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.

• Wolfgang's website.
• The book Wolfgang recommends:
  • The Brain from Inside Out by György Buzsáki.
• Papers we discuss or mention:
  • Searching for principles of brain computation.
  • Brain Computation: A Computer Science Perspective.
  • Long short-term memory and learning-to-learn in networks of spiking neurons.
  • A solution to the learning dilemma for recurrent networks of spiking neurons.
  • Reservoirs learn to learn.
• Talks that cover some of these topics:
  • Computation in Networks of Neurons in the Brain I.
  • Computation in Networks of Neurons in the Brain II.