Learning serves behavioural adaptation. Central dogma in neuroscience is that persistent modifications at the local level of single neurons and synapses underlie behavioural changes. In this workshop we are particularly interested in local modifications that depend on behavioural success or failure thereby going beyond the mechanisms of pure self-organization. We will therefore focus on the origin and the interactions of more global signals with local synaptic and neuronal adaptation mechanisms and discuss corresponding models which contribute to our understanding of behavioural adaptations and their failures.

Recent advances on experimental techniques for studying synaptic and neuronal adaptation have boosted our knowledge about these processes. On the one hand side, they have revealed a variety of intriguing local plasticity mechanisms as, for example, STDP, synaptic tagging, retro-axonal signals, and spine dynamics whose potential relevance for learning is subject to intense research. On the other hand side, theoretical approaches to learning in closed loop situations often require quite specific processes as e.g. exploration, control of reward signals and control of fluctuation amplitudes, whose relation to the local mechanisms is often not well established. The goal of our workshop is to bring together scientists from theory and experiment to exchange the newest results, ideas, and concepts on the neurobiological underpinnings of learning. Ideally our meeting will open new directions for theoretical investigations based on the presented experimental findings. Also we imagine progress in formulating unifying theoretical frameworks for learning that may foster novel experimental approaches for their testing.

Learning serves behavioural adaptation. Central dogma in neuroscience is that persistent modifications at the local level of single neurons and synapses underlie behavioural changes. In this workshop we are particularly interested in local modifications that depend on behavioural success or failure thereby going beyond the mechanisms of pure self-organization. We will therefore focus on the origin and the interactions of more global signals with local synaptic and neuronal adaptation mechanisms and discuss corresponding models which contribute to our understanding of behavioural adaptations and their failures.

Recent advances on experimental techniques for studying synaptic and neuronal adaptation have boosted our knowledge about these processes. On the one hand side, they have revealed a variety of intriguing local plasticity mechanisms as, for example, STDP, synaptic tagging, retro-axonal signals, and spine dynamics whose potential relevance for learning is subject to intense research. On the other hand side, theoretical approaches to learning in closed loop situations often require quite specific processes as e.g. exploration, control of reward signals and control of fluctuation amplitudes, whose relation to the local mechanisms is often not well established. The goal of our workshop is to bring together scientists from theory and experiment to exchange the newest results, ideas, and concepts on the neurobiological underpinnings of learning. Ideally our meeting will open new directions for theoretical investigations based on the presented experimental findings. Also we imagine progress in formulating unifying theoretical frameworks for learning that may foster novel experimental approaches for their testing.

• Michael S. Brainard, UC San Francisco
• Dominique Debanne, Faculté de Medecine, Marseille
• Hubert Dinse, Ruhr Universität Bochum
• Wulfram Gerstner, EPFL, Lausanne
• Richard Hahnloser, University of Zürich
• Kenneth D. Harris, Rutgers University New Jersey
• Peter Jonas, Freiburg Institute for Advanced Studies
• Yonatan Loewenstein, The Hebrew University Jersusalem
• Wolfgang Maass, TU Graz
• Filip Ponulak, Brain Corporation, San Diego
• Alexander Roxin, Institut d'Investigacions Biomédiques
  August Pi I Sunyer, Barcelona
• Dov Sagi, Weizmann Institute of Science, Rehovot
• Walter Senn, Institute for Physiology, Bern
• Henning Sprekeler, EPFL, Lausanne
• Misha Tsodyks, Weizmann Institute of Science, Rehovot
• Mark van Rossum, University of Edinburgh
• Florentin Wörgötter, University Göttingen

<link fileadmin dateien tagungen computational_aspects_of_learning programm_aktuell.pdf download>Download program

<link fileadmin dateien tagungen computational_aspects_of_learning programm_aktuell.pdf download>Download program

• Michael S. Brainard, UC San Francisco
• Dominique Debanne, Faculté de Medecine, Marseille
• Hubert Dinse, Ruhr Universität Bochum
• Wulfram Gerstner, EPFL, Lausanne
• Richard Hahnloser, University of Zürich
• Kenneth D. Harris, Rutgers University New Jersey
• Peter Jonas, Freiburg Institute for Advanced Studies
• Yonatan Loewenstein, The Hebrew University Jersusalem
• Wolfgang Maass, TU Graz
• Filip Ponulak, Brain Corporation, San Diego
• Alexander Roxin, Institut d'Investigacions Biomédiques
  August Pi I Sunyer, Barcelona
• Dov Sagi, Weizmann Institute of Science, Rehovot
• Walter Senn, Institute for Physiology, Bern
• Henning Sprekeler, EPFL, Lausanne
• Misha Tsodyks, Weizmann Institute of Science, Rehovot
• Mark van Rossum, University Edinburgh
• Florentin Wörgötter, University Göttingen