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.
Brain Inspired turns 100 (episodes) today! To celebrate, my patreon supporters helped me create a list of questions to ask my previous guests, many...
Support the show to get full episodes and join the Discord community. Eve discusses many of the lessons she has learned studying a small...
Show notes: Tony’s lab site, where there are links to his auditory decision making work and connectome work we discuss. Here are a few...
