The DOI matches its Crossref record; 105 of the 106 references it cites were found in a registry or an index.
Neurons in the Frontal Lobe Encode the Value of Multiple Decision Variables
Open accessAbstract
A central question in behavioral science is how we select among choice alternatives to obtain consistently the most beneficial outcomes. Three variables are particularly important when making a decision: the potential payoff, the probability of success, and the cost in terms of time and effort. A key brain region in decision making is the frontal cortex as damage here impairs the ability to make optimal choices across a range of decision types. We simultaneously recorded the activity of multiple single neurons in the frontal cortex while subjects made choices involving the three aforementioned decision variables. This enabled us to contrast the relative contribution of the anterior cingulate cortex (ACC), the orbito-frontal cortex, and the lateral prefrontal cortex to the decision-making process. Neurons in all three areas encoded value relating to choices involving probability, payoff, or cost manipulations. However, the most significant signals were in the ACC, where neurons encoded multiplexed representations of the three different decision variables. This supports the notion that the ACC is an important component of the neural circuitry underlying optimal decision making.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Although PFo has long been thought to represent positive and negative valuations, it has only recently been appreciated that PFo neurons can represent value independent of stimulus identity (86–89).”
From Localization of Dysfunction in Major Depressive Disorder: Prefrontal Cortex and Amygdala (2011) · cites this paper as [89]
In the citing paper
“neurophysiological studies in awake, behaving monkeys have revealed that neurons in MFa signal the value of expected rewards (89).”
From Localization of Dysfunction in Major Depressive Disorder: Prefrontal Cortex and Amygdala (2011) · cites this paper as [89]
In the citing paper
“In addition, single-unit studies have shown that dACC/dmPFC neurons signal the net value of rewards associated with effort, and the necessity of this region in cost–benefit valuation has been demonstrated by lesion studies that report that inactivation of medial prefrontal cortex impairs an animal’s ability to overcome effort costs [15, 16, 25, 48, 55].”
From Neurocomputational mechanisms underlying subjective valuation of effort costs (2017) · cites this paper as [55]
In the citing paper
“In addition, single-unit studies have shown that dACC/dmPFC neurons signal the net value of rewards associated with effort, and the necessity of this region in cost–benefit valuation has been demonstrated by lesion studies that report that inactivation of medial prefrontal cortex impairs an animal’s ability to overcome effort costs [15, 16, 25, 48, 55].”
From Neurocomputational mechanisms underlying subjective valuation of effort costs (2017) · cites this paper as [55]
In the citing paper
“Neurons sensitive to reward information have been identified in the dlPFC [55, 57–59], and the activity of lateral prefrontal areas in humans correlates with predicted SVs that guide decision making [60].”
From Neurocomputational mechanisms underlying subjective valuation of effort costs (2017) · cites this paper as [55]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Prospect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524
Prospect theory: An analysis of decision under risk
Kahneman, D. J., & Tversky, A. (1988) · Cambridge University Press eBooks · doi:10.1017/cbo9780511609220.014 · Cited by 32,720
An Integrative Theory of Prefrontal Cortex Function
Miller, E. K., & Cohen, J. D. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.167 · Cited by 12,803
Conflict monitoring and cognitive control
Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001) · Psychological Review · doi:10.1037/0033-295x.108.3.624 · Cited by 7,351
Insensitivity to future consequences following damage to human prefrontal cortex
Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994) · Cognition · doi:10.1016/0010-0277(94)90018-3 · Cited by 6,128
Separate neural systems value immediate and delayed monetary rewards
McClure, S. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2004) · Science · doi:10.1126/science.1100907 · Cited by 3,089
Ongur, D. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.3.206 · Cited by 2,627
Learning the value of information in an uncertain world
Behrens, T. E. J., Woolrich, M. W., Walton, M. E., & Rushworth, M. F. S. (2007) · Nature Neuroscience · doi:10.1038/nn1954 · Cited by 2,053
DEFICITS IN STRATEGY APPLICATION FOLLOWING FRONTAL LOBE DAMAGE IN MAN
SHALLICE, T., & BURGESS, P. W. (1991) · Brain · doi:10.1093/brain/114.2.727 · Cited by 2,017
Neural correlates of decision variables in parietal cortex
Platt, M. L., & Glimcher, P. W. (1999) · Nature · doi:10.1038/22268 · Cited by 1,721
Research works printed but not linked: 1
- Stephens, 1986, Foraging theory.
Cited by
Sorted by citations
Items 201–300 of 451
Context-dependent decision-making in the primate hippocampal–prefrontal circuit
Elston, T. W., & Wallis, J. D. (2025) · Nature Neuroscience · doi:10.1038/s41593-024-01839-5 · Cited by 43
Self-citationWhere We Mentalize: Main Cortical Areas Involved in Mentalization
Monticelli, M., Zeppa, P., Mammi, M., Penner, F., Melcarne, A., Zenga, F., & Garbossa, D. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.712532 · Cited by 49
A neural substrate of sex-dependent modulation of motivation
Cox, J., Minerva, A. R., Fleming, W., Zimmerman, C. A., Hayes, C. L., Zorowitz, S., Bandi, A., Ornelas, S., McMannon, B., Parker, N. F., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-022-01229-9 · Cited by 38
Challenges of Interpreting Frontal Neurons during Value-Based Decision-Making
Wallis, J. D., & Rich, E. L. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00124 · Cited by 41
Self-citationThe anterior cingulate cortex: Monitoring the outcomes of others' decisions
Apps, M. A. J., Balsters, J. H., & Ramnani, N. (2011) · Social Neuroscience · doi:10.1080/17470919.2011.638799 · Cited by 41
Learned Value Shapes Responses to Objects in Frontal and Ventral Stream Networks in Macaque Monkeys
Kaskan, P. M., Costa, V. D., Eaton, H. P., Zemskova, J. A., Mitz, A. R., Leopold, D. A., Ungerleider, L. G., & Murray, E. A. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw113 · Cited by 38
Value dynamics affect choice preparation during decision-making
Balewski, Z. Z., Elston, T. W., Knudsen, E. B., & Wallis, J. D. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01407-3 · Cited by 42
Self-citationImpact of Size and Delay on Neural Activity in the Rat Limbic Corticostriatal System
Roesch, M. R., & Bryden, D. W. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00130 · Cited by 41
The drive to strive: goal generation based on current needs
Murray, E. A., & Rudebeck, P. H. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00112 · Cited by 38
Value and choice as separable and stable representations in orbitofrontal cortex
Kimmel, D. L., Elsayed, G. F., Cunningham, J. P., & Newsome, W. T. (2020) · Nature Communications · doi:10.1038/s41467-020-17058-y · Cited by 41
Valence processing in the PFC: Reconciling circuit-level and systems-level views
Coley, A. A., Padilla-Coreano, N., Patel, R. R., & Tye, K. M. (2021) · International review of neurobiology · doi:10.1016/bs.irn.2020.12.002 · Cited by 39
A stable, distributed code for cue value in mouse cortex during reward learning
Ottenheimer, D. J., Hjort, M. M., Bowen, A. J., Steinmetz, N. A., & Stuber, G. D. (2023) · eLife · doi:10.7554/elife.84604 · Cited by 41
Ostrander, S., Cazares, V. A., Kim, C. R., Cheung, S., Gonzalez, I., & Izquierdo, A. (2011) · Behavioral Neuroscience · doi:10.1037/a0023574 · Cited by 41
Dopamine D2-Receptor Blockade Enhances Decoding of Prefrontal Signals in Humans
Kahnt, T., Weber, S. C., Haker, H., Robbins, T. W., & Tobler, P. N. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4182-14.2015 · Cited by 35
Shahnazian, D., & Holroyd, C. B. (2017) · Psychonomic Bulletin & Review · doi:10.3758/s13423-017-1280-1 · Cited by 42
Consistent patterns of distractor effects during decision making
Chau, B. K. H., Law, C.-K., Lopez‐Persem, A., Klein-Flügge, M. C., & Rushworth, M. F. S. (2020) · eLife · doi:10.7554/elife.53850 · Cited by 36
Coding of Reward Probability and Risk by Single Neurons in Animals
Burke, C. J., & Tobler, P. N. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00121 · Cited by 42
Disordered Decision Making: A Cognitive Framework for Apathy and Impulsivity in Huntington’s Disease
Morris, L., O'Callaghan, C., & Le Heron, C. (2022) · Movement Disorders · doi:10.1002/mds.29013 · Cited by 36
Neuronal evidence for good-based economic decisions under variable action costs
Cai, X., & Padoa‐Schioppa, C. (2019) · Nature Communications · doi:10.1038/s41467-018-08209-3 · Cited by 37
Anterior cingulate cortex and adaptive control of brain and behavior
Brockett, A. T., & Roesch, M. R. (2020) · International review of neurobiology · doi:10.1016/bs.irn.2020.11.013 · Cited by 39
Impaired error-likelihood prediction in medial prefrontal cortex in schizophrenia
Krawitz, A., Braver, T. S., Barch, D. M., & Brown, J. W. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.09.027 · Cited by 35
Neural and neurochemical basis of reinforcement-guided decision making
Khani, A., & Rainer, G. (2016) · Journal of Neurophysiology · doi:10.1152/jn.01113.2015 · Cited by 38
Lopatina, N., Sadacca, B. F., McDannald, M. A., Styer, C. V., Peterson, J. F., Cheer, J. F., & Schoenbaum, G. M. (2017) · Behavioral Neuroscience · doi:10.1037/bne0000195 · Cited by 35
Purchase decision-making is modulated by vestibular stimulation
Preuss, N., Mast, F. W., & Hasler, G. (2014) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2014.00051 · Cited by 38
What Can Different Brains Do with Reward?
Gottfried, J. A. (2011) · CRC Press eBooks · doi:10.1201/b10776-10 · Cited by 33
Risk Prediction Error Coding in Orbitofrontal Neurons
O’Neill, M. J., & Schultz, W. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.4236-12.2013 · Cited by 35
Walton, M. E., Chau, B. K. H., & Kennerley, S. W. (2014) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2014.10.005 · Cited by 35
Self-citationHarris, A. M., & Lim, S.-L. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.4016-15.2016 · Cited by 36
Goal-Driven Cognition in the Brain: A Computational FrameworkPreprint
O’Reilly, R. C., Hazy, T. E., Mollick, J., Mackie, P., & Herd, S. A. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1404.7591 · Cited by 54
Bliss-Moreau, E., & Rudebeck, P. (2020) · Neuroscience and Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.06.024 · Cited by 27
Anterior Cingulate Cortex Ablation Disrupts Affective Vigor and Vigilance
Bliss‐Moreau, E., Santistevan, A. C., Bennett, J., Moadab, G., & Amaral, D. G. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0673-21.2021 · Cited by 35
Lynn, S. K., Wormwood, J. B., Barrett, L. F., & Quigley, K. S. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00952 · Cited by 39
Ichihara‐Takeda, S., & Funahashi, S. (2007) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.20047 · Cited by 35
Simmons, J. M., Minamimoto, T., Murray, E. A., & Richmond, B. J. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.1802-10.2010 · Cited by 30
Asymmetric coding of reward prediction errors in human insula and dorsomedial prefrontal cortex
Hoy, C. W., Quiroga‐Martinez, D. R., Sandoval, E., King‐Stephens, D., Laxer, K. D., Weber, P. B., Lin, J. J., & Knight, R. T. (2023) · Nature Communications · doi:10.1038/s41467-023-44248-1 · Cited by 39
Premkumar, P., Parbhakar, V. A., Fannon, D. G., Lythgoe, D. J., Williams, S., Kuipers, E., & Kumari, V. (2010) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2010.02.008 · Cited by 30
Moneta, N., Grossman, S., & Schuck, N. W. (2024) · Trends in Neurosciences · doi:10.1016/j.tins.2024.10.005 · Cited by 37
Electroencephalogram-Based Brain-Computer Interface for Internet of Robotic Things
Katona, J., Ujbányi, T., Sziládi, G., & Kővári, A. (2018) · Topics in intelligent engineering and informatics · doi:10.1007/978-3-319-95996-2_12 · Cited by 28
Believing and Beliefs—Neurophysiological Underpinnings
Seitz, R. J. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.880504 · Cited by 31
Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility
Frydman, C., Barberis, N., Camerer, C. F., Bossaerts, P. L., & Rangel, A. (2012) · National Bureau of Economic Research · doi:10.3386/w18562 · Cited by 29
Boroujeni, K. B., Sigona, M. K., Treuting, R. L., Manuel, T. J., Caskey, C. F., & Womelsdorf, T. (2022) · PLoS Biology · doi:10.1371/journal.pbio.3001785 · Cited by 29
Stress Degrades Prefrontal Cortex Neuronal Coding of Goal-Directed Behavior
Devilbiss, D. M., Spencer, R. C., & Berridge, C. W. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw140 · Cited by 30
Primate amygdala neurons evaluate the progress of self-defined economic choice sequences
Fabian Grabenhorst, B., Hernádi, I., & Schultz, W. (2016) · eLife · doi:10.7554/elife.18731 · Cited by 26
Cavanagh, S. E., Malalasekera, W. M. N., Miranda, B., Hunt, L. T., & Kennerley, S. W. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1906662116 · Cited by 28
Self-citationSignal dynamics of midbrain dopamine neurons during economic decision-making in monkeys
Yun, M., Kawai, T., Nejime, M., Yamada, H., & Matsumoto, M. (2020) · Science Advances · doi:10.1126/sciadv.aba4962 · Cited by 26
Value Representations in the Rodent Orbitofrontal Cortex Drive Learning, not ChoicePreprint
Miller, K. J., Botvinick, M., & Brody, C. D. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/245720 · Cited by 27
Agency matters! Social preferences in the three-person ultimatum game
Alexopoulos, J., Pfabigan, D. M., Göschl, F., Bauer, H., & Fischmeister, F. P. S. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00312 · Cited by 27
San‐Galli, A., Varazzani, C., Abitbol, R., Pessiglione, M., & Bouret, S. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw351 · Cited by 28
Beta traveling waves in monkey frontal and parietal areas encode recent reward history
Zabeh, E., Foley, N. C., Jacobs, J., & Gottlieb, J. P. (2023) · Nature Communications · doi:10.1038/s41467-023-41125-9 · Cited by 28
First-Pass Processing of Value Cues in the Ventral Visual Pathway
Sasikumar, D., Emeric, E. E., Stuphorn, V., & Connor, C. E. (2018) · Current Biology · doi:10.1016/j.cub.2018.01.051 · Cited by 25
Stress induced risk-aversion is reverted by D2/D3 agonist in the rat
Morgado, P. F., Marques, F., Ribeiro, B. M., Leite‐Almeida, H., Pêgo, J. M., Rodrigues, A. J., Dalla, C., Kokras, N., Sousa, N., & Cerqueira, J. (2015) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2015.07.003 · Cited by 25
Maoz, U., Rutishauser, U., Kim, S., Cai, X., Lee, D., & Koch, C. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00225 · Cited by 22
Mosher, C. P., Zimmerman, P. E., Fuglevand, A. J., & Gothard, K. M. (2016) · eNeuro · doi:10.1523/eneuro.0182-16.2016 · Cited by 23
Persistent Valence Representations by Ensembles of Anterior Cingulate Cortex Neurons
Caracheo, B. F., Grewal, J. J. S., & Seamans, J. K. (2018) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2018.00051 · Cited by 27
A cognitive map for value-guided choice in the ventromedial prefrontal cortex
Veselič, S., Müller, T., Gutierrez, E., Behrens, T. E. J., Hunt, L. T., Butler, J. L., & Kennerley, S. W. (2025) · Cell · doi:10.1016/j.cell.2025.03.038 · Cited by 26
Self-citationMarcos, E., & Genovesio, A. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2016.00075 · Cited by 23
Frontal circuit specialisations for decision making
Hunt, L. T. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15236 · Cited by 21
The orbitofrontal cortex represents advantageous choice in the Iowa gambling task
Zha, R., Li, P., Liu, Y., Li, N., Gao, M., Fan, Y., Aili, R., Liu, Y., Zhang, X., & Li, J. (2022) · Human Brain Mapping · doi:10.1002/hbm.25887 · Cited by 21
Solving the Credit Assignment Problem With the Prefrontal Cortex
Stolyarova, A. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00182 · Cited by 22
Toda, K., Sugase-Miyamoto, Y., Mizuhiki, T., Inaba, K., Richmond, B. J., & Shidara, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030190 · Cited by 21
EEG correlates of physical effort and reward processing during reinforcement learning
Palidis, D. J., & Gribble, P. L. (2020) · Journal of Neurophysiology · doi:10.1152/jn.00370.2020 · Cited by 24
Integrating Benefits and Costs in Decision Making
Wallis, J. D., & Rushworth, M. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-416008-8.00022-x · Cited by 19
Self-citationKahnt, T., & Tobler, P. N. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-805308-9.00009-9 · Cited by 22
Porter, B. S., Li, K., & Hillman, K. L. (2020) · eNeuro · doi:10.1523/eneuro.0243-20.2020 · Cited by 18
Jenison, R. L. (2014) · PLoS ONE · doi:10.1371/journal.pone.0109689 · Cited by 18
Klein-Flügge, M. C., Kennerley, S. W., Friston, K. J., & Bestmann, S. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/064105 · Cited by 19
Self-citationSilveira, M. M., Tremblay, M., & Winstanley, C. A. (2018) · Neuropharmacology · doi:10.1016/j.neuropharm.2018.04.025 · Cited by 21
What Can Different Brains Do with Reward?
Murray, E. A., Wise, S. P., & Rhodes, S. E. V. (2011) · Frontiers in neuroscience · doi:10.1201/b10776-6 · Cited by 19
Damage to the Ventromedial Prefrontal Cortex Impairs Learning from Observed Outcomes
Kumaran, D., Warren, D. E., & Tranel, D. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv080 · Cited by 20
Clarifying the role of an unavailable distractor in human multiattribute choice
Cao, Y., & Tsetsos, K. (2022) · eLife · doi:10.7554/elife.83316 · Cited by 16
Newton‐Fenner, A., Hewitt, D., Henderson, J. R., Roberts, H., Mari, T., Gu, Y., Gorelkina, O., Giesbrecht, T., Fallon, N. B., Roberts, C. A., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0286969 · Cited by 19
The economics of cognitive effort
Westbrook, J. A., & Braver, T. S. (2013) · Behavioral and Brain Sciences · doi:10.1017/s0140525x13001179 · Cited by 19
Abstract Value Encoding in Neural Populations But Not Single Neurons
Fine, J. M., Maisson, D. J.-N., Yoo, S. B. M., Cash-Padgett, T. V., Wang, M. Z., Zimmermann, J., & Hayden, B. Y. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.1954-22.2023 · Cited by 19
Fast and slow contributions to decision-making in corticostriatal circuits
Balewski, Z. Z., Knudsen, E. B., & Wallis, J. D. (2022) · Neuron · doi:10.1016/j.neuron.2022.04.005 · Cited by 18
Self-citationSachuriga, Nishimaru, H., Takamura, Y., Matsumoto, J., de Araújo, M. F. P., Ono, T., & Nishijo, H. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.655110 · Cited by 18
Pelletier, G., Aridan, N., Fellows, L. K., & Schönberg, T. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0241-21.2021 · Cited by 22
Cai, X., & Padoa‐Schioppa, C. (2021) · eLife · doi:10.7554/elife.71695 · Cited by 19
Behavioral read-out from population value signals in primate orbitofrontal cortex
McGinty, V. B., & Lupkin, S. M. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01473-7 · Cited by 25
Predictive coding of the statistical parameters of uncertain rewards by orbitofrontal neurons
O’Neill, M. J., & Schultz, W. (2018) · Behavioural Brain Research · doi:10.1016/j.bbr.2018.04.041 · Cited by 16
van de Vijver, I., van Schie, H. T., Veling, H., van Dooren, R., & Holland, R. W. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.08.023 · Cited by 17
Fabian Grabenhorst, B., Tsutsui, K., Kobayashi, S., & Schultz, W. (2019) · eLife · doi:10.7554/elife.44838 · Cited by 17
Value-based decisions involve sequential sampling from memoryPreprint
Bakkour, A., Zylberberg, A., Shadlen, M. N., & Shohamy, D. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/269290 · Cited by 16
Inhibitory control of frontal metastability sets the temporal signature of cognition
Fontanier, V., Sarazin, M., Stoll, F. M., Delord, B., & Procyk, E. (2022) · eLife · doi:10.7554/elife.63795 · Cited by 19
The Computational and Neural Substrates of Ambiguity Avoidance in Anxiety
Lawrance, E., Gagne, C., O’Reilly, J. X., Bijsterbosch, J. D., & Bishop, S. J. (2022) · Computational Psychiatry · doi:10.5334/cpsy.67 · Cited by 17
The Cost of Imagined Actions in a Reward-Valuation Task
Sellitto, M., Terenzi, D., Starita, F., di Pellegrino, G., & Battaglia, S. (2022) · Brain Sciences · doi:10.3390/brainsci12050582 · Cited by 13
Valence processing differs across stimulus modalities
Dalenberg, J. R., Weitkamp, L., Renken, R. J., & Horst, G. J. T. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.059 · Cited by 13
Visualization and bibliometric analysis on the research of financial well-being
Sáng, N. M. (2022) · International Journal of ADVANCED AND APPLIED SCIENCES · doi:10.21833/ijaas.2022.03.002 · Cited by 18
Unsigned value prediction-error modulates the motor system in absence of choice
Vassena, E., Cobbaert, S., Andres, M., Fias, W., & Verguts, T. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.081 · Cited by 14
The Neurobiology of Preferences
Symmonds, M., & Dolan, R. J. (2011) · Elsevier eBooks · doi:10.1016/b978-0-12-381431-9.00001-2 · Cited by 13
Chien, J. M., Wallis, J. D., & Rich, E. L. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0292-23.2023 · Cited by 19
Self-citationStoll, F. M., & Rudebeck, P. H. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.0464-24.2024 · Cited by 14
Anhedonia and Reward System: Psychobiology, Evaluation, and Clinical Features
Martinotti, G., Hatzigiakoumis, D. S., Vita, O. D., Clerici, M., Petruccelli, F., Giannantonio, M. D., & Janiri, L. (2012) · International Journal of Clinical Medicine · doi:10.4236/ijcm.2012.37125 · Cited by 13
Piantadosi, S. T., & Hayden, B. Y. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00105 · Cited by 11
Lindsay, A. J., Caracheo, B. F., Grewal, J. J. S., Leibovitz, D., & Seamans, J. K. (2018) · eNeuro · doi:10.1523/eneuro.0023-18.2018 · Cited by 14
Hong, D., Huang, W., Ji, A.-A., Yang, S.-S., Xu, H., Sun, K.-Y., Cao, A., Gao, W., Zhou, N., & Yu, P. (2018) · Metabolic Brain Disease · doi:10.1007/s11011-018-0360-x · Cited by 18
Pritchard, T. C. (2012) · Elsevier eBooks · doi:10.1016/b978-0-12-374236-0.10033-1 · Cited by 12
Amphetamine reduces reward encoding and stabilizes neural dynamics in rat anterior cingulate cortex
Hashemnia, S., Euston, D. R., & Gruber, A. J. (2020) · eLife · doi:10.7554/elife.56755 · Cited by 14
Macaque monkeys exhibit behavioral signs of metamemory in an oculomotor working memory task
Tanaka, A., & Funahashi, S. (2012) · Behavioural Brain Research · doi:10.1016/j.bbr.2012.05.013 · Cited by 13
A view-based decision mechanism for rewards in the primate amygdala
Fabian Grabenhorst, B., Ponce‐Alvarez, A., Battaglia‐Mayer, A., Deco, G., & Schultz, W. (2023) · Neuron · doi:10.1016/j.neuron.2023.08.024 · Cited by 11
Tan, J., Zhang, X., Wu, S., Song, Z., Chen, S., Huang, Y., & Wang, Y. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad017d · Cited by 13
Metadata
- Authors
- Kennerley, S. W., Dahmubed, A. F., Lara, A. H., & Wallis, J. D.
- Affiliations
- University of California, Berkeley (US)
- ORCID
- Kennerley, Steven W.
- Venue
- Journal of Cognitive Neuroscience
- Publisher
- MIT Press - Journals
- Published
- 2009-06-01
- Volume
- 21
- Issue
- 6
- Pages
- 1162-1178
- ISSN
- 0898-929X (ISSN-L)
- 1530-8898
- PMC
- PMC2715848
- OpenAlex
- W2048142524
- Cited by
- 453
- References
- 106
- Citations by year
- 2026: 10 · 2025: 20 · 2024: 25 · 2023: 27 · 2022: 26 · 2021: 26 · 2020: 24 · 2019: 20 · 2018: 28 · 2017: 26 · 2016: 28 · 2015: 21 · 2014: 24 · 2013: 28 · 2012: 22
- FWCI
- 16.71
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Cognitive Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Institutes of Health (5f32mh081521-02)
- National Institute of Mental Health (F32MH-081521)
- National Institute on Drug Abuse (R01-DA19028, R01DA019028)
- National Institute of Neurological Disorders and Stroke (P01NS040813)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- decision-making, frontal cortex, anterior cingulate cortex, orbitofrontal cortex, lateral prefrontal cortex, single-unit recording, payoffs, success probability, cost, value encoding, optimal choice
- MeSH terms
- Action Potentials, Analysis of Variance, Animals, Brain Mapping, Decision Making, Eye Movements, Frontal Lobe, Functional Laterality, Macaca mulatta, Male, Neural Pathways, Neurons, Neuropsychological Tests, Photic Stimulation, Probability, Reaction Time, Reward, Time Factors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review