BI 115 Steve Grossberg: Conscious Mind, Resonant Brain

Support the show to get full episodes, full archive, and join the Discord community. Steve and I discuss his book Conscious Mind, Resonant Brain: How Each Brain Makes a Mind.  The book is a huge collection of his models and their predictions and explanations for a wide array of cognitive brain functions. Many of the models spring from his Adaptive Resonance Theory (ART) framework, which explains how networks of neurons deal with changing environments while maintaining self-organization and retaining learned knowledge. ART led Steve to the hypothesis that all conscious states are resonant states, which we discuss. There are also guest questions from György Buzsáki, Jay McClelland, and John Krakauer. Steve's BU website.Conscious Mind, Resonant Brain: How Each Brain Makes a MindPrevious Brain Inspired episode:BI 082 Steve Grossberg: Adaptive Resonance Theory 0:00 - Intro 2:38 - Conscious Mind, Resonant Brain 11:49 - Theoretical method 15:54 - ART, learning, and consciousness 22:58 - Conscious vs. unconscious resonance 26:56 - Györy Buzsáki question 30:04 - Remaining mysteries in visual system 35:16 - John Krakauer question 39:12 - Jay McClelland question 51:34 - Any missing principles to explain human cognition? 1:00:16 - Importance of an early good career start 1:06:50 - Has modeling training caught up to experiment training? 1:17:12 - Universal development code

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Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.