Despite huge advances in artificial intelligence (AI), the mammalian brain is still unrivaled in terms of sustainability and speed of learning, and robustness in inference. One central goal of AI research is to build intelligent systems that exceed the capabilities of biological brains. However, to date we know very little about how computations in neuronal circuits give rise to biological intelligence.
Our group uses AI both as a testbed and a tool on large scale neuro-physiological and -anatomical data to better understand the constituent elements of neuronal intelligence. We are inspired by the idea that a deeper understanding of computational motifs in cortical circuits can help build the next generation of intelligent systems.
We are based at the University Tübingen as part of the Cybervalley initiative. We closely collaborate with experimental and computational neuroscientists to develop new tools and experimental paradigms to discover principles of biological intelligence.
Upcoming Talks and Presentations
Our paper Factorized Neural Processes for Neural Processes: K-Shot Prediction of Neural Responses got accepted to NeurIPS 2020. Joint work with James R. Cotton and Andreas Tolias.
Arne and Mohammad got accepted to the interactive track of the NeuroMatch Academy 2020. Congrats!
Our paper Simultaneous spike-time locking to multiple frequencies got accepted to Journal of Neurophysiology. Joint work with Carolin Sachgau, Jörg Henninger, Jan Benda, and Jan Grewe.
Cathryn Cadwell’s (Tolias lab) paper on “Cell type composition and circuit organization of clonally related excitatory neurons in the juvenile mouse neocortex” got accepted to eLife. Collaboration with Tolias Lab.
Jörg Henninger’s (Benda lab) paper on “Tracking activity patterns of a multispecies community of gymnotiform weakly electric fish in their neotropical habitat without tagging” got accepted to Journal of Experimental Biology. Collaboration with Benda lab.
Ivan’s paper on “Rotation-invariant clutering of neuronal responses in primary visual cortex” got accepted as a talk to ICLR 2020. Collaboration with Alex Ecker and Matthias Bethge lab.
Our perspective paper Engineering a less artificial intelligence got published in Neuron.
- Tolias Lab (Baylor College of Medicine, Rice University)
- Alex Ecker (University Göttingen)
- Jan Grewe (Neuroethology) (University Tübingen)
- Xaq Pitkow (Baylor College of Medicine, Rice University)
- Aristides Arrenberg (University Tübingen)
- Thomas Gasser (Hertie Institute for Clinical Brain Science)
- Holger Lerche (Hertie Institute for Clinical Brain Science)
- Hendrikje Nienborg (Centre for Intergrative Neuroscience; University Tübingen)