Theme 4: Brain Networks and Neuronal Communication
Cognitive Computational Neuroscience
The Kietzmann lab aims to understand the computational processes by which the brain and artificial agents can efficiently and robustly derive meaning from the world
around us. We ask how the brain acquires versatile representations from the statistical regularities in the input, how sensory information is dynamically transformed in the cortical network, and which information is extracted by the brain to support higher-level cognition. To find answers to these questions, we develop and employ machine learning techniques to discover and model structure in high-dimensional neural data.
As a target modality, we focus on vision, the most dominant of our senses both neurally and perceptually. To gain insight into the intricate system that enables us to see, the group advances along two interconnected lines of research: machine learning for discovery in neuroscience, and deep neural network modelling. This interdisciplinary work combines machine learning, computational neuroscience, computer vision, and semantics. Our work is therefore at the heart of the emerging fields of neuro-inspired machine learning and cognitive computational neuroscience.”
| Contact | |
| Name: | Tim Kietzmann |
| Telephone: | 024-3612554 |
| Email: | t.kietzmann@donders.ru.nl |
| Visiting address: | Donders Centre for Cognition Thomas van Aquinostraat 4 6525 GD Nijmegen The Netherlands |
| Postal address: | Donders Centre for Cognition P.O. Box 9104 6500 HE Nijmegen The Netherlands |
Key publications
- Kietzmann, T.C., McClure, P., & Kriegeskorte, N. (2019). Deep neural networks in computational neuroscience. In Oxford Research Encyclopedia of Neuroscience. Oxford University Press.
- Mehrer, J., Spoerer, C.J., Jones, E.C., Kriegeskorte, N., & Kietzmann, T.C. (2021). An ecologically motivated image dataset for deep learning yields better models of human vision. Proceedings of the National Academy of Sciences, 118 (8), e2011417118; DOI: 10.1073/pnas.2011417118
- Kietzmann, T.C., Spoerer, C.J., Sörensen, L., Cichy, R.M., Hauk, O., & Kriegeskorte, N. (2019). Recurrence is required to capture the representational dynamics of the human visual system. Proceedings of the National Academy of Sciences, p. 1-10
- Mehrer, J., Spoerer, C. J., Kriegeskorte, N. & Kietzmann, T. C. (2020). Individual differences among deep neural network models. Nature Communications, 11(1), 5725. https://doi.org/10.1038/s41467-020-19632-w
Link Kietzmann lab
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Theme 4:
Natural Computing & Neurotechnology
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Research Group
Cognitive Computational Neuroscience
Principal Investigator
Dr. T.C. Kietzmann (Tim)
Group members
Postdocs
Adrien Doerig
Johannes Mehrer
Students
Emer Jones
Abdullahi Ali
Bas Krahmer
Philip Sulewski
Elgar de Groot
Daniel Anthes