Outcome contingency selectively affects the neural coding of outcomes but not of tasks
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[1] B. Libet,et al. Time of conscious intention to act in relation to onset of cerebral activity (readiness-potential). The unconscious initiation of a freely voluntary act. , 1983, Brain : a journal of neurology.
[2] C. F. Kao,et al. The efficient assessment of need for cognition. , 1984, Journal of personality assessment.
[3] Richard S. Sutton,et al. Time-Derivative Models of Pavlovian Reinforcement , 1990 .
[4] M. Gabriel,et al. Learning and Computational Neuroscience: Foundations of Adaptive Networks , 1990 .
[5] C. Carver,et al. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS Scales , 1994 .
[6] Karl J. Friston,et al. Statistical parametric maps in functional imaging: A general linear approach , 1994 .
[7] J. Patton,et al. Factor structure of the Barratt impulsiveness scale. , 1995, Journal of clinical psychology.
[8] D. Meyer,et al. Executive control of cognitive processes in task switching. , 2001, Journal of experimental psychology. Human perception and performance.
[9] C. Ávila,et al. The Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) as a measure of Gray's anxiety and impulsivity dimensions. , 2001 .
[10] S. Kapur,et al. Direct Activation of the Ventral Striatum in Anticipation of Aversive Stimuli , 2003, Neuron.
[11] Brian Knutson,et al. A region of mesial prefrontal cortex tracks monetarily rewarding outcomes: characterization with rapid event-related fMRI , 2003, NeuroImage.
[12] E. Miller,et al. Neural circuits subserving the retrieval and maintenance of abstract rules. , 2003, Journal of neurophysiology.
[13] David D. Cox,et al. Functional magnetic resonance imaging (fMRI) “brain reading”: detecting and classifying distributed patterns of fMRI activity in human visual cortex , 2003, NeuroImage.
[14] Okihide Hikosaka,et al. Reward-Dependent Gain and Bias of Visual Responses in Primate Superior Colliculus , 2003, Neuron.
[15] D. Yves von Cramon,et al. Predicting events of varying probability: uncertainty investigated by fMRI , 2003, NeuroImage.
[16] W. Newsome,et al. Matching Behavior and the Representation of Value in the Parietal Cortex , 2004, Science.
[17] E. Murray,et al. Bilateral Orbital Prefrontal Cortex Lesions in Rhesus Monkeys Disrupt Choices Guided by Both Reward Value and Reward Contingency , 2004, The Journal of Neuroscience.
[18] Rebecca Elliott,et al. Instrumental responding for rewards is associated with enhanced neuronal response in subcortical reward systems , 2004, NeuroImage.
[19] David R. Anderson,et al. Multimodel Inference , 2004 .
[20] Tom M. Mitchell,et al. Learning to Decode Cognitive States from Brain Images , 2004, Machine Learning.
[21] M. Delgado,et al. Modulation of Caudate Activity by Action Contingency , 2004, Neuron.
[22] Catherine M Arrington,et al. PSYCHOLOGICAL SCIENCE Research Article The Cost of a Voluntary Task Switch , 2022 .
[23] F. Tong,et al. Decoding the visual and subjective contents of the human brain , 2005, Nature Neuroscience.
[24] W. Schultz,et al. Adaptive Coding of Reward Value by Dopamine Neurons , 2005, Science.
[25] J. C. Johnston,et al. On the limits of advance preparation for a task switch: do people prepare all the task some of the time or some of the task all the time? , 2005, Journal of experimental psychology. Human perception and performance.
[26] S. Inati,et al. An fMRI study of reward-related probability learning , 2005, NeuroImage.
[27] R. Dolan,et al. Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans , 2006, Nature.
[28] Rainer Goebel,et al. Information-based functional brain mapping. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[29] K. Doya,et al. The computational neurobiology of learning and reward , 2006, Current Opinion in Neurobiology.
[30] J. O'Doherty,et al. Model‐Based fMRI and Its Application to Reward Learning and Decision Making , 2007, Annals of the New York Academy of Sciences.
[31] E. Wagenmakers. A practical solution to the pervasive problems ofp values , 2007, Psychonomic bulletin & review.
[32] Timothy E. J. Behrens,et al. Adaptive decision making and value in the anterior cingulate cortex , 2007, NeuroImage.
[33] M. McCloskey,et al. IQ and nonplanning impulsivity are independently associated with delay discounting in middle-aged adults , 2007 .
[34] R. Passingham,et al. Reading Hidden Intentions in the Human Brain , 2007, Current Biology.
[35] Keiji Tanaka,et al. Medial prefrontal cell activity signaling prediction errors of action values , 2007, Nature Neuroscience.
[36] Jonathan W. Peirce,et al. PsychoPy—Psychophysics software in Python , 2007, Journal of Neuroscience Methods.
[37] Timothy E. J. Behrens,et al. Learning the value of information in an uncertain world , 2007, Nature Neuroscience.
[38] J. O'Doherty,et al. Decoding the neural substrates of reward-related decision making with functional MRI , 2007, Proceedings of the National Academy of Sciences.
[39] M. Brass,et al. Unconscious determinants of free decisions in the human brain , 2008, Nature Neuroscience.
[40] W. Senn,et al. Dopamine increases the gain of the input–output response of rat prefrontal pyramidal neurons. J. Neurophysiol. (in press). doi: 10.1152/jn.01098.2007 [epub ahead of print , 2008 .
[41] K. Doya. Modulators of decision making , 2008, Nature Neuroscience.
[42] John Duncan,et al. Hierarchical coding for sequential task events in the monkey prefrontal cortex , 2008, Proceedings of the National Academy of Sciences.
[43] D. Eckstein,et al. Rule-Selection and Action-Selection have a Shared Neuroanatomical Basis in the Human Prefrontal and Parietal Cortex , 2008, Cerebral cortex.
[44] Stefan Bode,et al. Decoding sequential stages of task preparation in the human brain , 2009, NeuroImage.
[45] T. Braver,et al. Attention, intention, and strategy in preparatory control , 2009, Neuropsychologia.
[46] Jeffrey N. Rouder,et al. Bayesian t tests for accepting and rejecting the null hypothesis , 2009, Psychonomic bulletin & review.
[47] J. Duncan. The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour , 2010, Trends in Cognitive Sciences.
[48] Hannah S. Locke,et al. Prefrontal cortex mediation of cognitive enhancement in rewarding motivational contexts , 2010, Proceedings of the National Academy of Sciences.
[49] P. Glimcher,et al. Testing the Reward Prediction Error Hypothesis with an Axiomatic Model , 2010, The Journal of Neuroscience.
[50] P. Fossati,et al. Different brain structures related to self- and external-agency attribution: a brief review and meta-analysis , 2011, Brain Structure and Function.
[51] Christian F. Doeller,et al. Anterior Hippocampus and Goal-Directed Spatial Decision Making , 2011, The Journal of Neuroscience.
[52] J. Duncan,et al. Adaptive Coding of Task-Relevant Information in Human Frontoparietal Cortex , 2011, The Journal of Neuroscience.
[53] S. Gilbert. Decoding the Content of Delayed Intentions , 2011, The Journal of Neuroscience.
[54] P. Dayan,et al. Model-based influences on humans’ choices and striatal prediction errors , 2011, Neuron.
[55] Dorit Wenke,et al. The shielding function of task sets and its relaxation during task switching. , 2011, Journal of experimental psychology. Learning, memory, and cognition.
[56] G. Dreisbach,et al. The role of affect and reward in the conflict-triggered adjustment of cognitive control , 2012, Front. Hum. Neurosci..
[57] James V. Haxby,et al. Multivariate pattern analysis of fMRI: The early beginnings , 2012, NeuroImage.
[58] Johan D. Carlin,et al. Choosing the Rules: Distinct and Overlapping Frontoparietal Representations of Task Rules for Perceptual Decisions , 2013, The Journal of Neuroscience.
[59] E. Murray,et al. The role of the anterior cingulate cortex in choices based on reward value and reward contingency. , 2013, Cerebral cortex.
[60] Jonathan D. Cohen,et al. Confounds in multivariate pattern analysis: Theory and rule representation case study , 2013, NeuroImage.
[61] N. Sigala,et al. Dynamic Coding for Cognitive Control in Prefrontal Cortex , 2013, Neuron.
[62] J. Haynes,et al. Predicting free choices for abstract intentions , 2013, Proceedings of the National Academy of Sciences.
[63] Franziska M. Korb,et al. Affective Modulation of Cognitive Control is Determined by Performance-Contingency and Mediated by Ventromedial Prefrontal and Cingulate Cortex , 2013, The Journal of Neuroscience.
[64] Nancy Kanwisher,et al. Broad domain generality in focal regions of frontal and parietal cortex , 2013, Proceedings of the National Academy of Sciences.
[65] D. Hassabis,et al. Foraging under Competition: The Neural Basis of Input-Matching in Humans , 2013, The Journal of Neuroscience.
[66] Jonathan D. Cohen,et al. The Computational and Neural Basis of Cognitive Control: Charted Territory and New Frontiers , 2014, Cogn. Sci..
[67] Yu Bai,et al. Dual learning processes underlying human decision-making in reversal learning tasks: functional significance and evidence from the model fit to human behavior , 2014, Front. Psychol..
[68] W. Fias,et al. Dissociating contributions of ACC and vmPFC in reward prediction, outcome, and choice , 2014, Neuropsychologia.
[69] Michael L. Waskom,et al. Frontoparietal Representations of Task Context Support the Flexible Control of Goal-Directed Cognition , 2014, The Journal of Neuroscience.
[70] John-Dylan Haynes,et al. Disentangling neural representations of value and salience in the human brain , 2014, Proceedings of the National Academy of Sciences.
[71] Polina Golland,et al. Coping with confounds in multivoxel pattern analysis: What should we do about reaction time differences? A comment on Todd, Nystrom & Cohen 2013 , 2014, NeuroImage.
[72] Kingson Man,et al. Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations , 2015, Front. Hum. Neurosci..
[73] J. Haynes. A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives , 2015, Neuron.
[74] Anina N. Rich,et al. Flexible Coding of Task Rules in Frontoparietal Cortex: An Adaptive System for Flexible Cognitive Control , 2015, Journal of Cognitive Neuroscience.
[75] Jörg Rieskamp,et al. An Introduction to Bayesian Hypothesis Testing for Management Research , 2015 .
[76] I. Momennejad,et al. The Role of the Parietal Cortex in the Representation of Task–Reward Associations , 2015, The Journal of Neuroscience.
[77] E. Wagenmakers,et al. An Introduction to Model-Based Cognitive Neuroscience , 2015, Springer New York.
[78] John-Dylan Haynes,et al. The Neural Representation of Voluntary Task-Set Selection in Dynamic Environments. , 2015, Cerebral cortex.
[79] K. Cheng,et al. Neural basis of decision making guided by emotional outcomes. , 2015, Journal of neurophysiology.
[80] Martin N. Hebart,et al. The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data , 2015, Front. Neuroinform..
[81] Jan De Houwer,et al. Potentiation of the startle reflex is in line with contingency reversal instructions rather than the conditioning history , 2016, Biological Psychology.
[82] Michael W. Cole,et al. Reward Motivation Enhances Task Coding in Frontoparietal Cortex. , 2016, Cerebral cortex.
[83] Wolfram Schultz,et al. Dopamine reward prediction-error signalling: a two-component response , 2016, Nature Reviews Neuroscience.
[84] Hans Knutsson,et al. Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates , 2016, Proceedings of the National Academy of Sciences.
[85] John-Dylan Haynes,et al. Similar coding of freely chosen and externally cued intentions in a fronto-parietal network , 2016, NeuroImage.
[86] Lasse S Loose,et al. Switch independent task representations in frontal and parietal cortex , 2017, bioRxiv.
[87] David Badre,et al. Just above chance: is it harder to decode information from human prefrontal cortex BOLD signals? , 2017, bioRxiv.
[88] Tobias Egner,et al. Dynamic Trial-by-Trial Recoding of Task-Set Representations in the Frontoparietal Cortex Mediates Behavioral Flexibility , 2017, The Journal of Neuroscience.
[89] David Badre,et al. Working Memory Load Strengthens Reward Prediction Errors , 2017, The Journal of Neuroscience.
[90] Jens Schwarzbach,et al. Decoding of auditory and tactile perceptual decisions in parietal cortex , 2017, NeuroImage.
[91] David Badre,et al. Just above Chance: Is It Harder to Decode Information from Prefrontal Cortex Hemodynamic Activity Patterns? , 2018, Journal of Cognitive Neuroscience.
[92] Etienne Koechlin,et al. The Neuro-Computational Architecture of Value-Based Selection in the Human Brain , 2017, Cerebral cortex.
[93] David Wisniewski. Context-Dependence and Context-Invariance in the Neural Coding of Intentional Action , 2018, Front. Psychol..
[94] A. R. Otto,et al. Cognitive capacity limitations and Need for Cognition differentially predict reward-induced cognitive effort expenditure , 2018, Cognition.