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Jonathan D. Cohen [29]Jonathan David Cohen [1]
  1.  64
    An Integrative Theory of Prefrontal Cortex Function.Earl K. Miller & Jonathan D. Cohen - 2001 - Annual Review of Neuroscience 24 (1):167-202.
    The prefrontal cortex has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals. Its neural basis, however, has remained a mystery. Here, we propose that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of (...)
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  2.  66
    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.
  3. Pushing moral buttons: The interaction between personal force and intention in moral judgment.Joshua D. Greene, Fiery A. Cushman, Lisa E. Stewart, Kelly Lowenberg, Leigh E. Nystrom & Jonathan D. Cohen - 2009 - Cognition 111 (3):364-371.
    In some cases people judge it morally acceptable to sacrifice one person’s life in order to save several other lives, while in other similar cases they make the opposite judgment. Researchers have identified two general factors that may explain this phenomenon at the stimulus level: (1) the agent’s intention (i.e. whether the harmful event is intended as a means or merely foreseen as a side-effect) and (2) whether the agent harms the victim in a manner that is relatively “direct” or (...)
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  4. Cognitive load selectively interferes with utilitarian moral judgment.Joshua D. Greene, Sylvia A. Morelli, Kelly Lowenberg, Leigh E. Nystrom & Jonathan D. Cohen - 2008 - Cognition 107 (3):1144-1154.
    Traditional theories of moral development emphasize the role of controlled cognition in mature moral judgment, while a more recent trend emphasizes intuitive and emotional processes. Here we test a dual-process theory synthesizing these perspectives. More specifically, our theory associates utilitarian moral judgment (approving of harmful actions that maximize good consequences) with controlled cognitive processes and associates non-utilitarian moral judgment with automatic emotional responses. Consistent with this theory, we find that a cognitive load manipulation selectively interferes with utilitarian judgment. This interference (...)
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  5. 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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  6.  40
    On the control of automatic processes: A parallel distributed processing account of the Stroop effect.Jonathan D. Cohen, Kevin Dunbar & James L. McClelland - 1990 - Psychological Review 97 (3):332-361.
  7.  49
    Context, cortex, and dopamine: A connectionist approach to behavior and biology in schizophrenia.Jonathan D. Cohen & David Servan-Schreiber - 1992 - Psychological Review 99 (1):45-77.
  8.  44
    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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  9.  42
    The physics of optimal decision making: A formal analysis of models of performance in two-alternative forced-choice tasks.Rafal Bogacz, Eric Brown, Jeff Moehlis, Philip Holmes & Jonathan D. Cohen - 2006 - Psychological Review 113 (4):700-765.
  10.  92
    Neuroeconomics: cross-currents in research on decision-making.Alan G. Sanfey, George Loewenstein, Samuel M. McClure & Jonathan D. Cohen - 2006 - Trends in Cognitive Sciences 10 (3):108-116.
  11. Should I stay or should I go? How the human brain manages the trade-off between exploitation and exploration.Jonathan D. Cohen, Samuel M. McClure & Yu & J. Angela - 2008 - In Jon Driver, Patrick Haggard & Tim Shallice (eds.), Mental Processes in the Human Brain. Oxford University Press.
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  12.  27
    The temporal dynamics of opportunity costs: A normative account of cognitive fatigue and boredom.Mayank Agrawal, Marcelo G. Mattar, Jonathan D. Cohen & Nathaniel D. Daw - 2022 - Psychological Review 129 (3):564-585.
  13.  63
    Context processing in older adults: evidence for a theory relating cognitive control to neurobiology in healthy aging.Todd S. Braver, Deanna M. Barch, Beth A. Keys, Cameron S. Carter, Jonathan D. Cohen, Jeffrey A. Kaye, Jeri S. Janowsky, Stephan F. Taylor, Jerome A. Yesavage & Martin S. Mumenthaler - 2001 - Journal of Experimental Psychology: General 130 (4):746.
  14.  37
    Cyclical population dynamics of automatic versus controlled processing: An evolutionary pendulum.David G. Rand, Damon Tomlin, Adam Bear, Elliot A. Ludvig & Jonathan D. Cohen - 2017 - Psychological Review 124 (5):626-642.
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  15.  47
    When working memory may be just working, not memory.Andre Beukers, Maia Hamin, Kenneth A. Norman & Jonathan D. Cohen - 2024 - Psychological Review 131 (2):563-577.
  16.  44
    Optimality and Some of Its Discontents: Successes and Shortcomings of Existing Models for Binary Decisions.Philip Holmes & Jonathan D. Cohen - 2014 - Topics in Cognitive Science 6 (2):258-278.
    We review how leaky competing accumulators (LCAs) can be used to model decision making in two‐alternative, forced‐choice tasks, and we show how they reduce to drift diffusion (DD) processes in special cases. As continuum limits of the sequential probability ratio test, DD processes are optimal in producing decisions of specified accuracy in the shortest possible time. Furthermore, the DD model can be used to derive a speed–accuracy trade‐off that optimizes reward rate for a restricted class of two alternative forced‐choice decision (...)
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  17.  61
    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.
  18.  28
    Neural mechanism for the magical number 4: Competitive interactions and nonlinear oscillation.Marius Usher, Jonathan D. Cohen, Henk Haarmann & David Horn - 2001 - Behavioral and Brain Sciences 24 (1):151-152.
    The aim of our commentary is to strengthen Cowan's proposal for an inherent capacity limitation in STM by suggesting a neurobiological mechanism based on competitive networks and nonlinear oscillations that avoids some of the shortcomings of the scheme discussed in the target article (Lisman & Idiart 1995).
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  19.  18
    Human inference in changing environments with temporal structure.Arthur Prat-Carrabin, Robert C. Wilson, Jonathan D. Cohen & Rava Azeredo da Silveira - 2021 - Psychological Review 128 (5):879-912.
  20.  17
    Amplified selectivity in cognitive processing implements the neural gain model of norepinephrine function.Eran Eldar, Jonathan D. Cohen & Yael Niv - 2016 - Behavioral and Brain Sciences 39.
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  21.  17
    Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large‐Scale Text Corpora.Marius Cătălin Iordan, Tyler Giallanza, Cameron T. Ellis, Nicole M. Beckage & Jonathan D. Cohen - 2022 - Cognitive Science 46 (2):e13085.
    Applying machine learning algorithms to automatically infer relationships between concepts from large-scale collections of documents presents a unique opportunity to investigate at scale how human semantic knowledge is organized, how people use it to make fundamental judgments (“How similar are cats and bears?”), and how these judgments depend on the features that describe concepts (e.g., size, furriness). However, efforts to date have exhibited a substantial discrepancy between algorithm predictions and human empirical judgments. Here, we introduce a novel approach to generating (...)
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  22.  17
    Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large‐Scale Text Corpora.Marius Cătălin Iordan, Tyler Giallanza, Cameron T. Ellis, Nicole M. Beckage & Jonathan D. Cohen - 2022 - Cognitive Science 46 (2):e13085.
    Cognitive Science, Volume 46, Issue 2, February 2022.
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  23.  7
    A Commentary on Kinsbourne and Hobson.Jonathan D. Cohen - 1997 - In Jonathan D. Cohen & Jonathan W. Schooler (eds.), Scientific Approaches to Consciousness. Lawrence Erlbaum. pp. 25--397.
  24.  13
    A PDP approach to set size effects within the Stroop task: Reply to Kanne, Balota, Spieler, and Faust (1998).Jonathan D. Cohen, Marius Usher & James L. McClelland - 1998 - Psychological Review 105 (1):188-194.
  25.  11
    Los Angeles, CA, USA.Jonathan D. Cohen, Fergus Im Craik, Ieffrey L. Cummings & Lauren Dade - 2002 - In Donald T. Stuss & Robert T. Knight (eds.), Principles of Frontal Lobe Function. Oxford University Press.
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  26. Scientific Approaches to Consciousness.Jonathan D. Cohen & Jonathan W. Schooler (eds.) - 1997 - Lawrence Erlbaum.
  27.  10
    Frontal eye fields: Inhibition through competition.Steven D. Forman, Jonathan D. Cohen & Mark H. Johnson - 1993 - Behavioral and Brain Sciences 16 (3):578-578.
  28.  27
    Brain systems and economics.Alan G. Sanfey, George Loewenstein, Samuel M. McClure & Jonathan D. Cohen - 2006 - Trends in Cognitive Sciences 10 (3):108-116.
  29. On the neural implementation of optimal decisions.Patrick Simen, Philip Holmes & Jonathan D. Cohen - 2008 - In Ezequiel Morsella, John A. Bargh & Peter M. Gollwitzer (eds.), Oxford handbook of human action. New York: Oxford University Press.
     
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