Resource for the Study of Neural Models of Behavior

Home
Research
-VR Lab
---People
---Experiments
---Equipment
---Papers
---User Tools
-SOSI Lab
-SIM Lab
The Virtual Reality Laboratory

Home   |   People   |   Experiments   |   Equipment   |   Publications

Experiments

Virtual Environments Photo Gallery

Baufix  |   Bricks   |   VR-Lab   |   Phantom   |   SGI Town


Baufix (Baufix VR Environment)

This 3-dimensional environment has toy "Baufix" construction pieces that can be moved using a Fastrak as a 3-D mouse. The environment is rendered using an SGI Onxy 2. Direction of gaze in the environment is monitored using the ASL 501 eye tracker mounted in the HMD. Head position is measured using a Fastrak position tracker. Head, eye, and hand movements are recorded in the data stream. A video record of performance with direction of gaze superimposed is also made. In the current paradigm, observers copy a model pattern shown at the top of the display, using pieces in the area on the right. This environment complements the driving environment by allowing investigation of visuo-motor coordination in the space near the observer. Current experiments investigate learning of the model pattern, eye movement targeting, and eye, head, and hand coordination.


Bricks (Bricks Paradigm)

Driving and Attention (SGI VR Driving Environment)

The highly task-specific fixation patterns revealed in performance of natural tasks demonstrate the fundamentally active nature of vision, and suggest that in many situations, top-down processes may be a major factor in the acquisition of visual information. Understanding how a top-down visual system could function requires understanding the mechanisms that control the initiation of the different task-specific computations at the appropriate time. This is particularly difficult in dynamic environments, like driving, where many aspects of the visual input may be unpredictable. We therefore examined drivers’ ability to detect Stop signs in a virtual environment when the signs were visible for restricted periods of time. Detection performance is heavily modulated both by the instructions and the local visual context. This suggests that visibility of the signs requires active search, and that the frequency of this search is influenced by learnt knowledge of the probabilistic structure of the environment.

Driving Example Movie 1

Driving Example Movie 2



Home   |   People   |   Experiments   |   Equipment   |   Publications


Last Updated October 2002 by B. Sullivan