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. Author manuscript; available in PMC: 2009 Jul 6.
Published in final edited form as: Neurosci Biobehav Rev. 2007 Aug 10;32(2):219–236. doi: 10.1016/j.neubiorev.2007.07.008

Figure 3.

Figure 3

Simulated performance and strategies in a computational model of probabilistic category learning based on the Gluck & Myers cortico-hippocampal model. Parkinson’s disease is simulated by assuming lower learning rates in learning modules outside of the hippocampus. (A) Overall % correct performance in the simulations show that the Parkinson’s model is slower to learn relative to the intact model. (B) The models also capture the overall pattern in the strategy fits from the human data, with the Parkinson’s model better fit by suboptimal strategies. (C) Strategy fits in the Parkinson’s model demonstrate that with much extensive training, eventually the models are able to produce optimal responding.