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. Author manuscript; available in PMC: 2012 Feb 1.
Published in final edited form as: Neurobiol Learn Mem. 2010 Sep 24;95(2):145–151. doi: 10.1016/j.nlm.2010.09.010

Figure 5.

Figure 5

Augmented Hebbian Reweighting Model (AHRM, Petrov, Dosher & Lu, 2005, 2006) passes stimulus images through a representational system of orientation and spatial-frequency tuned units, with non-linearities and spatial pooling. These activations, along with inputs to a bias and feedback unit are weighted by the task-specific weighting system to yield a decision. The AHRM has predicted the dynamics of learning in non-stationary training, the various roles of feedback in learning, and performance in external noise paradigms. (After Petrov et al, 2005).