Todd M Gureckis

Summary

Affiliation: New York University
Country: USA

Publications

  1. pmc Short-term gains, long-term pains: how cues about state aid learning in dynamic environments
    Todd M Gureckis
    Department of Psychology, New York University, 6 Washington Place, New York, NY 10003, USA
    Cognition 113:293-313. 2009
  2. doi request reprint Re-evaluating dissociations between implicit and explicit category learning: an event-related fMRI study
    Todd M Gureckis
    Department of Psychology, New York University, 6 Washington Place, New York, NY 10003, USA
    J Cogn Neurosci 23:1697-709. 2011
  3. doi request reprint Regulatory fit and systematic exploration in a dynamic decision-making environment
    A Ross Otto
    Department of Psychology, University of Texas, Austin, TX 78712, USA
    J Exp Psychol Learn Mem Cogn 36:797-804. 2010
  4. ncbi request reprint Models in search of a brain
    Bradley C Love
    Department of Psychology, University of Texas, Austin, Texas 78712 0187, USA
    Cogn Affect Behav Neurosci 7:90-108. 2007
  5. pmc Evaluating Amazon's Mechanical Turk as a tool for experimental behavioral research
    Matthew J C Crump
    Department of Psychology, Brooklyn College of CUNY, Brooklyn, New York, USA
    PLoS ONE 8:e57410. 2013
  6. ncbi request reprint SUSTAIN: a network model of category learning
    Bradley C Love
    Department of Psychology, University of Texas at Austin, Austin, TX 78712, USA
    Psychol Rev 111:309-32. 2004
  7. ncbi request reprint Navigating through abstract decision spaces: evaluating the role of state generalization in a dynamic decision-making task
    A Ross Otto
    Department of Psychology, University of Texas, Austin, Texas 78712, USA
    Psychon Bull Rev 16:957-63. 2009

Detail Information

Publications7

  1. pmc Short-term gains, long-term pains: how cues about state aid learning in dynamic environments
    Todd M Gureckis
    Department of Psychology, New York University, 6 Washington Place, New York, NY 10003, USA
    Cognition 113:293-313. 2009
    ....
  2. doi request reprint Re-evaluating dissociations between implicit and explicit category learning: an event-related fMRI study
    Todd M Gureckis
    Department of Psychology, New York University, 6 Washington Place, New York, NY 10003, USA
    J Cogn Neurosci 23:1697-709. 2011
    ....
  3. doi request reprint Regulatory fit and systematic exploration in a dynamic decision-making environment
    A Ross Otto
    Department of Psychology, University of Texas, Austin, TX 78712, USA
    J Exp Psychol Learn Mem Cogn 36:797-804. 2010
    ..Implications for contemporary models of human reinforcement learning are discussed...
  4. ncbi request reprint Models in search of a brain
    Bradley C Love
    Department of Psychology, University of Texas, Austin, Texas 78712 0187, USA
    Cogn Affect Behav Neurosci 7:90-108. 2007
    ..Thus, the model holds that the line separating episodic and semantic information can become blurred. Dissociations (categorization vs. recognition) are explained in terms of cluster recruitment demands...
  5. pmc Evaluating Amazon's Mechanical Turk as a tool for experimental behavioral research
    Matthew J C Crump
    Department of Psychology, Brooklyn College of CUNY, Brooklyn, New York, USA
    PLoS ONE 8:e57410. 2013
    ..A number of important lessons were encountered in the process of conducting these replications that should be of value to other researchers...
  6. ncbi request reprint SUSTAIN: a network model of category learning
    Bradley C Love
    Department of Psychology, University of Texas at Austin, Austin, TX 78712, USA
    Psychol Rev 111:309-32. 2004
    ..SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning...
  7. ncbi request reprint Navigating through abstract decision spaces: evaluating the role of state generalization in a dynamic decision-making task
    A Ross Otto
    Department of Psychology, University of Texas, Austin, Texas 78712, USA
    Psychon Bull Rev 16:957-63. 2009
    ..We found support for this hypothesis in an experiment in which generalizations based on this state information worked to the benefit or detriment of task performance, depending on the task's payoff structure...