Del Grosso, Nicholas Andrew (2018): Design of virtual reality systems for animal behavior research. Dissertation, LMU München: Graduate School of Systemic Neurosciences (GSN) |
Preview |
PDF
Del_Grosso_Nicholas_Andrew.pdf 13MB |
Abstract
Virtual reality (VR) experimental behavior setups enable cognitive neuroscientists to study the integration of visual depth cues and self-motion cues into a single percept of three-dimensional space. Rodents can navigate a virtual environment by running on a spherical treadmill, but simulating locomotion in this way can both bias and suppress the frequency of their behaviors as well as introduce vestibulomotor and vestibulovisual sensory conflict during locomotion. Updating the virtual environment via the subject's own freely-moving head movements solves both the naturalistic behavior bias and vestibular conflict issues. In this thesis, I review elements of self-motion and 3D scene perception that contribute to a sense of immersion in virtual environments and suggest a freely-moving CAVE system as a VR solution for low-artifact neuroscience experiments. The manuscripts describing the 3D graphics Python package and the virtual reality setup are included. In this freely-moving CAVE VR setup, freely-moving rats demonstrate immersion in virtual environments by displaying height aversion to virtual cliffs, exploration preference of virtual objects, and spontaneously modify their locomotion trajectories near virtual walls. These experiments help bridge the classic behavior and virtual reality literature by showing that rats display similar behaviors to virtual environment features without training.
Item Type: | Theses (Dissertation, LMU Munich) |
---|---|
Keywords: | Virtual Reality, Behavior, Spatial Perception, CAVE |
Subjects: | 500 Natural sciences and mathematics 500 Natural sciences and mathematics > 570 Life sciences |
Faculties: | Graduate School of Systemic Neurosciences (GSN) |
Language: | English |
Date of oral examination: | 30. November 2018 |
1. Referee: | Sirota, Anton |
MD5 Checksum of the PDF-file: | 0a68a05f4926ed4d381a9c6da44100c1 |
MD5 Checksum of the ZIP-file: | de342ded291838d1f9abf900bb35c4e7 |
Signature of the printed copy: | 0001/UMC 26085 |
ID Code: | 23559 |
Deposited On: | 04. Feb 2019 13:41 |
Last Modified: | 23. Oct 2020 16:04 |