Understanding Local Third Factors in Synaptic Plasticity: Mechanisms and Functional Implications

Organizers

Andreas Schneider | University of Göttingen, Germany
Fabian Mikulasch | Max Planck Institute for Dynamics and Self-Organization, Germany
Viola Priesemann | Max Planck Institute for Dynamics and Self-Organization, Germany

Abstract

Synaptic plasticity, the cornerstone of learning and memory, traditionally emphasizes the interplay of pre- and post-synaptic activity. However, recent research highlights the crucial role of “third factors” in shaping this process. These factors, distinct from pre- and post-synaptic activity, can be broadly categorized as “global” (e.g., dopaminergic reward signals) or “local” (e.g., postsynaptic membrane potential, or glial influence). While the importance of global third factors is well-established, the mechanisms and functional implications of local third factors remain largely unexplored. This workshop delves into this exciting frontier, exploring the intricate interplay between mechanisms and functions of local third factors in learning. We will bring together experts in biological learning, bio-inspired AI, and neuromorphic computing for a comprehensive discussion on key open questions. These questions encompass the biophysical underpinnings of local third factors, their impact on synaptic plasticity at the cellular and molecular level, and how they contribute to shaping network function and information processing across various brain regions. The workshop will conclude by discussing in which brain regions and in which learning tasks local third factors play a crucial role.

Schedule (CEST)

Sunday, Sep 29

14:00

Viola Priesemann | Max Planck Institute for Dynamics and Self-Organization, Germany
Introduction

14:30

Friedemann Zenke | Friedrich Miescher Institute for Biomedical Research, Switzerland
Local learning algorithms for spiking and physical neural networks

15:00

Melika Payvand | University of Zurich and Eidgenössische Technische Hochschule Zürich, Switzerland
Analog substrates for physics-based online learning on chip

15:30

Kevin Max | University of Bern, Switzerland
Biological deep learning with three-component rules

16:00

Coffee break

16:30

Tim Vogels (TBC) | Institute of Science and Technology Austria, Austria
TBA

17:00

Ariane Delrocq | École Polytechnique Fédérale de Lausanne, Switzerland
A predictive third factor in a visual cortex model

17:30

Charlotte Frenkel | Delft University of Technology, Netherlands
Locality in space and time is key for neuromorphic hardware to learn efficiently with three-factor rules

18:00

Pau Vilimelis Aceituno | University of Zurich, Switzerland
From synaptic calcium to hierarchical learning, or some preliminary experimental evidence against backpropagation of error in cortex

18:30

End of first day

Monday, Sep 30

08:30

Wulfram Gerstner | University of Zurich, Switzerland
Surprise extracted from spiking activity as a third factor: a model

09:00

Alice Dauphin | Graz University of Technology, Austria
From connectivity to functionality: disinhibition and synaptic plasticity in cortical microcircuits

09:30

Anna Levina | University of Tübingen, Germany
Structural network features and their impact on effectiveness of plasticity

10:00

Coffee break

10:30

Claudia Clopath | Imperial College London, UK
Latent representations in hippocampal formed by three-factor learning

11:00

Julijana Gjorgjieva | Technical University of Munich, Germany
TBA

11:30

Katharina Wilmes University of Bern, Switzerland
TBA

12:00

Andreas Schneider and Fabian Mikulasch | University of Göttingen, Germany, and Max Planck Institute for Dynamics and Self-Organization, Germany
Panel discussion

12:30

End