People

Henning Sprekeler

Principal Investigator

Computational Neuroscience

TU Berlin

 

Email:
h.sprekeler@tu-berlin.de

Phone: +49 30 314 24390

 

Photo: SCIoI

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Henning Sprekeler

Henning Sprekeler

Photo: SCIoI

Henning Sprekeler is Bernstein Professor of Modeling of Cognitive Processes. For SCIoI, he represents the analytical discipline computational neuroscience. He has extensive expertise in computational modelling of synaptic plasticity and its consequences for behavioural learning and the formation of memories. He has also worked on the self-organised development of high-level sensory representations, an essential prerequisite for intelligent behaviour.


Projects

Henning Sprekeler is member of Project 03, Project 12, Project 13, Project 25, Project 33, Project 40, Project 58.


Oksuz, H. Y., Molinari, F., Sprekeler, H., & Raisch, J. (2024). Boosting Fairness and Robustness in Over-the-Air Federated Learning. IEEE Control Systems Letters (LCSS), 8, 682–687. https://doi.org/10.1109/lcsys.2024.3402123
Hohlbaum, K., Andresen, N., Mieske, P., Kahnau, P., Lang, B., Diederich, K., Palme, R., Mundhenk, L., Sprekeler, H., Hellwich, O., Thöne-Reineke, C., & Lewejohann, L. (2024). Lockbox enrichment facilitates manipulative and cognitive activities for mice. Open Research Europe. https://doi.org/10.12688/openreseurope.17624.2
Boon, M. N., Andresen, N., Traverso, S., Meier, S., Schuessle, F., Hellwich, O., Lewejohann, L., Thöne-Reineke, C., Sprekeler, H., & Hohlbaum, K. (2024). Mechanical problem solving in mice. bioRxiv. https://doi.org/10.1101/2024.07.29.605658
Lukas, J., Krause, J., Träger, A. S., Piotrowski, J. M., Romanczuk, P., Sprekeler, H., Arias-Rodriguez, L., Krause, S., Schutz, C., & Bierbach, D. (2023). Multispecies collective waving behaviour in fish. Philosophical Transactions of the Royal Society B. https://doi.org/10.1098/rstb.2022.0069
Gómez-Nava, L., Lange, R. T., Klamser, P. P., Lukas, J., Arias-Rodriguez, L., Bierbach, D., Krause, J., Sprekeler, H., & Romanczuk, P. (2023). Fish shoals resemble a stochastic excitable system driven by environmental perturbations. Nature Physics. https://doi.org/10.1038/s41567-022-01916-1
Boon, M. N., Andresen, N., Meier, S., Hellwich, O., Lewejohann, L., Thöne-Reineke, C., Sprekeler, H., & Hohlbaum, K. (2023). Mouse lock box: a sequential mechanical decision-making task to investigate complex mouse behavior. Bernstein Conference. https://doi.org/10.12751/nncn.bc2023.056
Oksuz, H. Y., Molinari, F., Sprekeler, H., & Raisch, J. (2023). Federated Learning in Wireless Networks via Over-the-Air Computations. 62nd IEEE Conference on Decision and Control (CDC), 4379–4386. https://doi.org/10.1109/CDC49753.2023.10384001
Vischer, M., Lange, R., & Sprekeler, H. (2022). On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. ICLR 2022. https://doi.org/10.48550/arXiv.2105.01648
Lange, R., & Sprekeler, H. (2022). Learning not to learn: Nature versus Nurture in Silico. AAAI 2022. https://doi.org/10.48550/arXiv.2010.04466

Research

An overview of our scientific work

See our Research Projects