
In this first part of our conversation (here's the second part), Wolfgang and I discuss the state of theoretical and computational neuroscience, and how experimental results in neuroscience should guide theories and models to understand and explain how brains compute. We also discuss brain-machine interfaces, neuromorphics, and more. In the next part (here), we discuss principles of brain processing to inform and constrain theories of computations, and we briefly talk about some of his most recent work making spiking neural networks that incorporate some of these brain processing principles.
Support the show to get full episodes and join the Discord community. Henry and I discuss why he thinks neuroscience is in a crisis...
Randy and I discuss his LEABRA cognitive architecture that aims to simulate the human brain, plus his current theory about how a loop between...
Support the Podcast Andrew and I discuss his work exploring how various facets of deep networks contribute to their function, i.e. deep network theory....