Show Thoughts

Weber and Triesch's model learns task-relevant features.

However, a brain region like the SC, which serves a very general task, cannot specialize in one task—it has to serve all goals that the system has.

It therefore should change its behavior depending on the task. Attention is one mechanism which might determine how to change behavior in a given situation.

If the goal is predictive of the input, then a purely unsupervised algorithm could take a representation of the goal as just another input.

While it is possible that the goal often is predictive of the input, some error feedback is probably necessary to tune the degree to which the algorithm can be `distracted' by task-irrelevant but interesting stimuli.