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. Author manuscript; available in PMC: 2010 Mar 20.
Published in final edited form as: Learn Percept. 2009 Jun 1;1(1):37–58. doi: 10.1556/LP.1.2009.1.4

Figure 5.

Figure 5

Schematic of the augmented Hebbian reweighting model consists of a stable representation system (top) and weight structure that associates a pattern of input activity to a decision unit (bottom). The representation system computes an activity pattern over 35 units reflecting activity through a spatial filter centered at one of 5 spatial frequencies and 7 orientations, combined over phase, normalized, and averaged in the spatial region of the Gabor. The learning system incrementally adjusts the weights to a decision unit using Hebbian associative learning, augmented by input from an external feedback signal and a bias or criterion unit.