In this second part of my discussion with Wolfgang (check out the first part), we talk about spiking neural networks in general, principles of brain computation he finds promising for implementing better network models, and we quickly overview some of his recent work on using these principles to build models with biologically plausible learning mechanisms, a spiking network analog of the well-known LSTM recurrent network, and meta-learning using reservoir computing.
Support the Show How does knowledge in the world get into our brains and integrated with the rest of our knowledge and memories? Anna...
Steve and I discuss his long and productive career as a theoretical neuroscientist. We cover his tried and true method of taking a large...
Matt and I discuss how cognition and behavior drifts over the course of minutes and hours, and how global brain activity drifts with it....
