Publikationen von SA Bruijns

Ecke, G.; Bruijns, S.; Hölscher, J.; Mikulasch, F.; Witschel, T.; Arrenberg, A.; Mallot, H.: Sparse coding predicts optic flow specificities of zebrafish pretectal neurons. Neural Computing and Applications 32 (11), S. 6745 - 6754 (2020)

Meding, K.; Bruijns, S.; Schölkopf, B.; Berens, P.; Wichmann, F.: Phenomenal Causality and Sensory Realism. i-Perception 11 (3), S. 1 - 16 (2020)

Bruijns, S.; Dayan, P.; The International Brain Laborartory: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.97, S. 770 - 772. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

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)

Bruijns, S.; Dayan, P.: Dissecting the Complexities of the Learning Curve With State-Based Models. In NeNa Conference 2023: Neurowissenschaftliche Nachwuchskonferenz (Conference of Junior Neuroscientists), T12, S. 25. 24th Conference of Junior Neuroscientists (NeNa 2023), Frankfurt a.M., Germany, 11. September 2023 - 13. September 2023. (2023)

Ecke, G.; Mikulasch, F.; Bruijns, S.; Witschel, T.; Arrenberg, A.; Mallot, H.: Sparse Coding Predicts Optic Flow Specificities of Zebrafish Pretectal Neurons. In 27th International Conference on Artificial Neural Networks (ICANN 2018). 27th International Conference on Artificial Neural Networks (ICANN 2018), Rhodos, Greece, 04. Oktober 2018 - 07. Oktober 2018. (2018)

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

Bruijns, S.; The International Brain Laboratory; Dayan, P.: Fear and anxiety influences on probabilistic learning: A pilot online study and computational modeling. 23rd Conference of Junior Neuroscientists (NeNa 2022), Bad Urach, Germany (2022)

Bonacchi, N.; Bruijns, S.; Chapuis, G.; Churchland, A.; Faulkner, M.; Lee, H.; Meijer, G.; Paninski, L.; Roth, N.; Steinmetz, N. et al.; Taheri, M.; West, S.; Winter, O.: Reproducibility of electrophysiological measurements during decision-making. 50th Annual Meeting of the Society for Neuroscience (Neuroscience 2021) (2021)

Bruijns, S.; Dayan, P.: Exploring learning trajectories with dynamic infinite hidden Markov models. 43rd Annual Conference of the Cognitive Science Society (CogSci 2021), Wien, Austria (2021)

Bruijns, S.; Dayan, P.: Anticipating Every Turn: Learning About Learning in Mice. 20th Conference of Junior Neuroscientists (NeNa 2019) , Schramberg, Germany (2019)

Bruijns, S.; Meding, K.; Schölkopf, B.; Wichman, F.: Phenomenal Causality and Sensory Realism. 42nd European Conference on Visual Perception (ECVP 2019), Leuven, Belgium (2019)

Mallot, H.; Ecke, G.; Mikulasch, F.; Bruijns, S.; Witschel, T.; Arrenberg, A.: Sparse coding predicts optic flow specificities of zebrafish pretectal neurons. 13th Göttingen Meeting of the German Neuroscience Society, 37th Göttingen Neurobiology Conference, Göttingen, Germany (2019)

Bruijns, S.; International Brain Laboratory; Bougrova, K.; Laranjeira, I.; Lau, P.; Meijer, G.; Miska, N.; Noel, J.-P.; Pan-Vazquez, A.; Roth, N. et al.; Socha, K.; Urai, A.; Dayan, P.: Dissecting the Complexities of Learning With Infinite Hidden Markov Models. (eingereicht)

Findling, C.; Hubert, F.; International Brain Lab; Acerbi, L.; Benson, B.; Benson, J.; Birman, D.; Bonacchi, N.; Bruijns, S.; Carandini, M. et al.; Catarino, J.; Chapuis, G.; Churchland, A.; Dan, Y.; Davatolhagh, F.; DeWitt, E.; Engel, T.; Fabbri, M.; Faulkner, M.; Fiete, I.; Freitas-Silva, L.; Gercek, B.; Harris, K.; Häusser, M.; Hofer, S.; Hu, F.; Huntenburg, J.; Khanal, A.; Krasniak, C.; Langdon, C.; Latham, P.; Lau, P.; Mainen, Z.; Meijer, G.; Miska, N.; Mrsic-Flogel, T.; Noel, J.-P.; Nylund, K.; Pan-Vazquez, A.; Paninski, L.; Pillow, J.; Rossant, C.; Roth, N.; Schaeffer, R.; Schartner, M.; Shi, Y.; Socha, K.; Steinmetz, N.; Svoboda, K.; Tessereau, C.; Urai, A.; Wells, M.; West, S.; Whiteway, M.; Winter, O.; Witten, I.; Zador, A.; Zhang, Y.; Dayan, P.; Pouget, A.: Brain-wide representations of prior information in mouse decision-making. (eingereicht)

International Brain Laboratory; Banga, K.; Benson, J.; Bonacchi, N.; Bruijns, S.; Campbell, R.; Chapuis, G.; Churchland, A.; Davatolhagh, M.; Lee, H. et al.; Faulkner, M.; Hu, F.; Huntenburg, J.; Khanal, A.; Krasniak, C.; Meijer, G.; Miska, N.; Mohammadi, Z.; Noel, J.-P.; Paninski, L.; Pan-Vazquez, A.; Roth, N.; Schartner, M.; Socha, K.; Steinmetz, N.; Taheri, M.; Urai, A.; Wells, M.; West, S.; Whiteway, M.; Winter, O.: Reproducibility of in-vivo electrophysiological measurements in mice. (eingereicht)