Home
Vita
Vacations
Selected Web Pages
Experiencing Sensation and Perception
Advanced Training Institute on Web Research
Class Web Sites
Play
DRAFT
On this site, I have a little tool I developed to visualize in some fashion the way the retinal ganglion cells/LGN cells and V1 simple Cells (Hubel and Wiesel, 1962) behave when there are a lot of the cells. While I often call this a model, it is more of a tool for visualizing the output of these different levels of visual processing. The attempt is to find ways to look into these outputs and perhaps understand the nature of the information contained in these arrays of cells so that richness of visual processing can be better understood.
Background on the ganglion cells/LGN Model can be found here and here for the basic model. The ganglions cell/LGN model can process information in the three color channels (R/G, B/Y and achromatic). Information on this ability is here. Information on the modeling of eye jitter, which applies to all modeling within the program now is found here.
The effort to model simple cells is newer, the basics of this effort and the initial attempts to process this information in a meaningful manner is found here.
You can run the model/tool here as a Java Applet. In this model you can create inputs for the model using the Image Create menu. Select the type of image, alter it, press the Grab Image button and then play around with the model. I will try to add some help pages soon.
Here you can download the full Java executable .jar file where you can have full file opening capability. You can load any image (I would recommend not too big of an image). Color is fine. You can also save your model outputs, both the DOG model of retinal ganglion/LGN cells and the Gabor model of the simple cells in space delimited files that can be read by spreadsheets.
Related Sites:
 SurveyBuildR. An open-source tool for building Web-Based Surveys |
 Cognition Laboratory Experiments |
 Neuroscience Animations |
|
 Psychology Tutorials |
 Sensation and Perception Tutorials |
 Basic Neural Tutorials |
|