Design of a Virtual Reality Navigational (VRN) experiment for assessment of egocentric spatial cognition.
Virtual reality (VR) experiments are commonly used to assess human brain functions. We orient ourselves in an environment by computing precise self-to-object spatial relations (egocentric orientation) as well as object-to-object spatial relations (allocentric orientation). Egocentric orientation involves cues that depend on the position of the observer (i.e. left-right, front-behind), whereas allocentric orientation is maintained through the use of environmental features such as landmarks. As such, allocentric orientation involves short-term memory, whereas egocentric orientation does not. This paper presents a Virtual Reality Navigational (VRN) experiment specifically designed to assess egocentric spatial cognition. The design aimed to minimize the effect of spatial cues or landmarks for human navigation in a naturalistic VR environment. The VRN experiment designed for this study, called the Virtual House, is a symmetric three story cubic building, with 3 windows on each side on every floor, and one entrance on each side of the building. In each trial, a window is marked by a pseudo-random sequence as the objective. The marked window is shown to the participant from an outdoor view. The task is to reach the objective window using the shortest path through the building. The experiment entails 2 sets of 8 trials to cover all possibilities. The participants' performance error is measured by the difference between their traversed distance trajectory and the shortest natural distance (calculated using the VR engine), normalized by the shortest distance, in each trial. Fifty-two cognitively healthy adults participated in the study. The results show no learning effect during the 16 trails, implying that the experiment does not rely on short-term memory. Furthermore, the subjects' normalized performance error showed an almost linear increase with age, implying that egocentric spatial cognition ability declines with age.
Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada. byagowi@cc.umanitoba.ca
Ahmad
A
Byagowi
Zahra
Z
Moussavi
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003071:Cognition / Q000502:physiology*; D003196:Computer Graphics; D005260:Female; D006801:Humans; D008875:Middle Aged; D009949:Orientation / Q000502:physiology*; D012107:Research Design; D013028:Space Perception / Q000502:physiology*; D014584:User-Computer Interface; D055815:Young Adult