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  1. Is blindsight possible under signal detection theory? Comment on Phillips (2021).Mathias Michel & Hakwan Lau - 2021 - Psychological Review 128 (3):585-591.
    Phillips argues that blindsight is due to response criterion artefacts under degraded conscious vision. His view provides alternative explanations for some studies, but may not work well when one considers several key findings in conjunction. Empirically, not all criterion effects are decidedly non-perceptual. Awareness is not completely abolished for some stimuli, in some patients. But in other cases, it was clearly impaired relative to the corresponding visual sensitivity. This relative dissociation is what makes blindsight so important and interesting.
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  • A context noise model of episodic word recognition.Simon Dennis & Michael S. Humphreys - 2001 - Psychological Review 108 (2):452-478.
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  • Signal detection theory with finite mixture distributions: Theoretical developments with applications to recognition memory.Lawrence T. DeCarlo - 2002 - Psychological Review 109 (4):710-721.
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  • Context Noise and Item Noise Jointly Determine Recognition Memory: A Comment on Dennis and Humphreys (2001).Amy H. Criss & Richard M. Shiffrin - 2004 - Psychological Review 111 (3):800-807.
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  • Criterion Setting and the Dynamics of Recognition Memory.Gregory E. Cox & Richard M. Shiffrin - 2012 - Topics in Cognitive Science 4 (1):135-150.
    Models of recognition memory have traditionally struggled with the puzzle of criterion setting, a problem that is particularly acute in cases in which items for study and test are of widely varying types, with differing degrees of baseline familiarity and experience (e.g., words vs. random dot patterns). We present a dynamic model of the recognition process that addresses the criterion setting problem and produces joint predictions for choice and reaction time. In this model, recognition decisions are based not on the (...)
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  • A dynamic approach to recognition memory.Gregory E. Cox & Richard M. Shiffrin - 2017 - Psychological Review 124 (6):795-860.
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  • Holistic Representations of Internal and External Face Features are Used to Support Recognition.Jessica P. K. Chan & Jennifer D. Ryan - 2012 - Frontiers in Psychology 3.
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  • Signal detection with criterion noise: Applications to recognition memory.Aaron S. Benjamin, Michael Diaz & Serena Wee - 2009 - Psychological Review 116 (1):84-115.
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  • Superadditive memory strength for item and source recognition: The role of hierarchical relational binding in the medial temporal lobe.Arthur P. Shimamura & Thomas D. Wickens - 2009 - Psychological Review 116 (1):1-19.
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  • Modeling memory and perception.Richard M. Shiffrin - 2003 - Cognitive Science 27 (3):341-378.
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  • A Bayesian model for implicit effects in perceptual identification.Lael J. Schooler, Richard M. Shiffrin & Jeroen G. W. Raaijmakers - 2001 - Psychological Review 108 (1):257-272.
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  • Modeling hippocampal and neocortical contributions to recognition memory: A complementary-learning-systems approach.Kenneth A. Norman & Randall C. O'Reilly - 2003 - Psychological Review 110 (4):611-646.
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  • Postscript: Reply to Macmillan and Rotello (2006).Bennet Murdock - 2006 - Psychological Review 113 (3):655-656.
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  • Decision-making models of remember-know judgments: Comment on Rotello, Macmillan, and Reeder (2004).Bennet Murdock - 2006 - Psychological Review 113 (3):648-655.
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  • Counter model for word identification: Reply to Bowers (1999).Gail McKoon & Roger Ratcliff - 2001 - Psychological Review 108 (3):674-681.
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  • The Place of Modeling in Cognitive Science.James L. McClelland - 2009 - Topics in Cognitive Science 1 (1):11-38.
    I consider the role of cognitive modeling in cognitive science. Modeling, and the computers that enable it, are central to the field, but the role of modeling is often misunderstood. Models are not intended to capture fully the processes they attempt to elucidate. Rather, they are explorations of ideas about the nature of cognitive processes. In these explorations, simplification is essential—through simplification, the implications of the central ideas become more transparent. This is not to say that simplification has no downsides; (...)
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  • Letting structure emerge: connectionist and dynamical systems approaches to cognition.James L. McClelland, Matthew M. Botvinick, David C. Noelle, David C. Plaut, Timothy T. Rogers, Mark S. Seidenberg & Linda B. Smith - 2010 - Trends in Cognitive Sciences 14 (8):348-356.
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  • Modeling Recognition Memory Using the Similarity Structure of Natural Input.Joyca P. W. Lacroix, Jaap M. J. Murre, Eric O. Postma & H. Jaap Herik - 2006 - Cognitive Science 30 (1):121-145.
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  • Modeling Recognition Memory Using the Similarity Structure of Natural Input.Joyca P. W. Lacroix, Jaap M. J. Murre, Eric O. Postma & H. Jaap van den Herik - 2006 - Cognitive Science 30 (1):121-145.
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  • Generalization through the recurrent interaction of episodic memories: A model of the hippocampal system.Dharshan Kumaran & James L. McClelland - 2012 - Psychological Review 119 (3):573-616.
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  • Letting Structure Emerge: Connectionist and Dynamical Systems Approaches to Cognition.Linda B. Smith James L. McClelland, Matthew M. Botvinick, David C. Noelle, David C. Plaut, Timothy T. Rogers, Mark S. Seidenberg - 2010 - Trends in Cognitive Sciences 14 (8):348.
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  • Simple Co‐Occurrence Statistics Reproducibly Predict Association Ratings.Markus J. Hofmann, Chris Biemann, Chris Westbury, Mariam Murusidze, Markus Conrad & Arthur M. Jacobs - 2018 - Cognitive Science 42 (7):2287-2312.
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  • Eye-tracking the own-race bias in face recognition: Revealing the perceptual and socio-cognitive mechanisms.Peter J. Hills & J. Michael Pake - 2013 - Cognition 129 (3):586-597.
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  • In praise of secular Bayesianism.Evan Heit & Shanna Erickson - 2011 - Behavioral and Brain Sciences 34 (4):202-202.
    It is timely to assess Bayesian models, but Bayesianism is not a religion. Bayesian modeling is typically used as a tool to explain human data. Bayesian models are sometimes equivalent to other models, but have the advantage of explicitly integrating prior hypotheses with new observations. Any lack of representational or neural assumptions may be an advantage rather than a disadvantage.
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  • Eye movements and the label feedback effect: Speaking modulates visual search via template integrity.Katherine P. Hebert, Stephen D. Goldinger & Stephen C. Walenchok - 2021 - Cognition 210 (C):104587.
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