Temporal Difference Models and Reward-Related Learning in the Human Brain

A neural substrate of prediction and reward

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A theory of Pavlovian conditioning : Variations in the effectiveness of reinforcement and nonreinforcement

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Learning to predict by the methods of temporal differences

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Predictive reward signal of dopamine neurons

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Spatial registration and normalization of images

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A model for Pavlovian learning: Variations in the effectiveness of conditioned but not of unconditioned stimuli.

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Anticipation of Increasing Monetary Reward Selectively Recruits Nucleus Accumbens

Knutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001) · The Journal of Neuroscience · doi:10.1523/jneurosci.21-16-j0002.2001 · Cited by 2,244

Functional imaging of neural responses to expectancy and experience of monetary gains and losses

Breiter, H. C., Aharon, I., Kahneman, D., Dale, A., & Shizgal, P. (2001) · Neuron · doi:10.1016/s0896-6273(01)00303-8 · Cited by 1,404

Dissociation of reward anticipation and outcome with event-related fMRI

Knutson, B., Fong, G. W., Adams, C. M., Varner, J. L., & Hommer, D. (2001) · Neuroreport · doi:10.1097/00001756-200112040-00016 · Cited by 1,300

Tracking the Hemodynamic Responses to Reward and Punishment in the Striatum

Delgado, M. R., Nystrom, L. E., Fissell, C., Noll, D. C., & Fiez, J. A. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.84.6.3072 · Cited by 1,116

Elevated arousal levels enhance contrast perception

Kim, D., Lokey, S., & Ling, S. (2017) · Journal of Vision · doi:10.1167/17.2.14 · Cited by 27

Neural Mechanisms for Adaptive Learned Avoidance of Mental Effort

Nagase, A. M., Onoda, K., Foo, J. C., Haji, T., Akaishi, R., Yamaguchi, S., Sakai, K., & Morita, K. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1995-17.2018 · Cited by 27

Insula and putamen centered functional connectivity networks reflect healthy agers' subjective experience of cognitive fatigue in multiple tasks

Anderson, A. J., Ren, P., Baran, T. M., Zhang, Z., & Lin, F. V. (2019) · Cortex · doi:10.1016/j.cortex.2019.07.019 · Cited by 27

Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms

Flannery, J. S., Riedel, M. C., Bottenhorn, K. L., Poudel, R., Salo, T., Hill-Bowen, L. D., Laird, A. R., & Sutherland, M. T. (2019) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-019-00763-7 · Cited by 26

Action selection performance of a reconfigurable basal ganglia inspired model with Hebbian–Bayesian Go-NoGo connectivity

Berthet, P., Kotaleski, J. H., & Lansner, A. (2012) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2012.00065 · Cited by 26

Brain Maturation and Risky Behavior: The Promise and the Challenges of Neuroimaging-Based Accounts

Bjork, J. M., Lynne‐Landsman, S. D., Sirocco, K. Y., & Boyce, C. A. (2012) · Child Development Perspectives · doi:10.1111/cdep.12001 · Cited by 27

The involvement of model-based but not model-free learning signals during observational reward learning in the absence of choice

Dunne, S., D’Souza, A., & O’Doherty, J. P. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00046.2016 · Cited by 25

Striatal hub of dynamic and stabilized prediction coding in forebrain networks for olfactory reinforcement learning

Winkelmeier, L., Filosa, C., Hartig, R., Scheller, M. F., Sack, M., Reinwald, J., Becker, R., Wolf, D., Gerchen, M. F., Sartorius, A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30978-1 · Cited by 24

Three studies on the neuroeconomics of decision-making when payoffs are real and negative

Berns, G. S., Capra, C. M., Moore, S. E., & NOUSSAIR, C. N. (2008) · Advances in health economics and health services research · doi:10.1016/s0731-2199(08)20001-4 · Cited by 25

The Value of Being Wrong: Intermittent Feedback Delivery Alters the Striatal Response to Negative Feedback

Lempert, K. M., & Tricomi, E. M. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00892 · Cited by 25

Normal aging and Parkinson's disease are associated with the functional decline of distinct frontal-striatal circuits

Gruszka, A., Hampshire, A., Barker, R. A., & Owen, A. M. (2017) · Cortex · doi:10.1016/j.cortex.2017.05.020 · Cited by 25

Trauma-associated anterior cingulate connectivity during reward learning predicts affective and anxiety states in young adults

Eckstrand, K., Hanford, L. C., Bertocci, M. A., Chase, H. W., Greenberg, T., Lockovich, J., Stiffler, R., Aslam, H. A., Graur, S., Bebko, G. M., et al. (2018) · Psychological Medicine · doi:10.1017/s0033291718002520 · Cited by 25

Orbitofrontal Cortex and Outcome Expectancies: Optimizing Behavior and Sensory Perception

Gottfried, J. A. (2011) · CRC Press eBooks · doi:10.1201/b10776-23 · Cited by 25

Neural circuits associated with positive and negative self-appraisal

Brühl, A. B., Rufer, M., Kaffenberger, T., Baur, V., & Herwig, U. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.01.053 · Cited by 24

The roots of polarization in the individual reward system

Lefebvre, G., Deroy, O. D., & Bahrami, B. (2024) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2023.2011 · Cited by 26

Many hats: intratrial and reward level-dependent BOLD activity in the striatum and premotor cortex

Peterson, E. J., & Seger, C. A. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00164.2012 · Cited by 24

Inter-individual discount factor differences in reward prediction are topographically associated with caudate activation

Onoda, K., Okamoto, Y., Kunisato, Y., Aoyama, S., Shishida, K., Okada, G., Tanaka, S., Schweighofer, N., Yamaguchi, S., Doya, K., et al. (2011) · Experimental Brain Research · doi:10.1007/s00221-011-2771-3 · Cited by 25

Valenced action/inhibition learning in humans is modulated by a genetic variant linked to dopamine D2 receptor expression

Richter, A., Guitart‐Masip, M., Barman, A., Libeau, C., Behnisch, G., Czerney, S., Schanze, D., Assmann, A., Klein, M., Düzel, E., et al. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00140 · Cited by 25

Conceptual representations in goal-directed decision making

Shea, N. J., Krug, K., & Tobler, P. N. (2008) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/cabn.8.4.418 · Cited by 24

Delineating the social valuation network in adolescents

Kumar, P., Pisoni, A., Bondy, E., Kremens, R., Singleton, P., Pizzagalli, D. A., & Auerbach, R. P. (2019) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsz086 · Cited by 23

Predictive value and reward in implicit classification learning

Lam, J. M., Wächter, T., Globas, C., Karnath, H., & Luft, A. R. (2012) · Human Brain Mapping · doi:10.1002/hbm.21431 · Cited by 24

Reinforcement learning and higher level cognition: Introduction to special issue

Daw, N. D., & Frank, M. J. (2009) · Cognition · doi:10.1016/j.cognition.2009.09.005 · Cited by 24

Surprise beyond prediction error

Chumbley, J. R., Burke, C. J., Stephan, K. E., Friston, K. J., Tobler, P. N., & Fehr, E. (2014) · Human Brain Mapping · doi:10.1002/hbm.22513 · Cited by 23

Reward Responsiveness, Learning, and Valuation Implicated in Problematic Pornography Use — a Research Domain Criteria Perspective

Klein, S., Krikova, K., Antons, S., Brand, M., Klucken, T., & Stark, R. M. (2022) · Current Addiction Reports · doi:10.1007/s40429-022-00423-w · Cited by 25

Artificial Motivation for Cognitive Software Agents

McCall, R. J., Franklin, S., Faghihi, U., Snaider, J., & Kugele, S. (2020) · Journal of Artificial General Intelligence · doi:10.2478/jagi-2020-0002 · Cited by 23

Instrumental and Pavlovian Mechanisms in Alcohol Use Disorder

Doñamayor, N., Ebrahimi, C., Garbusow, M., Wedemeyer, F., Schlagenhauf, F., & Heinz, A. (2020) · Current Addiction Reports · doi:10.1007/s40429-020-00333-9 · Cited by 24

Decoding the brain state-dependent relationship between pupil dynamics and resting state fMRI signal fluctuation

Sobczak, F., Pais‐Roldán, P., Takahashi, K., & Yu, X. (2021) · eLife · doi:10.7554/elife.68980 · Cited by 23

Analysis of individual differences in neurofeedback training illuminates successful self-regulation of the dopaminergic midbrain

Hellrung, L., Kirschner, M., Sulzer, J. S., Sladky, R., Scharnowski, F., Herdener, M., & Tobler, P. N. (2022) · Communications Biology · doi:10.1038/s42003-022-03756-4 · Cited by 23

Internal-Time Temporal Difference Model for Neural Value-Based Decision Making

Nakahara, H., & Kaveri, S. R. (2010) · Neural Computation · doi:10.1162/neco_a_00049 · Cited by 25

Callous-Unemotional Traits and Developmental Pathways to the Disruptive Behavior Disorders

Frick, P. J., Blair, J., & Castellanos, F. X. (2013) · Springer eBooks · doi:10.1007/978-1-4614-7557-6_4 · Cited by 26

Human substantia nigra and ventral tegmental area involvement in computing social error signals during the ultimatum game

Hétu, S., Luo, Y., D’Ardenne, K., Lohrenz, T. M., & Montague, P. R. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx097 · Cited by 23

The Development of Goal-Directed Decision-Making

Raab, H. A., & Hartley, C. A. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-812098-9.00013-9 · Cited by 25

Striatal functional connectivity in chronic ketamine users: a pilot study

Hung, C., Zhang, S., Chen, C., Duann, J., Lin, C., Lee, T. S., & Li, C. R. (2019) · The American Journal of Drug and Alcohol Abuse · doi:10.1080/00952990.2019.1624764 · Cited by 24

fMRI of the brain’s response to stimuli experimentally paired with alcohol intoxication

Kareken, D. A., Grahame, N. J., Džemidžić, M., Walker, M. J., Lehigh, C. A., & O’Connor, S. (2011) · Psychopharmacology · doi:10.1007/s00213-011-2526-7 · Cited by 23

Imaging the changing role of feedback during learning in decision-making

Sailer, U., Robinson, S., Fischmeister, F. P. S., Moser, E., Kryspin‐Exner, I., & Bauer, H. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.012 · Cited by 24

Neuroeconomics and Neurofinance

Peterson, R. L. (2010) · Wiley eBooks · doi:10.1002/9781118258415.ch5 · Cited by 27

Organoid intelligence for developmental neurotoxicity testing

Din, D. A. E., Shin, J., Lysinger, A., Roos, M. J., Johnson, E. C., Shafer, T. J., Härtung, T., & Smirnova, L. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1480845 · Cited by 25

The curious case of dopaminergic prediction errors and learning associative information beyond value

Kahnt, T., & Schoenbaum, G. M. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-024-00898-8 · Cited by 22

Multi-Agent Deep Q Network to Enhance the Reinforcement Learning for Delayed Reward System

Kim, K. (2022) · Applied Sciences · doi:10.3390/app12073520 · Cited by 22

Dissociation of BOLD responses to reward prediction errors and reward receipt by a model comparison

Rohe, T., Weber, B., & Fließbach, K. (2012) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2012.08125.x · Cited by 22

When is a loss a loss? Excitatory and inhibitory processes in loss-related decision-making

Seymour, B., Maruyama, M., & Martino, B. D. (2015) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2015.09.003 · Cited by 24

The role of moral utility in decision making: An interdisciplinary framework

Tobler, P. N., Kalis, A., & Kalenscher, T. (2008) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/cabn.8.4.390 · Cited by 27

The effects of energy balance, obesity-proneness and sex on the neuronal response to sweet taste

Cornier, M., Shott, M. E., Thomas, E. A., Bechtell, J. L., Bessesen, D. H., Tregellas, J. R., & Frank, G. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.10.024 · Cited by 22

A hierarchical model for integrating unsupervised generative embedding and empirical Bayes

Raman, S., Deserno, L., Schlagenhauf, F., & Stephan, K. E. (2016) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2016.04.022 · Cited by 21

The network architecture of value learning

Mattar, M. G., Thompson‐Schill, S. L., & Bassett, D. S. (2017) · Network Neuroscience · doi:10.1162/netn_a_00021 · Cited by 21

Individual differences in eye blink rate predict both transient and tonic pupil responses during reversal learning

Slooten, J. C. V., Jahfari, S., Knapen, T. H. J., & Theeuwes, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0185665 · Cited by 23

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Das, R., Gale, G., Hennessy, V. E., & Kamboj, S. K. (2018) · Journal of Visualized Experiments · doi:10.3791/56097 · Cited by 24

Neural correlates of subjective CS/UCS association in appetitive conditioning

León, I. T., Kruse, O., Stalder, T., Stark, R. M., & Klucken, T. (2018) · Human Brain Mapping · doi:10.1002/hbm.23940 · Cited by 23

Accounting for Dynamic Fluctuations across Time when Examining fMRI Test-Retest Reliability: Analysis of a Reward Paradigm in the EMBARC Study

Chase, H. W., Fournier, J. C. J., Greenberg, T., Almeida, J., Stiffler, R. S., Zevallos, C. R., Aslam, H. A., Cooper, C. M., Deckersbach, T., Weyandt, S., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0126326 · Cited by 22

Dopaminergic challenge dissociates learning from primary versus secondary sources of information

Rybicki, A. J., Sowden, S., Schuster, B. A., & Cook, J. L. (2022) · eLife · doi:10.7554/elife.74893 · Cited by 21

Reward Processing

Smith, D. V., & Delgado, M. R. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00255-4 · Cited by 25

Advances in the diagnosis of anorexia nervosa and bulimia nervosa using brain imaging

Frank, G. (2012) · Expert Opinion on Medical Diagnostics · doi:10.1517/17530059.2012.673583 · Cited by 24

Computational Models in Social Neuroscience

Cheong, J. H., Jolly, E., Sul, S., & Chang, L. J. (2017) · Wiley eBooks · doi:10.1002/9781119159193.ch17 · Cited by 20

Disrupted reinforcement learning during post-error slowing in ADHD

Chevrier, A., Bhaijiwala, M., Lipszyc, J., Cheyne, D., Graham, S., & Schachar, R. (2019) · PLOS ONE · doi:10.1371/journal.pone.0206780 · Cited by 21

Bringing in the negative reinforcements: the avoidance feedback-related negativity

Crowley, M. J., Wu, J., Bailey, C. A., & Mayes, L. C. (2009) · Neuroreport · doi:10.1097/wnr.0b013e32832ff2f5 · Cited by 21

Feedback-related negativity reflects omission of monetary gains: Evidence from ERP gambling study

Yaple, Z. A., Шестакова, А. Н., & Klucharev, V. A. (2018) · Neuroscience Letters · doi:10.1016/j.neulet.2018.09.007 · Cited by 21

Fast neural learning in dogs: A multimodal sensory fMRI study

Prichard, A., Chhibber, R., Athanassiades, K., Spivak, M., & Berns, G. S. (2018) · Scientific Reports · doi:10.1038/s41598-018-32990-2 · Cited by 25

Strategic cognitive sequencing: a computational cognitive neuroscience approach

Herd, S. A., Krueger, K. A., Kriete, T. E., Huang, T.-R., Hazy, T. E., & O'Reilly, R. C. (2013) · Computational Intelligence and Neuroscience · doi:10.1155/2013/149329 · Cited by 20

The neural basis of the insight memory advantage

Becker, M., & Cabeza, R. E. L. (2025) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2025.01.001 · Cited by 26

The Role of the Basal Ganglia in Discovering Novel Actions

Redgrave, P., Gurney, K., Stafford, T., Thirkettle, M., & Lewis, J. (2012) · Springer eBooks · doi:10.1007/978-3-642-32375-1_6 · Cited by 22

Oscillatory signatures of reward prediction errors in declarative learning

Ergo, K., Loof, E. D., Janssens, C., & Verguts, T. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.083 · Cited by 21

Reward salience and risk aversion underlie differential ACC activity in substance dependence

Alexander, W. H., Fukunaga, R., Finn, P., & Brown, J. W. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.02.025 · Cited by 22

Differential representation of feedback and decision in adolescents and adults

Javadi, A., Schmidt, D. H. K., & Smolka, M. N. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2014.01.021 · Cited by 18

Congruence of Inherent and Acquired Values Facilitates Reward-Based Decision-Making

Chien, S., Wiehler, A., Spezio, M., & Gläscher, J. P. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.3084-15.2016 · Cited by 19

Lucky Rhythms in Orbitofrontal Cortex Bias Gambling Decisions in Humans

Sacré, P., Kerr, M. S. D., Kahn, K., Gonzalez-Martinez, J. A., Bulacio, J. C., Park, H.-J., Johnson, M. A., Thompson, S., Jones, J., Chib, V. S., et al. (2016) · Scientific Reports · doi:10.1038/srep36206 · Cited by 19

Gender Differences and Unfairness Processing during Economic and Moral Decision-Making: A fNIRS Study

Vanutelli, M. E., Meroni, F., Fronda, G., Balconi, M., & Lucchiari, C. (2020) · Brain Sciences · doi:10.3390/brainsci10090647 · Cited by 22

Differential neural mechanisms for early and late prediction error detection

Malekshahi, R., Seth, A. K., Papanikolaou, A., Mathews, Z., Birbaumer, N., Verschure, P. F. M. J., & Carìa, A. (2016) · Scientific Reports · doi:10.1038/srep24350 · Cited by 26

Dual-System Learning Models and Drugs of Abuse

Simon, D. A., & Daw, N. D. (2011) · Springer eBooks · doi:10.1007/978-1-4614-0751-5_5 · Cited by 22

Decision-making in brains and robots — the case for an interdisciplinary approach

Lee, S. W., & Seymour, B. (2019) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.12.012 · Cited by 19

Stress reduces both model-based and model-free neural computations during flexible learning

Cremer, A., Kalbe, F., Gläscher, J. P., & Schwabe, L. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117747 · Cited by 20

Cross‐species translational paradigms for assessing positive valence system as defined by the RDoC matrix

Dexter, T. D., Roberts, B. Z., Ayoub, S. M., Noback, M. N., Barnes, S. A., & Young, J. W. (2024) · Journal of Neurochemistry · doi:10.1111/jnc.16243 · Cited by 20

Dissociable functions of reward inference in the lateral prefrontal cortex and the striatum

Tanaka, S., Pan, X., Oguchi, M., Taylor, J. E., & Sakagami, M. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00995 · Cited by 19

Inter-temporal choice and self-control: saving and borrowing

Webley, P., & Nyhus, E. K. (2008) · Cambridge University Press eBooks · doi:10.1017/cbo9780511490118.005 · Cited by 20

Structure-function relationships in the context of reinforcement-related learning: a combined diffusion tensor imaging–functional magnetic resonance imaging study

Koch, K., Wagner, G., Dahnke, R., Schachtzabel, C., Güllmar, D., Reichenbach, J. R., & Schlösser, R. G. M. (2010) · Neuroscience · doi:10.1016/j.neuroscience.2010.03.026 · Cited by 19

Neural insensitivity to upticks in value is associated with the disposition effect

Brooks, A. M., Capra, C. M., & Berns, G. S. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.081 · Cited by 20

Inter-trial coherence of medial frontal theta oscillations linked to differential feedback processing in youth and young adults with autism

van Noordt, S. J. R., Wu, J., Venkataraman, A., Larson, M. J., South, M., & Crowley, M. J. (2017) · Research in Autism · doi:10.1016/j.rasd.2017.01.011 · Cited by 21

Individual differences in dopamine D2 receptor availability correlate with reward valuation

Dang, L. C., Samanez-Larkin, G. R., Castrellon, J. J., Perkins, S. F., Cowan, R. L., & Zald, D. H. (2018) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-018-0601-9 · Cited by 18

Aberrant striatal tracking of reward magnitude in youth with current or past-year depression.

Insel, C., Glenn, C. R., Nock, M. K., & Somerville, L. H. (2018) · Journal of Abnormal Psychology · doi:10.1037/abn0000389 · Cited by 19

Threat rapidly disrupts reward reversal learning

Paret, C., & Bublatzky, F. (2020) · Behaviour Research and Therapy · doi:10.1016/j.brat.2020.103636 · Cited by 19

Revisiting the importance of model fitting for model-based fMRI: It does matter in computational psychiatry

Katahira, K., & Toyama, A. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008738 · Cited by 18

A discriminative account of the learning, representation and processing of inflection systems

Ramscar, M. (2021) · Language Cognition and Neuroscience · doi:10.1080/23273798.2021.2014062 · Cited by 19

Dyspnea relief: More than just the perception of a decrease in dyspnea

Peiffer, C. (2009) · Respiratory Physiology & Neurobiology · doi:10.1016/j.resp.2009.04.001 · Cited by 21

Brain Predictors of Individual Differences in Placebo Responding

Koban, L., Ruzic, L. L., & Wager, T. D. (2013) · Elsevier eBooks · doi:10.1016/b978-0-12-397928-5.00010-6 · Cited by 19

Toward a Mechanistic Understanding of Human Decision Making

O’Doherty, J. P., & Bossaerts, P. L. (2008) · Current Directions in Psychological Science · doi:10.1111/j.1467-8721.2008.00560.x · Cited by 21

Using ethological principles to study psychosocial influences on coronary atherosclerosis in monkeys.

Kaplan, J. R., & Manuck, S. B. (1997) · PubMed · Cited by 19

Reward System Abnormalities in Anorexia Nervosa

STEINGLASS, J. E., & Foerde, K. (2018) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2018.1924 · Cited by 19

Boredom and Flow: A Counterfactual Theory of Attention-Directing Motivational StatesPreprint

Chater, N., Loewenstein, G. F., & Wojtowicz, Z. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3339123 · Cited by 21

The Neural Correlates of Cued Reward Omission

Mollick, J., Chang, L. J., Krishnan, A., Hazy, T. E., Krueger, K. A., Frank, G., Wager, T. D., & O’Reilly, R. C. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.615313 · Cited by 19

Computational reinforcement learning, reward (and punishment), and dopamine in psychiatric disorders

Liebenow, B., Jones, R., DiMarco, E. K., Trattner, J. D., Humphries, J. B., Sands, L. P., Spry, K. P., Johnson, C. K., Farkas, E. B., Jiang, A., et al. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.886297 · Cited by 23

Cerebellar and basal ganglia structural connections in humans: Effect of aging and relation with memory and learning

Radhakrishnan, V., Galléa, C., Valabrègue, R., Krishnan, S., Kesavadas, C., Thomas, B., James, P., Menon, R. N., & Kishore, A. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1019239 · Cited by 18

Economic and social values in the brain: evidence from lesions to the human ventromedial prefrontal cortex

Messimeris, D., Lévy, R., & Bouc, R. L. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1198262 · Cited by 19

Differential contributions of the globus pallidus and ventral thalamus to stimulus–response learning in humans

Schroll, H., Horn, A., Gröschel, C., Brücke, C., Lütjens, G., Schneider, G., Krauss, J. K., Kühn, A. A., & Hamker, F. H. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.061 · Cited by 20

Amino acid challenge and depletion techniques in human functional neuroimaging studies: an overview

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The Effect of Reduced Learning Ability on Avoidance in Psychopathy: A Computational Approach

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