Brain Inspired
A podcast by Paul Middlebrooks - Wednesdays
163 Episodes
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BI 222 Nikolay Kukushkin: Minds and Meaning from Nature’s Ideas
Published: 10/8/2025 -
BI 221 Ann Kennedy: Theory Beneath the Cortical Surface
Published: 9/24/2025 -
BI 220 Michael Breakspear and Mac Shine: Dynamic Systems from Neurons to Brains
Published: 9/10/2025 -
BI 219 Xaq Pitkow: Principles and Constraints of Cognition
Published: 8/27/2025 -
BI 218 Chris Rozell: Brain Stimulation and AI for Mental Disorders
Published: 8/13/2025 -
BI 217 Jennifer Prendki: Consciousness, Life, AI, and Quantum Physics
Published: 7/30/2025 -
BI 216 Woodrow Shew and Keith Hengen: The Nature of Brain Criticality
Published: 7/16/2025 -
BI 215 Xiao-Jing Wang: Theoretical Neuroscience Comes of Age
Published: 7/2/2025 -
BI 214 Nicole Rust: How To Actually Fix Brains and Minds
Published: 6/18/2025 -
BI 213 Representations in Minds and Brains
Published: 6/4/2025 -
BI 212 John Beggs: Why Brains Seek the Edge of Chaos
Published: 5/21/2025 -
BI 211 COGITATE: Testing Theories of Consciousness
Published: 5/7/2025 -
BI 210 Dean Buonomano: Consciousness, Time, and Organotypic Dynamics
Published: 4/22/2025 -
BI 209 Aran Nayebi: The NeuroAI Turing Test
Published: 4/9/2025 -
BI 208 Gabriele Scheler: From Verbal Thought to Neuron Computation
Published: 3/26/2025 -
BI 207 Alison Preston: Schemas in our Brains and Minds
Published: 3/12/2025 -
Quick Announcement: Complexity Group
Published: 3/5/2025 -
BI 206 Ciara Greene: Memories Are Useful, Not Accurate
Published: 2/26/2025 -
BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think
Published: 2/12/2025 -
BI 204 David Robbe: Your Brain Doesn’t Measure Time
Published: 1/29/2025
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.