Flexible analysis of animal behavior via time-resolved embedding
York, Ryan (2021), Flexible analysis of animal behavior via time-resolved embedding, Dryad, Dataset, https://doi.org/10.5061/dryad.ksn02v743
Uncovering relationships between neural activity and behavior represents a critical challenge, one that would benefit from facile tools that can capture complex structures within large datasets.Using data from synthetic trajectories, adult and larval Drosophila, and mice we show how TREBLE captures both continuous and discrete behavioral dynamics, can uncover variation across individuals, detect the effects of optogenetic perturbation in unbiased fashion, and reveal structure in pose estimation data. By applying TREBLE to moving mice, and medial entorhinal cortex (MEC) recordings, we show that nearly all MEC neurons encode information relevant to specific movement patterns, expanding our understanding of how navigation is related to the execution of locomotion. Thus, TREBLE provides a flexible framework for describing the structure of complex behaviors and their relationships to neural activity.
Drosophila embryos were collected for 1 h on standard 3.0% agar molasses collection caps covered with a thin layer of wet yeast. Twenty-four hours later, hatched embryos were transferred to standard cornmeal fly food. After forty-eight hours (L2 larval stage), animals were collected and transferred to a Petri dish with1.2% agar and relocated to a behavioral room kept at 23°C and 60% humidity. Ten to fifteen minutes after acclimation to the room, groups of 5 to 10 larvae were transferred to a 30 x 30 cm 1.2% agar arena. After 15 to 30 seconds, locomotion was recorded using a FIM imaging system (https://www.uni muenster.de) at 10 fps for 5 minutes. The FIM system was equipped with an azA2040-25gm (Basler) camera and a LM16HC-SW (Kowa) lens. Individual larvae were then tracked using FIMtrack software.
Collected here are primary measurements of larvae shape and movement that were used for downstreamn analysis: area, bending, velocity, spine length, head radius, midpoint radius, tail radius, perimeter, head angular velocity, midpoint angular velocity, and tail angular velocity. Distance from origin is also included for data filtering purposes.