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  1. Impaired rapid error monitoring but intact error signaling following rostral anterior cingulate cortex lesions in humans.Martin E. Maier, Francesco Di Gregorio, Teresa Muricchio & Giuseppe Di Pellegrino - 2015 - Frontiers in Human Neuroscience 9.
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  • The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity.Clay B. Holroyd & Michael G. H. Coles - 2002 - Psychological Review 109 (4):679-709.
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  • Model-Based Influences on Humans' Choices and Striatal Prediction Errors.Nathaniel D. Daw, Samuel J. Gershman, Ben Seymour, Peter Dayan & Raymond J. Dolan - 2011 - Neuron 69 (6):1204-1215.
    The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could (...)
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  • Inhibition and the right inferior frontal cortex.Adam R. Aron, Trevor W. Robbins & Russell A. Poldrack - 2004 - Trends in Cognitive Sciences 8 (4):170-177.
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  • Computational psychiatry.P. Read Montague, Raymond J. Dolan, Karl J. Friston & Peter Dayan - 2012 - Trends in Cognitive Sciences 16 (1):72-80.
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  • Does Feedback-Related Brain Response during Reinforcement Learning Predict Socio-motivational (In-)dependence in Adolescence?Diana Raufelder, Rebecca Boehme, Lydia Romund, Sabrina Golde, Robert C. Lorenz, Tobias Gleich & Anne Beck - 2016 - Frontiers in Psychology 7:190427.
    This multi-methodological study applied functional magnetic resonance imaging to investigate neural activation in a group of adolescent students ( N = 88) during a probabilistic reinforcement learning task. We related patterns of emerging brain activity and individual learning rates to socio-motivational (in-)dependence manifested in four different motivation types (MTs): (1) peer-dependent MT, (2) teacher-dependent MT, (3) peer-and-teacher-dependent MT, (4) peer-and-teacher-independent MT. A multinomial regression analysis revealed that the individual learning rate predicts students’ membership to the independent MT, or the peer-and-teacher-dependent (...)
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