Automated gesture tracking in head-fixed mice

Andrea Giovannucci, Eftychios A. Pnevmatikakis, Ben Deverett, Talmo Pereira, J. Fondriest, M Brady, Shaozhen Wang, Waseem Abbas, P. Parés

Journal of Neuroscience Methods · 2017 · 21 citations · 41 references

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Abstract

• The head-fixed mouse preparation offers unique advantages in a variety of experimental contexts. • We present an affordable and flexible framework for measuring behavior in head-fixed preparations. • We benchmark our algorithms against ground truth data and demonstrate good performance. • The framework is a valuable complement to recording and stimulation technologies. The preparation consisting of a head-fixed mouse on a spherical or cylindrical treadmill offers unique advantages in a variety of experimental contexts. Head fixation provides the mechanical stability necessary for optical and electrophysiological recordings and stimulation. Additionally, it can be combined with virtual environments such as T-mazes, enabling these types of recording during diverse behaviors. In this paper we present a low-cost, easy-to-build acquisition system, along with scalable computational methods to quantitatively measure behavior (locomotion and paws, whiskers, and tail motion patterns) in head-fixed mice locomoting on cylindrical or spherical treadmills. Several custom supervised and unsupervised methods have been developed for measuring behavior in mice. However, to date there is no low-cost, turn-key, general-purpose, and scalable system for acquiring and quantifying behavior in mice. We benchmark our algorithms against ground truth data generated either by manual labeling or by simpler methods of feature extraction. We demonstrate that our algorithms achieve good performance, both in supervised and unsupervised settings. We present a low-cost suite of tools for behavioral quantification, which serve as valuable complements to recording and stimulation technologies being developed for the head-fixed mouse preparation.

References

41