Duke Computational and Theoretical Neuroscience Group welcomes Wulfram Gerstner, Chair for Computational Neuroscience at the Swiss Federal Institute of Technology in Lausanne (EPFL), for his Zoom seminar "Neo-Hebbian three-factor rules of synaptic plasticity, eligibility traces and surprise."
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Abstract: Hebbbian learning has been the dominant paradigm of synaptic plasticity. Hebbian learning works with two factors, i.e., a combination of presynaptic spike arrivals with postsynaptic activation. In a more general theory, Hebbian learning just sets an eligibility trace and marks the synapse as being ready for change, but a third factor is needed to turn the potential plasticity into an actual change of synaptic weight. In this talk I discuss experimental and theoretical evidence supporting such a framework: In biology, the third factor could be provided by broadly projecting neuromodulators. In models, the third factor could be not just moments of reward, but also moments of surprise.