Spatial Navigation by Boundaries and Landmarks in Williams Syndrome in a Virtual Environment

2017 ◽  
pp. 83-89
Author(s):  
Marilina Mastrogiuseppe ◽  
Victor Chukwuemeka Umeh ◽  
Sang Ah Lee
Keyword(s):  
Virtual Environment ◽  
Williams Syndrome ◽  
Spatial Navigation

An fMRI study examining spatial navigation through a virtual environment: Partial least squares analysis

2005 ◽  
Author(s):  
Richard Mraz ◽  
Nancy J. Lobaugh ◽  
Genevieve Quintin ◽  
Konstantine K. Kakzanis ◽  
Simon J. Graham
Keyword(s):  
Least Squares ◽  
Virtual Environment ◽  
Partial Least Squares ◽  
Spatial Navigation ◽  
Partial Least Squares Analysis ◽  
Fmri Study

scholarly journals How useful are landmarks when learning a route in a virtual environment? Evidence from typical development and Williams syndrome

2012 ◽  
Vol 111 (4) ◽  
pp. 571-586 ◽  
Author(s):  
Emily K. Farran ◽  
Yannick Courbois ◽  
Jo Van Herwegen ◽  
Mark Blades
Keyword(s):  
Virtual Environment ◽  
Williams Syndrome ◽  
Typical Development

Spatial Navigation Assistance System for Large Virtual Environments

2011 ◽  
pp. 265-283
Author(s):  
Mehmed Kantardzic ◽  
Pedram Sadeghian ◽  
Walaa M. Sheta
Keyword(s):  
Virtual Environments ◽  
Virtual Environment ◽  
Spatial Navigation ◽  
Spatial Knowledge ◽  
Assistance System ◽  
Navigation Data ◽  
Navigation Assistance ◽  
Novice Users ◽  
The Cost

Advances in computing techniques, as well as the reduction in the cost of technology have made possible the viability and spread of large virtual environments. However, efficient navigation within these environments remains problematic for novice users. Novice users often report being lost, disorientated, and lacking the spatial knowledge to make appropriate decisions concerning navigation tasks. In this chapter, we propose the Frequent Wayfinding-Sequence (FWS) methodology to mine the sequences representing the routes taken by experienced users of a virtual environment in order to derive informative navigation models. The models are used to build a navigation assistance interface. We conducted several experiments using our methodology in simulated virtual environments. The results indicate that our approach is efficient in extracting and formalizing recommend routes of travel from the navigation data of previous users of large virtual environments.

EXPRESS: Resilient Allocentric Reorientation Following Transfer From the Inside to the Outside of an Arena

2021 ◽  
pp. 174702182110213
Author(s):  
Luke J. Holden ◽  
Emma J. Whitt ◽  
Mark Haselgrove
Keyword(s):  
Virtual Environment ◽  
Spatial Navigation ◽  
Single Test ◽  
Visual Appearance ◽  
Internet Connection ◽  
Training Stage ◽  
Human Participants ◽  
The Right ◽  
Previous Training ◽  
Start Location

In two virtual spatial-navigation experiments, human participants were trained to find a hidden goal (an “internet connection” point) that was located adjacent to one of the right-angled corners of a cross-shaped virtual environment. The location of the goal was defined solely with respect to the geometry of the environmental structure. Training trials started from a single central start location (Experiment 1) or from multiple start locations over two, four or sixteen training trials (Experiment 2). Following training, participants were placed onto the outside of the same environment and asked to again find the connection point (which, unbeknown to participants, was removed) during a single test-trial. The results from both experiments revealed that participants spent more time searching in regions on the outside of the environment that were closest to the location where the hidden goal was position during the previous training stage. In contrast, participants spent very little time searching in regions whose visual appearance matched those regions that contained the hidden goal during training. These results reproduce the findings from previous research which supports the idea of an allocentric encoding of the shape of the environment during navigation, and further implies that this encoding is relatively resilient to manipulations that might be expected to undermine it.

Spatial Navigation Assistance System for Large Virtual Environments

2008 ◽  
pp. 1573-1589
Author(s):  
Mehmed Kantardzic ◽  
Pedram Sadeghian ◽  
Walaa M. Sheta
Keyword(s):  
Virtual Environments ◽  
Virtual Environment ◽  
Spatial Navigation ◽  
Spatial Knowledge ◽  
Assistance System ◽  
Navigation Data ◽  
Navigation Assistance ◽  
Novice Users ◽  
The Cost

Advances in computing techniques, as well as the reduction in the cost of technology have made possible the viability and spread of large virtual environments. However, efficient navigation within these environments remains problematic for novice users. Novice users often report being lost, disorientated, and lacking the spatial knowledge to make appropriate decisions concerning navigation tasks. In this chapter, we propose the Frequent Wayfinding-Sequence (FWS) methodology to mine the sequences representing the routes taken by experienced users of a virtual environment in order to derive informative navigation models. The models are used to build a navigation assistance interface. We conducted several experiments using our methodology in simulated virtual environments. The results indicate that our approach is efficient in extracting and formalizing recommend routes of travel from the navigation data of previous users of large virtual environments.

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