Steve and I discuss his long and productive career as a theoretical neuroscientist. We cover his tried and true method of taking a large body of psychological behavioral findings, determining how they fit together and what’s paradoxical about them, developing design principles, theories, and models from that body of data, and using experimental neuroscience to inform and confirm his model predictions. We talk about his Adaptive Resonance Theory (ART) to describe how our brains are self-organizing, adaptive, and deal with changing environments. We also talk about his complementary computing paradigm to describe how two systems can complement each other to create emergent properties neither system can create on its own , how the resonant states in ART support consciousness, his place in the history of both neuroscience and AI, and quite a bit more.

Related:

• Steve's BU website.
• Some papers we discuss or mention (much more on his website):
  • Adaptive Resonance Theory: How a brain learns to consciously attend, learn, and recognize a changing world.
  • Towards solving the Hard Problem of Consciousness: The varieties of brain resonances and the conscious experiences that they support.
  • A Path Toward Explainable AI and Autonomous Adaptive Intelligence: Deep Learning, Adaptive Resonance, and Models of Perception, Emotion, and Action.

Topics Time stamps:

0:00 - Intro 5:48 - Skip Intro 9:42 - Beginnings 18:40 - Modeling method 44:05 - Physics vs. neuroscience 54:50 - Historical credit for Hopfield network 1:03:40 - Steve's upcoming book 1:08:24 - Being shy 1:11:21 - Stability plasticity dilemma 1:14:10 - Adaptive resonance theory 1:18:25 - ART matching rule 1:21:35 - Consciousness as resonance 1:29:15 - Complementary computing 1:38:58 - Vigilance to re-orient 1:54:58 - Deep learning vs. ART