_{Publications:
Department for Computational Neuroscience}

Kind, A.; Dayan, P.: Two sub-cultures of explanatory computational psychiatry. Molecular Psychiatry 29 (12), pp. 3928 - 3931 (2024)

Sacu, S.; Dubois, M.; Hezemans, F.; Aggensteiner, P.-M.; Monninger, M.; Brandeis, D.; Banaschewski, T.; Hauser, T.; Holz, N.: Early life adversities are associated with lower expected value signaling in the adult brain. Biological Psychiatry 96 (12), pp. 948 - 958 (2024)

Bröker, F.; Holt, L.; Roads, B.; Dayan, P.; Love, B.: Demystifying unsupervised learning: how it helps and hurts. Trends in Cognitive Sciences 28 (11), pp. 974 - 986 (2024)

Gharabaghi, A.; Cebi, I.; Leavitt, D.; Scherer, M.; Bookjans; Bookjans, P.; Brunnett, B.; Milosevic , L.; Weiss, D.: Randomized crossover trial on motor and non-motor outcome of directional deep brain stimulation in Parkinson's disease. npj Parkinson's Disease 10 (1), 204 (2024)

Giannakakis, E.; Vinogradov, O.; Buendía, V.; Levina, A.: Structural influences on synaptic plasticity: the role of presynaptic connectivity in the emergence of E/I co-tuning. PLOS Computational Biology 20 (10), e1012510 (2024)

Alon, N.; Schulz, L.; Bell, V.; Moutoussis, M.; Dayan, P.; Barnby, J.: (Mal)adaptive Mentalizing in the Cognitive Hierarchy, and Its Link to Paranoia. Computational Psychiatry 8 (1), pp. 159 - 177 (2024)

Ahmadabadi, S.; Haghifam, M.; Shah-Mansouri, V.; Ershadmanesh, S.: Design and evaluation of crowdsourcing platforms based on users' confidence judgments. Scientific Reports 14 (1), 18379 (2024)

Medrano, J.; Sajid, N.: A Broken Duet: Multistable Dynamics in Dyadic Interactions. Entropy 26 (9), 731 (2024)

Biderman, D.; Whiteway, M.; Hurwitz, C.; Greenspan, N.; Lee, R.; Vishnubhotla, A.; Warren, R.; Pedraja, F.; Noone, D.; Schartner, M. et al.; Huntenburg, J.; Khanal, A.; Meijer, G.; Noel, J.-P.; Pan-Vazquez, A.; Socha, K.; Urai, A.; The International Brain Laboratory; Cunningham, J.; Sawtell, N.; Paninski, L.: Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools. Nature Methods 21 (7), pp. 1316 - 1328 (2024)

Nath, S.; Brändle, F.; Schulz, E.; Dayan, P.; Brielmann, A.: Relating Objective Complexity, Subjective Complexity and Beauty in Binary Pixel Patterns. Psychology of Aesthetics, Creativity, and the Arts Epub ahead (2024)

Neville, V.; Finnegan, E.; Paul, E.; Davidson, M.; Dayan, P.; Mendl, M.: You are How You Eat: Foraging Behavior as a Potential Novel Marker of Rat Affective State. Affective Science 5 (3), pp. 232 - 245 (2024)

Zeraati, R.; Buendía, V.; Engel, T.; Levina, A.: Topology-dependent coalescence controls scaling exponents in finite networks. Physical Review Research 6 (2), 023131 (2024)

Kang, P.; Tobler, P.; Dayan, P.: Bayesian reinforcement learning: A basic overview. Neurobiology of Learning and Memory 211, 107924 (2024)

Batten, S.; Bang, D.; Kopell, B.; Davies, A.; Heflin, M.; Fu, X.; Perl, O.; Ziafat, K.; Hashemi , A.; Saez, I. et al.; Barbosa, L.; Twomey, T.; Lohrenz, T.; White, J.; Dayan, P.; Charney, A.; Figee, M.; Mayberg, H.; Kishida, K.; Gu, X.; Kishida, P.: Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange. Nature Human Behaviour 8 (4), pp. 718 - 728 (2024)

Master, S.; Curtis, C.; Dayan, P.: Wagers for work: Decomposing the costs of cognitive effort. PLOS Computational Biology 20 (4), e1012060 (2024)

Neville, V.; Mendl, M.; Paul, E.; Seriès, P.; Dayan, P.: A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals. Cognitive, Affective and Behavioral Neuroscience 24 (2), pp. 370 - 383 (2024)

Jäger, A.-T.; Bailey, A.; Huntenburg, J.; Tardif, C.; Villringer, A.; Gauthier, C.; Nikulin, V.; Bazin, P.-L.; Steele, C.: Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training. Human Brain Mapping 45 (4), e26539 (2024)

Kalhan, S.; Schwartenbeck, P.; Hester, R.; Garrido, M.: People with a tobacco use disorder exhibit misaligned Bayesian belief updating by falsely attributing non-drug cues as worse predictors of positive outcomes compared to drug cues. Drug and Alcohol Dependence 256, 111109 (2024)

Muller, T.; Butler, J.; Veselic, S.; Miranda, B.; Wallis, J.; Dayan, P.; Behrens, T.; Kurth-Nelson, Z.; Kennerley , S.: Distributional reinforcement learning in prefrontal cortex. Nature Neuroscience 27 (3), pp. 403 - 408 (2024)

Schulz, L.; Bhui, R.: Political reinforcement learners. Trends in Cognitive Sciences 28 (3), pp. 210 - 222 (2024)

Brielmann, A.; Berentelg, M.; Dayan, P.: Modelling individual aesthetic judgements over time. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 379 (1895), 20220414 (2024)

Brielmann, A.; Dayan, P.: Aesthetic boredom. In: The Routledge International Handbook of Boredom (Eds. Bieleke, M.; Wolff, W.; Martarelli, C.). Routledge, London, UK (2024)

Buckley, C.; Cialfi, D.; Lanillos, P.; Pitliya, R.; Sajid, N.; Shimazaki, H.; Verbelen, T.; Wisse, M. (Eds.): Active Inference: 5th International Workshop, IWAI 2024 (Communications in Computer and Information Science, 2193). IWAI 2024 International Workshop on Active Inference, Oxford, UK, September 09, 2024 - September 11, 2024. Springer, Cham, Switzerland (2024)

Chen, J.; Teng, T.; Shao, Y.; Zhang, H.: Why some simple probabilistic rules are difficult to learn: A hypothesis diffusion model. In: 2024 Conference on Cognitive Computational Neuroscience, C85. Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Lu, H.; Teng, T.; Zhang, H.: The Development of Superstitions in Uncontrollable Environment. In: 2024 Conference on Cognitive Computational Neuroscience, A8. Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Satti, M.; Wille, K.; Nassar, M.; Cichy, R.; Schuck, N.; Dayan, P.; Bruckner, R.: Absence of systematic effects of trait anxiety on learning under uncertainty. In: 7th Annual Conference on Cognitive Computational Neuroscience (CCN 2024). 7th Annual Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Satti, M.; Wille, K.; Nassar, M.; Cichy, R.; Schuck, N.; Dayan, P.; Bruckner, R.: Absence of Systematic Effects of Trait Anxiety on Learning Under Uncertainty. In: 2024 Conference on Cognitive Computational Neuroscience, B27. Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Sui, X.; Dayan, P.; Lloyd, K.: Exploring Optimal Risk-Sensitive Behavior in the Balloon Analogue Risk Task (BART). In: 2024 Conference on Cognitive Computational Neuroscience, A30. Conference on Cognitive Computational Neuroscience (CCN 2024), Boston, MA, USA, August 06, 2024 - August 09, 2024. (2024)

Chebolu, S.; Dayan, P.: Optimal and sub-optimal temporal decisions can explain procrastination in a real-world task. In: 46th Annual Meeting of the Cognitive Science Society (CogSci 2024), pp. 3102 - 3108. 46th Annual Meeting of the Cognitive Science Society (CogSci 2024) , Rotterdam, The Netherlands, July 24, 2024 - July 27, 2024. (2024)

Nazemorroaya, A.; Bang, D.; Dayan, P.: State-Independent and State-Dependent Learning in a Motivational Go/NoGo task. In: 46th Annual Conference of the Cognitive Science Society (CogSci 2024), pp. 2171 - 2178. 46th Annual Conference of the Cognitive Science Society (CogSci 2024), Rotterdam, The Netherlands, July 24, 2024 - July 27, 2024. (2024)

Shen, T.; Nath, S.; Brielmann, A.; Dayan, P.: Simplicity in Complexity: Explaining Visual Complexity using Deep Segmentation Models. In: 46th Annual Conference of the Cognitive Science Society (CogSci 2024), pp. 2017 - 2024. 46th Annual Conference of the Cognitive Science Society (CogSci 2024), Rotterdam, The Netherlands, July 24, 2024 - July 27, 2024. (2024)

Zhou, H.; Nagy, D.; Wu, C.: Harmonizing Program Induction with Rate-Distortion Theory. In: 46th Annual Meeting of the Cognitive Science Society (CogSci 2024), pp. 2511 - 2518. 46th Annual Meeting of the Cognitive Science Society (CogSci 2024), Rotterdam, the Netherlands, July 24, 2024 - July 27, 2024. (2024)

Nath, S.; Dayan, P.; Stevenson, C.: Characterising the Creative Process in Humans and Large Language Models. In: 15th International Conference on Computational Creativity: ICCC'24, 179. 15th International Conference on Computational Creativity (ICCC 2024), Jönköping, Sweden, June 17, 2024 - June 21, 2024. (2024)

Nath, S.; Shen, K.; Brielmann, A.; Dayan, P.: Simplicity in Complexity. In: ICLR 2024 Workshop on Representational Alignment (Re-Align). ICLR 2024 Workshop on Representational Alignment (Re-Align), Wien, Austria, May 11, 2024. (2024)

Saanum, T.; Éltetö, N.; Dayan, P.; Binz, M.; Schulz, E.: Reinforcement Learning with Simple Sequence Priors. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2710, pp. 61985 - 62005 (Eds. Oh, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M. et al.). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, December 10, 2023 - December 16, 2023. Curran, Red Hook, NY, USA (2024)

Antonov, G.; Dayan, P.: Exploring Uncertainty in Distributional Reinforcement Learning. Reinforcement Learning Conference (RLC 2024), Amherst, MA, USA, August 09, 2024 - August 12, 2024. Reinforcement Learning Journal 2, pp. 961 - 978 (2024)

Diaconescu, A.; Laessing, P.; Karvelis, P.; Dayan, P.: Formalizing Pavlovian Biases During Probabilistic Aversive Learning for Suicide Prevention. In Biological Psychiatry, 95 (10 Supplement), p. S63. 79th Annual Scientific Meeting of the Society of Biological Psychiatry (SOBP 2024), Austin, TX, USA, May 09, 2024 - May 11, 2024. Elsevier, New York (2024)

Nath, S.; Shen, K.; Dayan, P.; Brielmann, A.: Quantifying Complexity in Synthetic and Natural Images. In XXVIII Congress of the International Association of Empirical Aesthetics (IAEA 2024), p. 34. XXVIII Congress of the International Association of Empirical Aesthetics (IAEA 2024), Palma de Mallorca, Spain, May 08, 2024 - May 10, 2024. (2024)

Rachum, R.; Nakar, Y.; Tomlinson, B.; Alon, N.; Mirsky, R.: Emergent Dominance Hierarchies in Reinforcement Learning Agents. In 23rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2024), pp. 2426 - 2428. 23rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2024), Auckland, New Zealand, May 06, 2024 - May 10, 2024. (2024)

Dayan, P.: Navigating uncertainty: reward location variability induces reorganization of hippocampal spatial representations. Max Planck School of Cognition: Cognition Colloquium, Leipzig, Germany (2024)

Bruijns, S.; Chebolu, S.: Computations and mechanisms in neural reinforcement learning. Systems Neuroscience Symposium (SNS 2024), Tübingen, Germany (2024)

Dayan, P.: "Liking" as a First Draft of the Affective Future. 11th Biennial Neuroscience Conference (NEURIZONS 2024), Göttingen, Germany (2024)

Dayan, P.; Lloyd, K.; Nazemorroaya, A.; Bang, D.: Controlling the Controller: Instrumental Manipulations of Pavlovian Influences via Dopamine. Fifth International Convention on the Mathematics of Neuroscience and AI (Neuromonster 2024), Roma, Italy (2024)

Kastner, D.; Williams, G.; Holobetz, C.; Romano, J.; Dayan, P.: The choice-wide behavioral association study: data-driven identification of interpretable behavioral components. 63rd Annual Meeting of the American College of Neuropsychopharmacology (ACNP 2024), Phoenix, AZ, USA (2024)

Bucher, S.; Yan, Z.-Y.; Shen, B.; Dayan, P.; Glimcher, P.: Reward Prediction Updates: Tracking Changes in Reward Expectations. Annual Meeting of the Society of NeuroEconomics (SNE 2024), Cascais, Portugal (2024)

Buergi, N.; Konovalov, A.; Biegel, C.; De Araujo, T.; Aydogan, G.; Ruff, C.: Neurocomputational signatures of altered adaptive mentalization in autism. Annual Meeting of the Society of NeuroEconomics (SNE 2024), Cascais, Portugal (2024)

Chebolu, S.; Dayan, P.: Optimal and sub-optimal intertemporal decisions explain procrastination in a real-world task. Annual Meeting of the Society of NeuroEconomics (SNE 2024), Cascais, Portugal (2024)

Kastner, D.; Williams, G.; Holobetz, C.; Romano, J.; Dayan, P.: The choice-wide behavioral association study: data-driven identification of interpretable behavioral components. 53rd Annual Meeting of the Society for Neuroscience (Neuroscience 2024), San Diego, CA, USA (2024)

Yan, Z.-Y.; Bucher, S.; Shen, B.; Dayan, P.; Glimcher, P.: Reward Prediction Updates: What Happens When the Probability of Reward Changes. 53rd Annual Meeting of the Society for Neuroscience (Neuroscience 2024), San Diego, CA, USA (2024)

Chen, J.; Teng, T.; Shao, Y.; Zhang, H.: Why some simple probabilistic rules are difficult to learn: A hypothesis diffusion model. 17th Annual Meeting of the Chinese Neuroscience Society (CNS 2024), Suzhou, China (2024)

Ghalambor, A.; Fakharian, M.; Zeraati, R.; Safavi, S.: Identifying task-specific dynamics in recurrent neural networks using Dynamical Similarity Analysis. Bernstein Conference 2024, Frankfurt/Main, Germany (2024)

Ershadmanesh, S.; Rajabi, S.; Rostami, R.; Moran, R.; Dayan, P.: Noradrenergic and Dopaminergic modulation of control and metacontrol. 32nd Annual Computational Neuroscience Meeting (CNS*2023), Leipzig, Germany (2024)

Safavi, S.; Chalk, M.; Logothetis, N.; Levina, A.: Signatures of criticality in efficient coding networks. 32nd Annual Computational Neuroscience Meeting (CNS*2023), Leipzig, Germany (2024)

Safavi, S.; Dayan, P.: A decision-theoretic approach to binocular rivalry. 32nd Annual Computational Neuroscience Meeting (CNS*2023), Leipzig, Germany (2024)

Giannakakis, E.; Buendia, V.; Vinogradov, O.; Khajehabdollahi, S.; Levina, A.: Overlapping E/I neuronal assemblies generate rich network dynamics and enable complex computations. Research in Encoding and Decoding of Neural Ensembles (AREADNE 2024), Milos, Greece (2024)

Laessing, P.; Karvelis, P.; Kennedy, J.; Zai, C.; Dayan, P.; Diaconescu, A.: Identifying Suicidal Subtypes Using Computational Modelling. 79th Annual Scientific Meeting of the Society of Biological Psychiatry (SOBP 2024), Austin, TX, USA (2024)

Kastner, D.; Holobetz, C.; Yokota, N.; Williams, G.; Lee, C.; Ton, J.; Romano, J.; Dayan, P.: Choice-wide behavioral association study: reliable and interpretable differences across learning. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal (2024)

Shani, D.; Dayan, P.: Integrating allocentric and egocentric representations for flexible navigation. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal (2024)

Tessereau, C.; Mellor, J.; Dayan, P.; Xuan, F.; Dombeck, D.: The hippocampus as an unpredicted map: Hippocampal traces of uncertainties induced by changes in reward distributions. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal (2024)

International Brain Laboratory; Benson, B.; Benson, J.; Birman, D.; Bonacchi, N.; Carandini, M.; Catarino, J.; Chapuis, G.; Churchland, A.; Dan, Y. et al.; Dayan, P.; DeWitt, E.; Engel, T.; Fabbri, M.; Faulkner, M.; Fiete, I.; Findling, C.; Freitas-Silva, L.; Gercek, B.; Harris, K.; Häusser, M.; Hofer, S.; Hu, F.; Hubert, F.; Huntenburg, J.; Khanal, A.; Krasniak, C.; Langdon, C.; Lau, P.; Mainen, Z.; Meijer, G.; Miska, N.; Mrsic-Flogel, T.; Noel, J.-P.; Nylund, K.; Pan-Vazquez, A.; Pouget, A.; Rossant, C.; Roth, N.; Schaeffer, R.; Schartner, M.; Shi, Y.; Socha, K.; Steinmetz, N.; Svoboda, K.; Urai, A.; Wells, M.; West, S.; Whiteway, M.; Winter, O.; Witten, I.: A Brain-Wide Map of Neural Activity during Complex Behaviour. (submitted)

Menrath, D.; Woller, J.; Gharabaghi, A.: Real-Time Spatiotemporal Filtering for Artifact-Free EEG during Electrical Neurostimulation. (submitted)

Rangotis, R.; Nowakowska, S.; Dayan, P.; Parker, A.; Kakaei, E.; Akande, A.; Krug, K.: Distinct decision processes for 3D and motion stimuli in both humans and monkeys revealed by computational modelling. (submitted)

Binz, M.; Akata, E.; Bethge, M.; Brändle, F.; Callaway, F.; Coda-Forno, J.; Dayan, P.; Demircan, C.; Eckstein, M.; Éltetö, N. et al.; Griffiths, T.; Haridi, S.; Jagadish, A.; Ji-An; Kipnis, A.; Kumar, S.; Ludwig, T.; Mathony, M.; Mattar, M.; Modirshanechi, A.; Nath, S.; Peterson, J.; Rmus, M.; Russek, E.; Saanum, T.; Scharfenberg, N.; Schubert, J.; Schulze Buschoff, L.; Singhi, N.; Sui, X.; Thalmann, M.; Theis, F.; Truong, V.; Udandarao, V.; Voudouris, K.; Wilson, R.; Witte, K.; Wu, S.; Wulff, D.; Xiong, H.; Schulz, E.: Centaur: a foundation model of human cognition. (submitted)

Demircan, C.; Saanum, T.; Jagadish, A.; Binz, M.; Schulz, E.: Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models. (submitted)

Fazlali, F.; Lazar, R.; Yahya, F.; Stefani, O.; Spitschan, M.; Cajochen, C.: Sex and seasonal variations in melatonin suppression, and alerting response to light. (submitted)

Saanum, T.; Schulze Buschoff, L.; Dayan, P.; Schulz, E.: Next state prediction gives rise to entangled, yet compositional representations of objects. (submitted)

Wu, S.; Thalmann, M.; Dayan, P.; Akata, Z.; Schulz, E.: Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences. (submitted)

Barnby, J.; Nguyen, J.; Griem, J.; Wloszek, M.; Burgess, H.; Richards, L.; Kingston, J.; Cooper, G.; London Personality and Mood Disorders Consortium; Montague, P. et al.; Dayan, P.; Nolte, T.; Fonagy, P.: Self-Other Generalisation Shapes Social Interaction and Is Disrupted in Borderline Personality Disorder. (submitted)

Gruaz, L.; Modirshanechi, A.; Brea, J.: Merits of curiosity: a simulation study. (submitted)

Granwald, T.; Dayan, P.; Lengyel, M.; Guitart-Masip, M.: Bayesian Priors in Active Avoidance. (submitted)

Shen, T.; Dayan, P.: Risking your Tail: Modeling Individual Differences in Risk-sensitive Exploration using Conditional Value at Risk and Bayes Adaptive Markov Decision Processes. (submitted)

Vinogradov, O.; Giannakakis, E.; Buendía, V.; Uysal, B.; Ron, S.; Weinreb, E.; Schwarz, N.; Lerche, H.; Moses, E.; Levina, A.: Effective excitability captures network dynamics across development and phenotypes. (submitted)

Alon, N.; Schulz, L.; Barnby, J.; Rosenschein, J.; Dayan, P.: Detecting and Deterring Manipulation in a Cognitive Hierarchy. (submitted)

Woller, J.; Menrath, D.; Gharabaghi, A.: EEG denoising during transcutaneous auricular vagus nerve stimulation across simulated, phantom and human data. (submitted)

Kastner, D.; Williams, G.; Holobetz, C.; Romano, J.; Dayan, P.: The choice-wide behavioral association study: data-driven identification of interpretable behavioral components. (submitted)

Barnby, J.; Bellucci, G.; Alon, N.; Schilbach, L.; Frith, C.; Bell, V.: Beyond Theory of Mind: A formal interoperable framework for social inference and representation. (submitted)

Alon, N.; Schulz, L.; Bell, V.; Moutoussis, M.; Dayan, P.; Barnby, J.: Overly deep hierarchical mentalizing produces paranoia: a new formal theory. (submitted)

Fardet, T.; Giannakakis, E.; Paulun, K.; Levina, A.: Revising clustering and small-worldness in brain networks. (submitted)

Shen, T.; Dayan, P.: Risking your Tail: Curiosity, Danger and Exploration. (submitted)