I'm looking for a toolbox to model visual search performance in a singleton search task based on line orientations (you need to find a line that is most different from all others in it's orientation).
The desirable features would be:
- Feature-detectors that resemble real neurons.
- Memory for distribution of distractors in feature space during previous trials.
Is there something like that? I also know that sometimes similar tasks are studied in texture discrimination. Maybe there is something close to what I need in that domain?