Publikationen:
Abteilung für Computational Neuroscience

Zeitschriftenartikel (83)

1.
Zeitschriftenartikel
Bucher, S.; Brandenburger, A.: Divisive normalization is an efficient code for multivariate Pareto-distributed environments. Proceedings of the National Academy of Sciences of the United States of America 119 (40), e2120581119 (2022)
2.
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Roelofs, K.; Dayan, P.: Freezing revisited: coordinated autonomic and central optimization of threat coping. Nature Reviews Neuroscience 23 (9), S. 568 - 580 (2022)
3.
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Barnby, J.; Dean, R.; Burgess, H.; Kim, J.; Teunisse, A.; Mackenzie, L.; Robinson, G.; Dayan, P.; Richards, L.: Increased persuadability and credulity in people with corpus callosum dysgenesis. Cortex 155, S. 251 - 263 (2022)
4.
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Barnby, J.; Raihani, N.; Dayan, P.: Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent. Cognition 225, 105098 (2022)
5.
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Castro-Rodrigues, P.; Akam, T.; Snorasson, I.; Camacho, M.; Paixão, V.; Maia, A.; Barahona-Corrêa, J.; Dayan, P.; Simpson, H.; Costa, R. et al.; Oliveira-Maia, A.: Explicit knowledge of task structure is a primary determinant of human model-based action. Nature Human Behaviour 6 (8), S. 1126 - 1141 (2022)
6.
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Dubey, R.; Griffiths, T.; Dayan, P.: The pursuit of happiness: A reinforcement learning perspective on habituation and comparisons. PLoS Computational Biology 18 (8), e1010316 (2022)
7.
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Gagne, C.; Agai, S.; Ramiro, C.; Dayan, P.; Bishop, S.: Biased belief priors versus biased belief updating: Differential correlates of depression and anxiety. PLoS Computational Biology 18 (8), e1010176 (2022)
8.
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Janet, R.; Ligneul, R.; Losecaat-Vermeer, A.; Philippe, R.; Bellucci, G.; Derrington, E.; Park, S.; Dreher, J.-C.: Regulation of social hierarchy learning by serotonin transporter availability. Neuropsychopharmacology Epub ahead (2022)
9.
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Khajehabdollahi, S.; Prosi, J.; Giannakakis, E.; Martius, G.; Levina, A.: When to Be Critical? Performance and Evolvability in Different Regimes of Neural Ising Agents. Artificial Life Epub ahead (2022)
10.
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Lubianiker, N.; Paret, C.; Dayan, P.; Hendler, T.: Neurofeedback through the lens of reinforcement learning. Trends in Neurosciences 45 (8), S. 579 - 593 (2022)
11.
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Safavi, S.; Dayan, P.: Multistability, perceptual value, and internal foraging. Neuron Epub ahead (2022)
12.
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Bellucci, G.; Wang, C.; Sai, L.; Krueger, F.: Reply to Zhen and Yu: Cognitive control as questionable proxy for deliberation in honest behaviors. Proceedings of the National Academy of Sciences of the United States of America 119 (27), e2203613119 (2022)
13.
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Brielmann, A.; Dayan, P.: A computational model of aesthetic value. Psychological Review Epub ahead (2022)
14.
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Buendía, V.; Villegas, P.; Burioni, R.; Muñoz, M.: The broad edge of synchronization: Griffiths effects and collective phenomena in brain networks. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 380 (2227), 20200424 (2022)
15.
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Jain, Y.; Callaway, F.; Griffiths, T.; Dayan, P.; Krueger, P.; Lieder, F.: A computational process-tracing method for measuring people’s planning strategies and how they change over time. Behavior Research Methods Epub ahead (2022)
16.
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Bellucci, G.; Münte, T.; Park, S.: Influences of social uncertainty and serotonin on gambling decisions. Scientific Reports 12 (1), 10220 (2022)
17.
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Bellucci, G.: A Model of Trust. Games 13 (3), 39 (2022)
18.
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Bröker, F.; Love, B.; Dayan, P.: When unsupervised training benefits category learning. Cognition 221, 104984 (2022)
19.
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Kastner, D.; Miller, E.; Yang, Z.; Roumis, D.; Frank, L.; Dayan, P.: Spatial preferences account for inter-animal variability during the continual learning of a dynamic cognitive task. Cell Reports 39 (3), 110708 (2022)
20.
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Zeraati, R.; Engel, T.; Levina, A.: A flexible Bayesian framework for unbiased estimation of timescales. Nature Computational Science 2 (3), S. 193 - 204 (2022)
21.
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Gagne, C.; Dayan, P.: Peril, Prudence and Planning as Risk, Avoidance and Worry. Journal of Mathematical Psychology 106 (2022)
22.
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Lawrance, E.; Gagne, C.; O'Reilly, J.; Bijsterbosch, J.; Bishop, S.: The Computational and Neural Substrates of Ambiguity Avoidance in Anxiety. Computational Psychiatry 6 (1), S. 8 - 33 (2022)
23.
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Antonov, G.; Gagne, C.; Eldar, E.; Dayan, P.: Optimism and Pessimism in Optimised Replay. PLoS Computational Biology 18 (1) (2022)
24.
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Brielmann, A.; Buras, N.; Salingaros, N.; Taylor, R.: What Happens in Your Brain When You Walk Down the Street? Implications of Architectural Proportions, Biophilia, and Fractal Geometry for Urban Science. Urban Science 6 (1), 3 (2022)
25.
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Dayan, P.: "Liking" as an early and editable draft of long-run affective value. PLoS Biology 20 (1), S. 1 - 15 (2022)
26.
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Berridge, K.; Dayan, P.: Liking. Current Biology 31 (24), S. R1555 - R1557 (2021)
27.
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Deserno, L.; Moran, R.; Michely, J.; Lee, Y.; Dayan, P.; Dolan, R.: Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference. eLife 10 (2021)
28.
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Horvath, L.; Colcombe, S.; Milham, M.; Ray, S.; Schwartenbeck, P.; Ostwald, D.: Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit Task. Computational Brain & Behavior 4 (4), S. 442 - 462 (2021)
29.
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Wu, Y.; Veerareddy, A.; Lee, M.; Bellucci, G.; Camilleri, J.; Eickhoff, S.; Krueger, F.: Understanding identification-based trust in the light of affiliative bonding: Meta-analytic neuroimaging evidence. Neuroscience and Biobehavioral Reviews 131, S. 627 - 641 (2021)
30.
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Yang, Q.; Bellucci, G.; Hoffman, M.; Hsu, K.-T.; Lu, B.; Deshpande , G.; Krueger, F.: Intrinsic functional connectivity of the frontoparietal network predicts inter-individual differences in the propensity for costly third-party punishment. Cognitive, Affective and Behavioral Neuroscience 21 (6), S. 1222 - 1232 (2021)
31.
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Fardet, T.; Levina, A.: Weighted directed clustering: interpretations and requirements for heterogeneous, inferred, and measured networks. Physical Review Research 3, 043124, S. 1 - 16 (2021)
32.
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Neville, V.; Dayan, P.; Gilchrist, I.; Paul, E.; Mendl, M.: Using Primary Reinforcement to Enhance Translatability of a Human Affect and Decision-Making Judgment Bias Task. Journal of Cognitive Neuroscience 33 (12), S. 2523 - 2535 (2021)
33.
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Na, S.; Chung, D.; Hula, A.; Perl, O.; Jung, J.; Heflin, M.; Blackmore , S.; Fiore, V.; Dayan, P.; Gu, X.: Humans use forward thinking to exploit social controllability. eLife 10 (2021)
34.
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Sai, L.; Bellucci, G.; Wang, C.; Fu, G.; Camilleri , J.; Eickhoff, S.; Krueger, F.: Neural mechanisms of deliberate dishonesty: Dissociating deliberation from other control processes during dishonest behaviors. Proceedings of the National Academy of Sciences of the United States of America 118 (43), S. 1 - 3 (2021)
35.
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Brielmann, A.; Nuzzo, A.; Pelli, D.: Beauty, the feeling. Acta Psychologica 219, S. 1 - 12 (2021)
36.
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Buendia, V.; Villegas, P.; Burioni, R.; Muñoz, M.: The broad edge of synchronisation: Griffiths effects and collective phenomena in brain networks. (eingereicht)
37.
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Hall-McMaster , S.; Dayan, P.; Schuck, N.: Control over patch encounters changes foraging behavior. iScience 24 (9), 103005 (2021)
38.
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Silston, B.; Wise, T.; Qi, S.; Sui, X.; Dayan, P.; Mobbs, D.: Neural encoding of perceived patch value during competitive and hazardous virtual foraging. Nature Communications 12, 5478 (2021)
39.
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Terenzi, D.; Liu, L.; Bellucci, G.; Park, S.: Determinants and modulators of human social decisions. Neuroscience and Biobehavioral Reviews 128, S. 383 - 393 (2021)
40.
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Mancinelli, F.; Roiser, J.; Dayan, P.: Internality and the internalisation of failure: Evidence from a novel task. PLoS Computational Biology 17 (7), S. 1 - 25 (2021)
41.
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Moran, R.; Dayan, P.; Dolan, R.: Efficiency and prioritization of inference-based credit assignment. Current Biology 31 (13), S. 2747 - 2756 (2021)
42.
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Kóbor, A.; Kardos, Z.; Takács, Á.; Éltetö, N.; Janacsek, K.; Tóth-Fáber, E.; Csépe, V.; Nemeth, D.: Adaptation to recent outcomes attenuates the lasting effect of initial experience on risky decisions. Scientific Reports 11 (1), 10132, S. 1 - 20 (2021)
43.
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Brielmann, A.; Pelli, D.: The pleasure of multiple images. Attention, Perception & Psychophysics 83 (3), S. 1179 - 1188 (2021)
44.
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Brielmann, A.; Pelli, D.: Correction to: The pleasure of multiple images. Attention, Perception & Psychophysics 83 (3), S. 1189 (2021)
45.
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Dayan, P.: When will's wont wants wanting. Behavioral and Brain Sciences 44, e35 (2021)
46.
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Faulkner, P.; Huys, Q.; Renz, D.; Eshel, N.; Pilling, S.; Dayan, P.; Roiser, J.: A Comparison of "Pruning" During Multi-Step Planning in Depressed and Healthy Individuals. Psychological Medicine Epub ahead (2021)
47.
Zeitschriftenartikel
Sargent, K.; Chavez-Baldini, U.; Master, S.; Verweij, K.; Lok, A.; Sutterland, A.; Vulink, N.; Denys, D.; Smit, D.; Nieman, D.: Resting-state brain oscillations predict cognitive function in psychiatric disorders: A transdiagnostic machine learning approach. NeuroImage: Clinical 30, 102617, S. 1 - 9 (2021)
48.
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Sukenik, N.; Vinogradov, O.; Weinreb, E.; Segal, M.; Levina, A.; Moses, E.: Neuronal circuits overcome imbalance in excitation and inhibition by adjusting connection numbers. Proceedings of the National Academy of Sciences of the United States of America 118 (12), S. 1 - 9 (2021)
49.
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Akam, T.; Rodrigues-Vaz, I.; Marcelo , I.; Zhang, X.; Pereira, M.; Freire Oliveira , R.; Dayan, P.; Costa, R.: The Anterior Cingulate Cortex Predicts Future States to Mediate Model-Based Action Selection. Neuron 109 (1), S. 149 - 163 (2021)
50.
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Hall-McMaster, S.; Dayan, P.; Schuck, N.: Control over patch encounters changes foraging behaviour. iScience Epub ahead (2021)
51.
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Moran, R.; Dayan, P.; Dolan, R.: Human subjects exploit a cognitive map for credit assignment. Proceedings of the National Academy of Sciences of the United States of America 118 (4), S. 1 - 12 (2021)
52.
Zeitschriftenartikel
Neville, V.; Dayan, P.; Gilchrist, I.; Paul, E.; Mendl, M.: Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach. PLoS Computational Biology 17 (1), S. 1 - 27 (2021)
53.
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Bröker, F.; Ramscar, M.: Representing absence of evidence: why algorithms and representations matter in models of language and cognition. Language, Cognition and Neuroscience Epub ahead (2020)
54.
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Gagne, C.; Zika, O.; Dayan, P.; Bishop, S.: Impaired adaptation of learning to contingency volatility in internalizing psychopathology. eLife 9, S. 1 - 51 (2020)
55.
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Schulz, E.; Dayan, P.: Computational psychiatry for computers. iScience 23 (12), 101772 (2020)
56.
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Schulz, L.; Rollwage, M.; Dolan, R.; Fleming, S.: Dogmatism manifests in lowered information search under uncertainty. Proceedings of the National Academy of Sciences of the United States of America 117 (49), S. 31527 - 31534 (2020)
57.
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Bellucci, G.; Camilleri, J.; Eickhoff, S.; Krueger, F.: Neural signatures of prosocial behaviors. Neuroscience and Biobehavioral Reviews 118, S. 186 - 195 (2020)
58.
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Dayan, P.: Learning rules. Current Biology 30 (21), S. R1289 - R1290 (2020)
59.
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Dezfouli, A.; Nock, R.; Dayan, P.: Adversarial vulnerabilities of human decision-making. Proceedings of the National Academy of Sciences of the United States of America 117 (46), 202016921, S. 29221 - 29228 (2020)
60.
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Bellucci, G.: Positive attitudes and negative expectations in lonely individuals. Scientific Reports 10 (1), 18595, S. 1 - 9 (2020)
61.
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Neville, V.; King, J.; Gilchrist, I.; Dayan, P.; Paul, E.; Mendl, M.: Author Correction: Reward and punisher experience alter rodent decision-making in a judgement bias task. Scientific Reports 11 (1), 21387 (2020)
62.
Zeitschriftenartikel
Kastner, D.; Gillespie, A.; Dayan, P.; Frank, L.: Memory Alone Does Not Account for the Way Rats Learn a Simple Spatial Alternation Task. The Journal of Neuroscience 40 (38), S. 7311 - 7317 (2020)
63.
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Neville, V.; King, J.; Gilchrist, I.; Dayan, P.; Paul, E.; Mendl, M.: Reward and punisher experience alter rodent decision-making in a judgement bias task. Scientific Reports 10 (1), 11839, S. 1 - 14 (2020)
64.
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Bellucci, G.; Camilleri, J.; Iyengar, V.; Eickhoff, S.; Krueger, F.: The Emerging Neuroscience of Social Punishment: Meta-Analytic Evidence. Neuroscience and Biobehavioral Reviews 113, S. 426 - 439 (2020)
65.
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Bellucci, G.; Münte, T.; Park , S.: Effects of a dopamine agonist on trusting behaviors in females. Psychopharmacology 237 (6), S. 1671 - 1680 (2020)
66.
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Dayan, P.: Representation, abstraction, and simple-minded sophisticates. Behavioral and Brain Sciences 43, e126 (2020)
67.
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Eldar, E.; Lièvre, G.; Dayan, P.; Dolan, R.: The roles of online and offline replay in planning. eLife 9, e56911, S. 1 - 23 (2020)
68.
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Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dayan, P.; Dolan , R.: The Value of What's to Come: Neural Mechanisms Coupling Prediction Error and the Utility of Anticipation. Science Advances 6 (25), eaba3828, S. 1 - 16 (2020)
69.
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Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dayan, P.; Dolan, R.: The value of what’s to come: Neural mechanisms coupling prediction error and the utility of anticipation. Science Advances 6, 25, S. 1 - 16 (2020)
70.
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Krueger, F.; Bellucci, G.; Xu, P.; Feng, C.: The Critical Role of the Right Dorsal and Ventral Anterior Insula in Reciprocity: Evidence From the Trust and Ultimatum Games. Frontiers in Human Neuroscience 14, 176, S. 1 - 6 (2020)
71.
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Mobbs, D.; Headley, D.; Ding, W.; Dayan, P.: Space, Time, and Fear: Survival Computations along Defensive Circuits. Trends in Cognitive Sciences 24 (3), S. 228 - 241 (2020)
72.
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Schad, D.; Rapp, M.; Garbusow, M.; Nebe, S.; Sebold, M.; Obst, E.; Sommer, C.; Deserno, L.; Rabovsky, M.; Friedel, E. et al.; Romanczuk-Seiferth , N.; Wittchen, H.-U.; Zimmermann, U.; Walter, H.; Sterzer, P.; Smolka, M.; Schlagenhauf, F.; Heinz, A.; Dayan, P.; Huys, Q.: Dissociating neural learning signals in human sign- and goal-trackers. Nature Human Behaviour 4 (2), S. 201 - 214 (2020)
73.
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Stojić, H.; Orquin, J.; Dayan, P.; Dolan, R.; Speekenbrink, M.: Uncertainty in learning, choice and visual fixation. Proceedings of the National Academy of Sciences of the United States of America 117 (6), S. 3291 - 3300 (2020)
74.
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Lloyd, K.; Sanborn, A.; Leslie, D.; Lewandowsky, S.: Why Higher Working Memory Capacity May Help You Learn: Sampling, Search, and Degrees of Approximation. Cognitive Science 43 (12), S. 1 - 43 (2019)
75.
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Wise, T.; Michely, J.; Dayan, P.; Dolan, R.: A computational account of threat-related attentional bias. PLoS Computational Biology 15 (10), S. 1 - 21 (2019)
76.
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Zhao, S.; Chait, M.; Dick, F.; Dayan, P.; Furukawa, S.; Liao, H.: Pupil-linked phasic arousal evoked by violation but not emergence of regularity within rapid sound sequences. Nature Communications 10, 4030, S. 1 - 16 (2019)
77.
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Javadi, A.; Patai, E.; Marin-Garcia, E.; Margolis, A.; Tan, H.-R.; Kumaran, D.; Nardini, M.; Duzel, E.; Dayan, P.; Spiers, H.: Prefrontal Dynamics Associated with Efficient Detours and Shortcuts: A Combined Functional Magnetic Resonance Imaging and Magnetoencenphalography Study. Journal of Cognitive Neuroscience 31 (8), S. 1227 - 1247 (2019)
78.
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Javadi, A.-H.; Patai, E.; Marin-Garcia, E.; Margois, A.; Tan, H.-R.; Kumaran, D.; Nardini, M.; Penny, W.; Duzel, E.; Dayan, P. et al.; Spiers, H.: Backtracking during navigation is correlated with enhanced anterior cingulate activity and suppression of alpha oscillations and the "default-mode" network. Proceedings of the Royal Society B: Biological Sciences 286 (1908), 20191016, S. 1 - 9 (2019)
79.
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Ahilan, S.; Solomon, R.; Breton, A.-Y.; Conover, K.; Niyogi, R.; Shizgal, P.; Dayan, P.: Learning to use past evidence in a sophisticated world model. PLoS Computational Biology 15 (6), S. 1 - 20 (2019)
80.
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Dezfouli , A.; Griffiths, K.; Ramos, F.; Dayan, P.; Balleine, B.: Models that learn how humans learn: The case of decision-making and its disorders. PLoS Computational Biology 16 (6), S. 1 - 33 (2019)
81.
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Rouault, M.; Dayan, P.; Fleming, S.: Forming global estimates of self-performance from local confidence. Nature Communications 10 (1), 1141, S. 1 - 11 (2019)
82.
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Moran, R.; Keramati, M.; Dayan, P.; Dolan, R.: Retrospective model-based inference guides model-free credit assignment. Nature Communications 10, 750, S. 1 - 14 (2019)
83.
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Moutoussis, M.; Bullmore, E.; Goodyer, I.; Fonagy, P.; Jones, P.; Dolan, R.; Dayan, P.: Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood. PLoS Computational Biology 14 (12), S. 1 - 26 (2018)

Buchkapitel (5)

84.
Buchkapitel
Bellucci, G.; Dreher, J.-C.: Trust and Learning. In: The Neurobiology of Trust, 8, S. 185 - 220 (Hg. Krueger, F.). Cambridge University Press, Cambridge, UK (2022)
85.
Buchkapitel
Brielmann, A.: Empirical Aesthetics. In: Internet Encyclopedia of Philosophy (Hg. Fieser, J.; Dowden, B.) (2021)
86.
Buchkapitel
Dayan, P.; Roiser, J.; Viding, E.: The first steps on long marches: The costs of active observation. In: Psychiatry Reborn: Biopsychosocial psychiatry in modern medicine, 14, S. 213 - 228 (Hg. Davies, W.; Savulescu, J.; Roache, R.; Loebel, J.). Oxford University Press, Oxford, UK (2020)
87.
Buchkapitel
Gouw, M.; Alvarado-Valverde, J.; Čalyševa, J.; Diella, F.; Kumar, M.; Michael, S.; Van Roey, K.; Dinkel, H.; Gibson, T.: How to Annotate and Submit a Short Linear Motif to the Eukaryotic Linear Motif Resource. In: Intrinsically Disordered Proteins: Methods and Protocols, S. 73 - 102 (Hg. Kragelund, B.; Skriver, K.). Humana, New York, NY, USA (2020)
88.
Buchkapitel
Dayan, P.; Nakahara, H.: Models and Methods for Reinforcement Learning. In: Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Bd. 5: Methodology, 4. Aufl., S. 1 - 40 (Hg. Wixted, J.; Wagenmakers, E.-J.). Wiley, Hoboken, NJ, USA (2018)

Konferenzbeitrag (20)

89.
Konferenzbeitrag
Bruijns, S.; The International Brain Laboratory; Dayan, P.: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2022 Conference on Cognitive Computational Neuroscience, P-1.19, S. 64 - 66. Conference on Cognitive Computational Neuroscience (CCN 2022), San Francisco, CA, USA, 25. August 2022 - 28. August 2022. (2022)
90.
Konferenzbeitrag
Khajehnejad, M.; Habibollahi, F.; Nock, R.; Arabzadeh, E.; Dayan, P.; Dezfouli, A.: Neural Network Poisson Models for Behavioural and Neural Spike Train Data. In: International Conference on Machine Learning, 17-23 July 2022, Baltimore, Maryland, USA, S. 10974 - 10996 (Hg. Chaudhuri, K.; Jegelka, S.; Song, L.; Szepesvari, C.; Niu, G. et al.). Thirty-ninth International Conference on Machine Learning (ICML 2022), Baltimore, MD, USA, 17. Juli 2022 - 23. Juli 2022. (2022)
91.
Konferenzbeitrag
Renz, F.; Grossman, S.; Dayan, P.; Doeller, C.; Schuck, N.: Representation learning facilitates different levels of generalization. In: 2022 Conference on Cognitive Computational Neuroscience, P-2.66, S. 460 - 462. Conference on Cognitive Computational Neuroscience (CCN 2022), San Francisco, CA, USA, 25. August 2022 - 28. August 2022. (2022)
92.
Konferenzbeitrag
Ludwig, T.; Wu, C.; Schulz, E.: Connecting Exploration, Generalization, and Planning in Correlated Trees. In: 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity, S. 2940 - 2946 (Hg. Culbertson, J.; Perfors, A.; Rabagliati, H.; Ramenzoni, V.). 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity, Toronto, Canada, 27. Juli 2022 - 30. Juli 2022. (2022)
93.
Konferenzbeitrag
Bröker, F.; Roads, B.; Dayan, P.; Love, B.: Teaching categories to human semi-supervised learners. In: 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), 2.8, S. 122 - 125. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA, 08. Juni 2022 - 11. Juni 2022. (2022)
94.
Konferenzbeitrag
Dayan, P.; Gagne, C.: Two steps to risk sensitivity. In: Advances in Neural Information Processing Systems 34: 35th Conference on Neural Information Processing Systems (NeurIPS 2021), S. 22209 - 22220 (Hg. Ranzato, M.; Beygelzimer, A.; Liang, P.; Vaughan, J.; Dauphin, Y.). Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), 06. Dezember 2021 - 14. Dezember 2021. Curran, Red Hook, NY, USA (2022)
95.
Konferenzbeitrag
Wise, T.; Charpentier, C.; Dayan, P.; Mobbs, D.: Modeling the mind of a predator: Interactive cognitive maps enable avoidance of dynamic threats. In: 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), 1.49, S. 32 - 33. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA, 08. Juni 2022 - 11. Juni 2022. (2022)
96.
Konferenzbeitrag
Gagne, C.; Dayan, P.: Catastrophe, Compounding & Consistency in Choice. In: Workshop on Human and Machine Decisions @ NeurIPS 2021 (WHMD 2021). Workshop on Human and Machine Decisions @ NeurIPS 2021 (WHMD 2021), 14. Dezember 2021. (2021)
97.
Konferenzbeitrag
Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Learning Structure from the Ground up: Hierarchical Representation Learning by Chunking. In: Tenth International Conference on Learning Representations (ICLR 2022). Tenth International Conference on Learning Representations (ICLR 2022), 25. April 2022 - 29. April 2022. (eingereicht)
98.
Konferenzbeitrag
Khajehabdollahi, S.; Giannakakis, E.; Prosi, J.; Levina, A.: Reservoir computing with self-organizing neural oscillators. In: Artificial Life Conference Proceedings, Bd. 2021, 78, S. 1 - 3. ALIFE 2021: The 2021 Conference on Artificial Life, Praha, Czech Republic, 19. Juli 2021 - 23. Juli 2021. MIT Press (2021)
99.
Konferenzbeitrag
Prosi, J.; Khajehabdollahi, S.; Giannakakis, E.; Martius, G.; Levina, A.: The dynamical regime and its importance for evolvability, task performance and generalization. In: Artificial Life Conference Proceedings, Bd. 2021, 79. ALIFE 2021: The 2021 Conference on Artificial Life, Praha, Czech Republic, 19. Juli 2021 - 23. Juli 2021. MIT Press (2021)
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