| http://www.w3.org/ns/prov#value | - This thesis investigates synaptic plasticity and learning in neural networks with the help of datadriven, i.e. ???bottom-up???, and theory-driven, i.e. ???top-down???, models and focuses in particular on the implications of their distributed architecture and spike-based communication for learning.
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