ИСТИНА

The study of spatial navigation in three-dimensional environments has expanded rapidly, since traditional 2D paradigms fail to capture naturalistic exploration [1-2]. Place cells in rodents encode volumetric space and reveal properties of cognitive maps that remain obscured in planar arenas [3]. Although multi-camera triangulation and depth-sensing cameras have been applied [4-5], these approaches require complex hardware setups. Here, we extend the Sphynx [6] software to reconstruct 3D trajectories and extract behavioral variables from single-camera recordings. 1) R. Hayman, M. A. Verriotis, A. Jovalekic, A. A. Fenton, and K. J. Jeffery, “Anisotropic encoding of three-dimensional space by place cells and grid cells,” Nat. Neurosci., vol. 14, no. 9, pp. 1182–1188, Sep. 2011 2) M. M. Yartsev and N. Ulanovsky, “Representation of three-dimensional space in the hippocampus of flying bats,” Science, vol. 340, no. 6130, pp. 367–372, Apr. 2013 3) R. M. Grieves, S. Jedidi-Ayoub, K. Mishchanchuk et al., “The place-cell representation of volumetric space in rats,” Nat. Commun., vol. 11, p. 789, 2020 4) T. Nath, A. Mathis, A. C. Chen, A. Patel, M. Bethge, and M. W. Mathis, “Using DeepLabCut for 3D markerless pose estimation across species and behaviors,” Nat. Protoc., vol. 14, pp. 2152–2176, 2019 5) A. Wiltschko, M. Johnson, G. Iurilli, R. Peterson, J. Katon, S. Pashkovski, V. Abraira, R. Adams, S. Datta. “Mapping Sub-Second Structure in Mouse Behavior,” Neuron, vol. 88(6), pp. 1121–1135, December 2015 6) V. Plusnin et al., "Sphynx: An Automated Behavioral Analysis Tool for Neuronal Selectivity Identification," 2024 Sixth International Conference Neurotechnologies and Neurointerfaces (CNN), Kaliningrad, Russian Federation, 2024, pp. 156-159.