Neuromorphic Tug-of-War: Balancing the Pull of Neuroscience and AI


Matteo Saponati | Eidgenössische Technische Hochschule Zürich, Switzerland
Laura Kriener | University of Bern, Switzerland
Melika Payvand | Eidgenössische Technische Hochschule Zürich, Switzerland
Benjamin Grewe | Eidgenössische Technische Hochschule Zürich, Switzerland


Historically, Artificial Intelligence (AI) research has been inspired by understanding how the brain works and emulating its functioning principles with artificial machines (Mead 1990). Yet, current breakthroughs in AI are driven by Machine Learning (ML) algorithms that show unbelievable performances with only minimal inspiration from actual biological networks. This success has nudged the field of Neuromorphic Computing towards ML principles, with increasing hesitation in implementing additional biological mechanisms in artificial learning systems. Nonetheless, this trend has been counterbalanced by groundbreaking discoveries in Neuroscience, indicating novel learning mechanisms that offer fast, parsimonious, and potentially powerful solutions for credit assignment. This tug-of-war between Neuroscience and AI has centered on two crucial questions: Which biological features provide promising solutions for hardware implementation, and which are merely incidental, resulting from their biological substrates? Conversely, what could Neuromorphic Computing gain by integrating knowledge from the ML community, regardless of its biological plausibility? This workshop will bring together researchers in Computational, System, and Cellular Neuroscience, Neuromorphic engineering, and ML to discuss these conflicting perspectives: (a) What are the recent Neuroscience breakthroughs in understanding learning and intelligence? Which ones have not been explored in artificial systems yet?, (b) What can we learn from the successes and failures of ML models? , and from a wider angle, (c) How much biological inspiration is needed for an artificial system to be “Neuromorphic”?

Schedule (CEST)

Sunday, Sep 29


Matteo Saponati and Laura Kriener | Eidgenössische Technische Hochschule Zürich, Switzerland, and University of Bern, Switzerland


Elisabetta Chicca | University of Groningen, Netherlands
Finding the gap: bio-inspired neuromorphic motion-vision in dense environments


Emre Neftci | Forschungszentrum Jülich, Germany
Online learning: the key ingredient of success from brains to transformers


First Open Discussion


Coffee break


Sara Hooker | Cohere for AI, USA


Konrad Kording | University of Pennsylvania, USA
It’s all about the gradients


Second Open Discussion


End of first day

Monday, Sep 30


Charlotte Frenkel | Delft University of Technology, Netherlands
Neuromorphic hardware and NeuroAI algorithm design: Bottom-up or top-down?


Dylan Muir | SynSense, Switzerland
You got AI in my Neuroscience! How I learned to stop worrying and love the gradients


Coffee break


Mihai Petrovici | University of Bern, Switzerland
Computation and learning in physical neuronal systems


Panayiota Poirazi| University of Bern, Switzerland
Dendrites empower learning in biological and artificial networks


Final Open Discussion and Closing Remarks