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  1.  55
    Complementary Learning Systems.Randall C. O’Reilly, Rajan Bhattacharyya, Michael D. Howard & Nicholas Ketz - 2014 - Cognitive Science 38 (6):1229-1248.
    This paper reviews the fate of the central ideas behind the complementary learning systems (CLS) framework as originally articulated in McClelland, McNaughton, and O’Reilly (1995). This framework explains why the brain requires two differentially specialized learning and memory systems, and it nicely specifies their central properties (i.e., the hippocampus as a sparse, pattern-separated system for rapidly learning episodic memories, and the neocortex as a distributed, overlapping system for gradually integrating across episodes to extract latent semantic structure). We review the application (...)
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  2.  24
    Recurrent Processing during Object Recognition.Randall C. O’Reilly, Dean Wyatte, Seth Herd, Brian Mingus & David J. Jilk - 2013 - Frontiers in Psychology 4.
  3.  31
    Developing PFC Representations Using Reinforcement Learning.Jeremy R. Reynolds & Randall C. O’Reilly - 2009 - Cognition 113 (3):281-292.
  4. The Neural Correlates of Cued Reward Omission.Jessica A. Mollick, Luke J. Chang, Anjali Krishnan, Thomas E. Hazy, Kai A. Krueger, Guido K. W. Frank, Tor D. Wager & Randall C. O’Reilly - 2021 - Frontiers in Human Neuroscience 15.
    Compared to our understanding of positive prediction error signals occurring due to unexpected reward outcomes, less is known about the neural circuitry in humans that drives negative prediction errors during omission of expected rewards. While classical learning theories such as Rescorla–Wagner or temporal difference learning suggest that both types of prediction errors result from a simple subtraction, there has been recent evidence suggesting that different brain regions provide input to dopamine neurons which contributes to specific components of this prediction error (...)
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