapeutics. We present a powerful solution: a Scalable Apparatus to Measure Posture and Locomotion (SAMPL). SAMPL includes extensible imaging hardware and low-cost open-source acquisition software with real-time processing. We first demonstrate that SAMPL's hardware and acquisition software can acquire data from three species (flies, worms, and zebrafish) as they move vertically. Next, we leverage SAMPL's throughput to rapidly (two weeks) gather a new zebrafish dataset. We use SAMPL's analysis and visualization tools to replicate and extend our current understanding of how zebrafish balance as they navigate through a vertical environment. Next, we discover (1) that key kinematic parameters vary systematically with genetic background, and (2) that such background variation is small relative to the changes that accompany early development. Finally, we simulate SAMPL's ability to resolve differences in posture or vertical navigation as a function of affect size and data gathered -- key data for screens. Taken together, our apparatus, data, and analysis provide a powerful solution for labs using small animals to investigate balance and locomotor disorders at scale. More broadly, SAMPL is both an adaptable resource for labs looking process videographic measures of behavior in real-time, and an exemplar of how to scale hardware to enable the throughput necessary for screening.