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Zhaoping, L.: The Esd Framework For Understanding Vision. Living Machines: 9. International Conference on biomimetic und biohybrid Systems (2020)

Dayan, P.: Machine learning for Computational Neuroscience. Machine Learning Summer School (MLSS 2020), Tübingen, Germany (2020)

Logothetis, N.: Interaction of hippocampal ripples: Theta oscillations and Pontine-Geniculo-Occipital waves leading to brainwide metastates related to learning and memory consolidation. Neuroscience School of Advanced Studies: Neural Circuit Dynamics, Venezia, Italy (2020)

Kapoor, V.: Decoding the Contents of Conscious Perception from Neural Activity in the Prefrontal Cortex During a No Report Binocular Rivalry Paradigm. Third Meeting of Consciousness Research Network (CoRN 2020), Shanghai, China (submitted)

Dayan, P.: All Models Are Wronged. Gordon Research Conference: Functions of the Basal Ganglia from Thought to Action , Ventura, CA, USA (2020)

Gambino, T.: In vivo evaluation of calcium-responsive MRI probes. Université de Bordeaux: Institut de Bio-Imagerie, Bordeaux, France (2020)

Schulz, E.: Using Structure to Explore Efficiently. 27th Annual Meeting of the Cognitive Neuroscience Society (CNS 2020), Boston, MA, USA (2020)

Kumar, V.: Structural and Functional Anatomy of the Human Thalamus. University of California: BMC Seminar, Los Angeles, CA, USA (2020)

Logothetis, N.: Multidisciplinary Approaches for the Study of Self-Organization Principles in the Primate Brain. University of Copenhagen: Department of Neuroscience, Copenhagen, Denmark (2020)

Dayan, P.: Neural Reinforcement Learning. Forschungskolloquium 2020 der Medizinischen Fakultät, Tübingen, Germany (2020)

Robson, D.; Li, J.: Internal state dynamics shape brain-wide activity and foraging behavior. Neurobiological Monday Colloquium: Eberhard-Karls-Universität, Tübingen, Germany (2020)

Dayan, P.: Savouring and its Modulation by Prediction Errors. Central European University, Budapest, Hungary (2019)

Dayan, P.; Iigaya, K.; Hauser, T.; Kurth-Nelson, Z.; O'Doherty, J.; Dolan, R.: Savouring and its Modulation by Prediction Errors. Departmental Colloquium Max Planck for Biological Cybernetics, Tübingen, Germany (2019)

Dinkel, H.: Introduction of Linear motifs. EMBO Practical Course: Computational analysis of protein-protein interactions in cell function and disease, Bangalore, India (2019)

Dinkel, H.; Gibson, T.; Kumar, M.: Linear motif biology and prediction, cooperativity in cellular signaling (I). EMBO Practical Course: Computational analysis of protein-protein interactions in cell function and disease, Bangalore, India (2019)

Higgins, I.; Konkle, T.; Bethge, M.: What sorts of cognitive or biological (architectural) inductive biases will be crucial for developing effective artificial intelligence? NeurIPS 2019 Workshop: Shared Visual Representations in Human and Machine Intelligence, Vancouver, BC, Canada (2019)

Kumar, M.; Dinkel, H.; Gibson, T.: Linear motif biology and prediction, cooperativity in cellular signaling (II). EMBO Practical Course: Computational analysis of protein-protein interactions in cell function and disease, Bangalore, India (2019)

Safavi, S.; Logothetis, N.; Besserve, M.: Multivariate coupling estimation between continuous signals and point processes. NeurIPS 2019 Workshop: Learning with Temporal Point Processes, Vancouver, Canada (2019)

Sharan, M.; Dinkel, H.: Using informal meetings for building local (bioinformatics) communities. EMBO Practical Course: Computational analysis of protein-protein interactions in cell function and disease, Bangalore, India (2019)

Dayan, P.: Replay and Preplay in Human Planning. Université de Genève: C. Lüscher Synapses, Circuits and Behaviour in Addiction and Related Disorders, Genève, Switzerland (2019)