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Matthew M. Botvinick [16]Matthew Botvinick [8]
  1.  53
    Conflict monitoring and cognitive control.Matthew M. Botvinick, Todd S. Braver, Deanna M. Barch, Cameron S. Carter & Jonathan D. Cohen - 2001 - Psychological Review 108 (3):624-652.
  2. Conflict monitoring and anterior cingulate cortex: an update.Matthew M. Botvinick, Jonathan D. Cohen & Cameron S. Carter - 2004 - Trends in Cognitive Sciences 8 (12):539-546.
    One hypothesis concerning the human dorsal anterior cingulate cortex (ACC) is that it functions, in part, to signal the occurrence of conflicts in information processing, thereby triggering compensatory adjustments in cognitive control. Since this idea was first proposed, a great deal of relevant empirical evidence has accrued. This evidence has largely corroborated the conflict-monitoring hypothesis, and some very recent work has provided striking new support for the theory. At the same time, other findings have posed specific challenges, especially concerning the (...)
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  3.  74
    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.
  4.  32
    The Neural Basis of Error Detection: Conflict Monitoring and the Error-Related Negativity.Nick Yeung, Matthew M. Botvinick & Jonathan D. Cohen - 2004 - Psychological Review 111 (4):931-959.
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  5.  23
    Hierarchically organized behavior and its neural foundations: A reinforcement learning perspective.Matthew M. Botvinick, Yael Niv & Andrew C. Barto - 2009 - Cognition 113 (3):262-280.
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  6.  37
    The Computational and Neural Basis of Cognitive Control: Charted Territory and New Frontiers.Matthew M. Botvinick - 2014 - Cognitive Science 38 (6):1249-1285.
    Cognitive control has long been one of the most active areas of computational modeling work in cognitive science. The focus on computational models as a medium for specifying and developing theory predates the PDP books, and cognitive control was not one of the areas on which they focused. However, the framework they provided has injected work on cognitive control with new energy and new ideas. On the occasion of the books' anniversary, we review computational modeling in the study of cognitive (...)
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  7.  45
    Hierarchical models of behavior and prefrontal function.Matthew M. Botvinick - 2008 - Trends in Cognitive Sciences 12 (5):201.
  8.  9
    Doing Without Schema Hierarchies: A Recurrent Connectionist Approach to Normal and Impaired Routine Sequential Action.Matthew Botvinick & David C. Plaut - 2004 - Psychological Review 111 (2):395-429.
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  9. Planning as inference.Matthew Botvinick & Marc Toussaint - 2012 - Trends in Cognitive Sciences 16 (10):485-488.
  10.  2
    Hierarchically organized behavior and its neural foundations: A reinforcement learning perspective.Matthew M. Botvinick, Yael Niv & Andew G. Barto - 2009 - Cognition 113 (3):262-280.
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  11.  22
    Goal-directed decision making as probabilistic inference: A computational framework and potential neural correlates.Alec Solway & Matthew M. Botvinick - 2012 - Psychological Review 119 (1):120-154.
  12.  21
    Short-term memory for serial order: A recurrent neural network model.Matthew M. Botvinick & David C. Plaut - 2006 - Psychological Review 113 (2):201-233.
  13.  9
    Such stuff as habits are made on: A reply to Cooper and Shallice (2006).Matthew M. Botvinick & David C. Plaut - 2006 - Psychological Review 113 (4):917-927.
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  14.  39
    Building machines that learn and think for themselves.Matthew Botvinick, David G. T. Barrett, Peter Battaglia, Nando de Freitas, Darshan Kumaran, Joel Z. Leibo, Timothy Lillicrap, Joseph Modayil, Shakir Mohamed, Neil C. Rabinowitz, Danilo J. Rezende, Adam Santoro, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg & Demis Hassabis - 2017 - Behavioral and Brain Sciences 40.
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  15.  56
    Conflict monitoring in cognition-emotion competition.Samuel M. McClure, Matthew M. Botvinick, Nick Yeung, Joshua D. Greene & Jonathan D. Cohen - 2007 - In James J. Gross (ed.), Handbook of Emotion Regulation. Guilford Press.
  16.  3
    Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments.Francisco Pereira, Matthew Botvinick & Greg Detre - 2013 - Artificial Intelligence 194 (C):240-252.
  17.  25
    Effects of domain-specific knowledge on memory for serial order.Matthew M. Botvinick - 2005 - Cognition 97 (2):135-151.
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  18.  9
    Empirical and computational support for context-dependent representations of serial order: Reply to Bowers, Damian, and Davis (2009).Matthew M. Botvinick & David C. Plaut - 2009 - Psychological Review 116 (4):998-1001.
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  19. Commentary: Why I Am Not a Dynamicist.Matthew Botvinick - 2012 - Topics in Cognitive Science 4 (1):78-83.
    The dynamical systems approach in cognitive science offers a potentially useful perspective on both brain and behavior. Indeed, the importation of formal tools from dynamical systems research has already paid off for our field in many ways. However, like some other theoretical perspectives in cognitive science, the dynamical systems approach comes in both moderate or pragmatic and “fundamentalist” varieties (Jones & Love, 2011). In the latter form, dynamical systems theory can rise to some stirring rhetorical heights. However, as argued here, (...)
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  20.  33
    The intrinsic cost of cognitive control.Wouter Kool & Matthew Botvinick - 2013 - Behavioral and Brain Sciences 36 (6):661-698.
    Kurzban and colleagues carry forward an important contemporary movement in cognitive control research, tending away from resource-based models and toward a framework focusing on motivation or value. However, their specific proposal, centering on opportunity costs, appears problematic. We favor a simpler view, according to which the exertion of cognitive control carries intrinsic subjective costs.
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  21.  1
    Meta-Learned Models of Cognition.Marcel Binz, Ishita Dasgupta, Akshay K. Jagadish, Matthew Botvinick, Jane X. Wang & Eric Schulz - forthcoming - Behavioral and Brain Sciences:1-38.
    Psychologists and neuroscientists extensively rely on computational models for studying and analyzing the human mind. Traditionally, such computational models have been hand-designed by expert researchers. Two prominent examples are cognitive architectures and Bayesian models of cognition. While the former requires the specification of a fixed set of computational structures and a definition of how these structures interact with each other, the latter necessitates the commitment to a particular prior and a likelihood function which – in combination with Bayes’ rule – (...)
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  22.  6
    Postscript: The way forward: Comment.Matthew M. Botvinick & David C. Plaut - 2006 - Psychological Review 113 (4):928-928.
  23.  5
    Postscript: Winnowing out some take-home points.Matthew M. Botvinick & David C. Plaut - 2009 - Psychological Review 116 (4):1001-1002.
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