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 301–400 of 451
Feng, Y.-Y., Bromberg-Martin, E. S., & Monosov, I. E. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114341 · Cited by 18
Common Mechanisms of Learning in Motor and Cognitive Systems
Constantinidis, C., Ahmed, A. A., Wallis, J. D., & Batista, A. P. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.1505-23.2023 · Cited by 11
Self-citationEvaluating Visual Cues Modulates Their Representation in Mouse Visual and Cingulate Cortex
Wal, A., Klein, F. J., Born, G., Busse, L., & Katzner, S. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1828-20.2021 · Cited by 12
Neuronal Encoding in Prefrontal Cortex during Hierarchical Reinforcement Learning
Chiang, F.-K., & Wallis, J. D. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01272 · Cited by 11
Self-citationCui, M., Peng, C., Huang, M. H., & Chen, Y. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab466 · Cited by 12
The prefrontal cortex and hybrid learning during iterative competitive games
Abe, H., Seo, H., & Lee, D. (2011) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2011.06223.x · Cited by 11
Categorical representations of decision-variables in orbitofrontal cortexPreprint
Hirokawa, J., Vaughan, A., & Kepecs, Á. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/135707 · Cited by 11
Intersection of effort and risk: ethological and neurobiological perspectives
Miller, M. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00208 · Cited by 11
Comrie, A. E., Monroe, E. J., Kahn, A. E., Denovellis, E. L., Joshi, A., Guidera, J. A., Krausz, T. A., Berke, J. D., Daw, N. D., & Frank, L. M. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.23.613567 · Cited by 10
Distributed Intracranial Activity Underlying Human Decision-making Behavior
Overton, J. A., Moxon, K. A., Stickle, M. P., Peters, L. M., Lin, J. J., Chang, E. F., Knight, R. T., Hsu, M., & Sáez, I. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.0572-24.2024 · Cited by 13
Egalitarian reward contingency in competitive games and primate prefrontal neuronal activity
Hosokawa, T., & Watanabe, M. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00165 · Cited by 9
Vázquez, D., Schneider, K. N., & Roesch, M. R. (2022) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2022.926388 · Cited by 11
Decision-making shapes dynamic inter-areal communication within macaque ventral frontal cortex
Stoll, F. M., & Rudebeck, P. H. (2024) · Current Biology · doi:10.1016/j.cub.2024.08.034 · Cited by 11
Wang, S., Shi, Y., & Li, B. (2016) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2016.12.003 · Cited by 11
Mice optimize timed decisions about probabilistic outcomes under deadlines
Gür, E., & Balcı, F. (2017) · Animal Cognition · doi:10.1007/s10071-017-1073-y · Cited by 8
Tyson‐Carr, J., Soto, V., Kokmotou, K., Roberts, H., Fallon, N. B., Byrne, A., Giesbrecht, T., & Stančák, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116213 · Cited by 10
Neural Correlates of Strategy Switching in the Macaque Orbital Prefrontal Cortex
Fascianelli, V., Ferrucci, L., Tsujimoto, S., & Genovesio, A. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.1969-19.2020 · Cited by 8
Laser stimulation of the skin for quantitative study of decision-making and motivation
Pai, J., Ogasawara, T., Bromberg-Martin, E. S., Ogasawara, K., Gereau, R. W., & Monosov, I. E. (2022) · Cell Reports Methods · doi:10.1016/j.crmeth.2022.100296 · Cited by 9
ACC neural ensemble dynamics are structured by strategy prevalence
Proskurin, M., Manakov, M., & Karpova, A. Y. (2023) · eLife · doi:10.7554/elife.84897 · Cited by 10
Dynamic interactions of the cortical networks during thought suppression
Aso, T., Nishimura, K., Kiyonaka, T., Aoki, T., Inagawa, M., Matsuhashi, M., Tobinaga, Y., & Fukuyama, H. (2016) · Brain and Behavior · doi:10.1002/brb3.503 · Cited by 8
He, Q., Liu, J. L., Eschapasse, L., Zagora, A. K., & Brown, T. I. (2023) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2023.108758 · Cited by 7
Krikova, K., Klein, S., Kampa, M., Walter, B., Stark, R. M., & Klucken, T. (2024) · Human Brain Mapping · doi:10.1002/hbm.26711 · Cited by 9
Value construction through sequential sampling explains serial dependencies in decision making
Zylberberg, A., Bakkour, A., Shohamy, D., & Shadlen, M. N. (2024) · eLife · doi:10.7554/elife.96997.3 · Cited by 18
A Novel Weight Lifting Task for Investigating Effort and Persistence in Rats
Porter, B. S., & Hillman, K. L. (2019) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2019.00275 · Cited by 7
Emberly, E. G., & Seamans, J. K. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa019 · Cited by 11
Wallis, J. D. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-12-804281-6.00015-x · Cited by 8
Self-citationA stable, distributed code for cue value in mouse cortex during reward learningPreprint
Ottenheimer, D. J., Hjort, M. M., Bowen, A. J., Steinmetz, N. A., & Stuber, G. D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.13.499930 · Cited by 7
Feedback-related brain activity in individual decision: evidence from a gambling EEG study
Jiang, L., Wang, G., Zhang, S., Ye, J., He, R., Chen, B., Si, Y., Yao, D., Yu, J., Wan, F., et al. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad430 · Cited by 6
Londei, F., Ceccarelli, F., Arena, G., Ferrucci, L., Russo, E., Brunamonti, E., & Genovesio, A. (2025) · The Journal of Physiology · doi:10.1113/jp288015 · Cited by 8
The Neural Correlates of Intelligence Comparison
Wen, X., Cant, J. S., Xiang, Y., Huang, R., & Mo, L. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx329 · Cited by 6
Perkins, A. Q., & Rich, E. L. (2021) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2021.04.019 · Cited by 7
Ohnuki, T., Osako, Y., Manabe, H., Sakurai, Y., & Hirokawa, J. (2021) · Neuroscience Research · doi:10.1016/j.neures.2021.07.002 · Cited by 4
Inhibitory control of frontal metastability sets the temporal signature of cognitionPreprint
Fontanier, V., Sarazin, M., Stoll, F. M., Delord, B., & Procyk, E. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.20.259192 · Cited by 6
Dorsal raphe neurons signal integrated value during multi-attribute decision-makingPreprint
Feng, Y.-Y., Bromberg-Martin, E. S., & Monosov, I. E. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.17.553745 · Cited by 6
Predictive filtering of sensory response via orbitofrontal top-down inputPreprint
Tsukano, H., Garcia, M. M., Dandu, P. R., & Kato, H. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.17.613562 · Cited by 6
Orbitofrontal-Hippocampal State Coding Dynamics during Reversal Learning
Sanchez, A. N., Ford, C. F., Balewski, Z. Z., & Wallis, J. D. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1228-24.2025 · Cited by 5
Self-citationDistinct representations of economic variables across regions and projections of the frontal cortex
Majumdar, A., Ashcroft, C. A., Fritsche, M., Tan, S., Zatka-Haas, P., Fölsz, O., Walker, N., Mistry, L., Rominto, A. M., Tvrdic, M., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.09.027 · Cited by 5
Distinct cortico-striatal compartments drive competition between adaptive and automatized behavior
Barnett, W. H., Kuznetsov, A. S., & Lapish, C. C. (2023) · PLoS ONE · doi:10.1371/journal.pone.0279841 · Cited by 6
Tan, J., Zhang, X., Wu, S., Song, Z., & Wang, Y. (2024) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2024.3503713 · Cited by 6
Wang, X., Wang, D., & Zhao, Y. (2025) · Cognitive Computation · doi:10.1007/s12559-025-10416-2 · Cited by 6
Dynamic coding and sequential integration of multiple reward attributes by primate amygdala neurons
Fabian Grabenhorst, B., & Báez-Mendoza, R. (2025) · Nature Communications · doi:10.1038/s41467-025-58270-y · Cited by 6
Fidelity of the representation of value in decision-making
Bays, P. M., & Dowding, B. A. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005405 · Cited by 7
Porter, B. S., & Hillman, K. L. (2021) · Journal of Neurophysiology · doi:10.1152/jn.00003.2021 · Cited by 6
Behavioral read out of population value signals in primate orbitofrontal cortexPreprint
McGinty, V. B., & Lupkin, S. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.11.434452 · Cited by 5
Traveling waves in the monkey frontoparietal network predict recent reward memoryPreprint
Zabeh, E., Foley, N. C., Jacobs, J., & Gottlieb, J. P. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.02.03.478583 · Cited by 5
Neural dynamics of an extended frontal lobe network in goal-subgoal problem solvingPreprint
Mione, V., Achterberg, J., Mitchell, D. J., Kusunoki, M., Buckley, M. J., & Duncan, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.06.652442 · Cited by 8
Xu, Q., Yin, W., Zhou, X., Wang, S., Chen, S., Yang, J., Xi, C., & Sun, Z. (2025) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2024.1511287 · Cited by 4
Motivational control is implemented by a cingulo-prefrontal network
Gandaux, C., Sallet, J., Amiez, C., Autran-Clavagnier, D., Morel-Latour, V., Goussi-Denjean, C., Fontanier, V., Misery, P., Lamy, C., Lamberton, F., et al. (2025) · Current Biology · doi:10.1016/j.cub.2025.10.003 · Cited by 13
Regional specialization in prefrontal cortex manifests in the reliability of task progression codes
Guidera, J. A., Gramling, D. P., Comrie, A. E., Joshi, A., Tseng, S.-Y., Denovellis, E. L., Smyth, C., Lee, K. H., Zhou, J. J., Thompson, P., et al. (2026) · Neuron · doi:10.1016/j.neuron.2026.01.023 · Cited by 8
Willoughby, K. W. (2019) · Routledge eBooks · doi:10.4324/9780429308444-10 · Cited by 4
Goussi-Denjean, C., Fontanier, V., Stoll, F. M., & Procyk, E. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0007-22.2023 · Cited by 5
Linking neural activity to complex decisions
Hayden, B. Y., & Pasternak, T. (2013) · Visual Neuroscience · doi:10.1017/s0952523813000345 · Cited by 4
Subspace alignment as a mechanism for bindingPreprint
Fine, J. M., Yoo, S. B. M., Ebitz, R. B., & Hayden, B. Y. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.07.451472 · Cited by 4
Distinct neural representations for prosocial and self-benefitting effortPreprint
Lockwood, P. L., Wittmann, M. K., Nili, H., Matsumoto-Ryan, M., Abdurahman, A., Cutler, J., Masud Husain, B., & Apps, M. A. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.27.461936 · Cited by 4
Regional specialization manifests in the reliability of neural population codesPreprint
Guidera, J. A., Gramling, D. P., Comrie, A. E., Joshi, A., Denovellis, E. L., Lee, K. H., Zhou, J. J., Thompson, P., Vargas-Hernández, J. G., Yorita, A. M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.25.576941 · Cited by 4
Neural basis of cognitive control signals in anterior cingulate cortex during delay discountingPreprint
Seamans, J. K., White, S., Morningstar, M. D., Emberly, E. G., Linsenbardt, D. N., Ma, B., Czachowski, C. L., & Lapish, C. C. (2024) · eLife · doi:10.7554/elife.99930 · Cited by 4
Neural representation of the decisional reference point in monkeys
Nguyen, D., Rich, E. L., Wallis, J. D., Louie, K., & Glimcher, P. W. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2514110122 · Cited by 2
Self-citationClinical Computational Neuroscience
Hallquist, M. N., & Dombrovski, A. Y. (2020) · Cambridge University Press eBooks · doi:10.1017/9781316995808.017 · Cited by 3
Risk related brain regions detection and individual risk classification with 3D image FPCA
Chen, Y., Härdle, W. K., He, Q., & Majer, P. (2018) · Statistics & Risk Modeling · doi:10.1515/strm-2017-0011 · Cited by 4
Reference and preference: how does the brain scale subjective value?
Clithero, J. A. (2009) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.011.2009 · Cited by 4
Feedback-related potentials and oscillations during trial and error learning in Parkinson’s diseasePreprint
Viñales, L., Procyk, E., & Quilodran, R. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.05.438433 · Cited by 3
Multi-areal neural dynamics encode human decision makingPreprint
Overton, J. A., Moxon, K. A., Stickle, M. P., Peters, L. M., Lin, J. J., Chang, E. F., Knight, R. T., Hsu, M., & Sáez, I. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.05.502992 · Cited by 3
A stable, distributed code for cue value in mouse cortex during reward learningPreprint
Ottenheimer, D. J., Hjort, M. M., Bowen, A. J., Steinmetz, N. A., & Stuber, G. D. (2023) · eLife · doi:10.7554/elife.84604.2 · Cited by 4
Neural basis of cognitive control signals in anterior cingulate cortex during delay discountingPreprint
Seamans, J. K., Emberly, E. G., White, S., Morningstar, M. D., Linsenbardt, D. N., Ma, B., Czachowski, C. L., & Lapish, C. C. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.07.597894 · Cited by 3
Causal Economic Machine Learning (CEML): “Human AI”
Horton, A. (2024) · AI · doi:10.3390/ai5040094 · Cited by 3
Härmson, O., Grennan, I., Perry, B. A. L., Toth, R. A., McNamara, C. G., Denison, T., Cagnan, H., Manohar, S., Walton, M. E., & Sharott, A. (2025) · Cell Reports · doi:10.1016/j.celrep.2024.115209 · Cited by 5
Orbitofrontal cortex spontaneously recovers latent information about outcomes upon devaluation
Hart, E. E., Bahena, L., & Schoenbaum, G. M. (2025) · Current Biology · doi:10.1016/j.cub.2025.07.083 · Cited by 2
Exploring the Interplay of Working Memory, Apathy, and Mood/Emotional Factors
di Courtelary, E. T., Scozia, G., Lasaponara, S., Aguzzetti, G., Doricchi, F., & Conversi, D. (2024) · Brain Sciences · doi:10.3390/brainsci14010078 · Cited by 2
Prefrontal–Amygdala Pathways for Object and Social Value Representation
Pujara, M. S., & Murray, E. A. (2024) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02144 · Cited by 2
Orbitofrontal cortical activity during repeated free choice
Campos, M., Koppitch, K. A., Andersen, R. A., & Shimojo, S. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00690.2010 · Cited by 2
Petracca, E. (2022) · Economics and Philosophy · doi:10.1017/s0266267122000189 · Cited by 2
Brain Systems for the Pleasure of Food and Other Primary Rewards
Fabian Grabenhorst, B. (2014) · Springer eBooks · doi:10.1007/978-94-017-8591-4_8 · Cited by 3
Boas, C. A. V. (2015) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.41.2015.tde-20052015-095851 · Cited by 2
Anderson, B. J. P. (2010) · doi:10.17077/etd.6usjkjo3 · Cited by 2
Pelletier, G., Aridan, N., Fellows, L. K., & Schönberg, T. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.29.319293 · Cited by 2
Härmson, O., Grennan, I., Perry, B. A. L., Toth, R., McNamara, C. G., Denison, T., Cagnan, H., Manohar, S., Walton, M. E., & Sharott, A. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.31.563750 · Cited by 2
Dynamics of ACC excitatory neurons during reversal learning: Implications for cognitive flexibility
Zhang, M., Shen, F., Liao, C., Liu, S., Wang, H., & Li, C. (2025) · Behavioural Brain Research · doi:10.1016/j.bbr.2025.115902 · Cited by 1
Identity-specific reward expectations in orbitofrontal cortex guide goal-directed choices
Witkowski, P. P., Henein, N., Moussa, N., Schoenbaum, G. M., & Kahnt, T. (2026) · PLoS Biology · doi:10.1371/journal.pbio.3003829 · Cited by 1
Starkweather, C. K., Willbrand, E. H., Sellers, K. K., Hullett, P. W., Krystal, A. D., Lee, A. M., Weiner, K. S., Willie, J. T., Brunner, P., Hsu, M., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02444-4 · Cited by 2
The amygdala accountant: new tricks for an old structure
Mosher, C. P., & Rudebeck, P. H. (2015) · Nature Neuroscience · doi:10.1038/nn.3949 · Cited by 1
Neuroscience: Intracranial Recordings of Value
Kaanders, P., & Hunt, L. T. (2018) · Current Biology · doi:10.1016/j.cub.2018.08.003 · Cited by 1
Passingham, R. E. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198844570.003.0003 · Cited by 1
The Neuroeconomics of Food Selection and Purchase
Essex, B. G., & Zald, D. H. (2010) · Elsevier eBooks · doi:10.1016/b978-0-12-374387-9.00007-6 · Cited by 1
Reference and preference: how does the brain scale subjective value?
Clithero, J. A., & Smith, D. V. (2009) · PubMed Central · doi:10.3389/neuro.09/011.2009 · Cited by 1
Processos não-declarativos em tomadas de decisão: modelos e experimentos
Dias, Á. M. (2010) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.47.2010.tde-27072010-081906 · Cited by 1
Umemoto, A. (2016) · UVic’s Research and Learning Repository (University of Victoria) · Cited by 1
Neuroscience of Value‐Guided Choice
Jocham, G., Boorman, E. D., & Behrens, T. E. J. (2016) · Wiley eBooks · doi:10.1002/9781118650813.ch22 · Cited by 1
Ni, Y., Su, J., Wang, S., & Wan, X. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3155882 · Cited by 1
Dorsal anterior cingulate cortex neurons only partially integrate determinants of valuePreprint
Azab, H., & Hayden, B. Y. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.01.892380 · Cited by 1
Neural activity in the anterior cingulate cortex is required for effort-based decision makingPreprint
Kashay, A. Q., Cheung, J., Vaknalli, R. N., Delaney, M., Navarro, M. B., Junaidi, C., Veenker, F., Neuwirth, M. E., Gabriel, C., DeNardo, L. A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.22.485350 · Cited by 1
Uncertainty coding in the reward system
Chung, H.-K., Tobler, P. N., & Weber, E. U. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-820480-1.00013-9 · Cited by 2
Neural basis of cognitive control signals in anterior cingulate cortex during delay discountingPreprint
Seamans, J. K., White, S., Morningstar, M. D., Emberly, E. G., Linsenbardt, D. N., Ma, B., Czachowski, C. L., & Lapish, C. C. (2024) · eLife · doi:10.7554/elife.99930.1 · Cited by 1
London, L., Love, M., Zeisler, Z. R., Rudebeck, P., & Stoll, F. M. (2026) · Scientific Data · doi:10.1038/s41597-026-07129-y · Cited by 1
A model of the neural basis of predecisional processes
Taber‐Thomas, B. C. (2011) · doi:10.17077/etd.ekwc19m1
Wallis, J. D., Moorman, D. E., Aston‐Jones, G., Burton, A. C., Kashtelyan, V., Bryden, D. W., Roesch, M. R., Marsh, B. T., Tarigoppula, V. S. A., Chen, C., et al. (2015)
Self-citationThe Prefrontal Cortex and Hierarchical Behavior
Sloan, J. L. (2013) · eScholarship (California Digital Library)
The neural correlates of intentional control
Wisniewski, D. (2016) · edoc Publication server (Humboldt University of Berlin) · doi:10.18452/17500
Coding of sequential behaviors by anterior cingulate cortex ensembles
Ma, L. (2014) · cIRcle (University of British Columbia) · doi:10.14288/1.0167532
Neural coding of grasp force planning and control in macaque areas AIP, F5, and M1
Intveld, R. W. (2016) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-5912
decisions requiring an effort-reward trade-off
Klein-Flügge, M. C., Kennerley, S. W., Friston, K. J., & Bestmann, S. (2016)
Self-citation
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