All Episodes
BI 235 Romain Brette: The Brain, in Theory
rains encode information in representations that perform computations to make predictions, right? No, no, no, and no. That’s Romain Brette’s response to those ill-conceived notions that neuroscience relies on to try to explain how cognition works. He uses more words to do that in his new book, The Brain, in Theory, which we discuss today.
BI 234 Juan Gallego: The Neural Manifold Manifesto
Should we think of our brains as collections of neural population manifolds? Gallego suggests a wealth of evidence supports the view that neural manifolds are real and useful, even if they may not completely solve the age-old mind-body problem.
BI 233 Tom Griffiths: The Laws of Thought
Tom Griffiths on how neural networks, logic, and probability theory weave together to explain cognition.
BI 232 How Should Neuroscience Integrate with Ecological Psychology?
Three ecological psychologists on the right and wrong ways to use ecological psychology principles in neuroscience.
Luis Favela, Vicente Raja, and Mattheu de Wit weigh in on the recent trend of neuroscientists importing concepts from ecological psychology, and how assumptions in neuroscience may gloss over critical principles underlying ecological psychology.
BI 231 Jaan Aru: Conscious AI? Not Even Close!
Jaan Aru on why AI is nowhere near having consciousness, and how neuroscience might enlighten how consciousness comes about.
BI 230 Michael Shadlen: How Thoughts Become Conscious
Michael is with me today to discuss his account of what makes a thought conscious, in the hopes to inspire neuroscience research to eventually tackle the hard problem of consciousness – why and how we have subjective experience.
BI 229 Tomaso Poggio: Principles of Intelligence and Learning
Tomaso believes we are in-between building and understanding useful AI That is, we are in between engineering and theory. He likens this stage to the period after Volta invented the battery and Maxwell developed the equations of electromagnetism. Tomaso has worked for decades on the theory and principles behind intelligence and learning in brains and machines.
BI 228 Alex Maier: Laws of Consciousness
Alex Maier on why consciousness science needs mathematical formalization – in particular, a structuralist approach like that in integrated information theory
BI 227 Decoding Memories: Aspirational Neuroscience 2025
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BI 226 Tatiana Engel: The High and Low Dimensional Brain
Tatiana Engel on learning how low-dimensional function is embedded in high-dimensional networks, and timescales across the brain.
BI 225 Henk De Regt: Understanding in Machines and Humans
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BI 224 Dan Nicholson: Schrödinger’s What is Life? Revisited
Erwin Schrödinger’s What Is Life is a famous book that people point to as having predicted DNA and influenced and inspired many well-known biologists ushering in the molecular biology revolution. But Schrödinger was a physicist, not a biologist, and he spent very little time and effort toward understanding biology.
BI 223 Vicente Raja: Ecological Psychology Motifs in Neuroscience
Raja discusses his philosophical and scientific work assessing how concepts from ecological psychology might elucidate the brain’s role in perception and action, within the context of our inextricable embodiment and interaction with the environment. They also discuss Raja’s term “motif” to describe how a single term can enable scientific progress even when researchers use different definitions for the same words, and the ongoing research studying the nature of plant behavior.
BI 222 Nikolay Kukushkin: Minds and Meaning from Nature’s Ideas
This book is about essences across spatial scales in nature. More precisely, it’s about giving names to what is fundamental, or essential, to how things and processes function in nature. Niko argues those essences are where meaning resides.
BI 221 Ann Kennedy: Theory Beneath the Cortical Surface
Ann Kennedy is Associate Professor at Scripps Research Institute and runs the Laboratory for Theoretical Neuroscience and Behavior.
BI 220 Michael Breakspear and Mac Shine: Dynamic Systems from Neurons to Brains
What changes and what stays the same as you scale from single neurons up to local populations of neurons up to whole brains? How tuning parameters like the gain in some neural populations affects the dynamical and computational properties of the rest of the system.
BI 219 Xaq Pitkow: Principles and Constraints of Cognition
Xaq Pitkow shares his principles to study cognition in our imperfect brains and bodies, and how AI and machine learning are contributing to our efforts to understand brains and minds.
BI 218 Chris Rozell: Brain Stimulation and AI for Mental Disorders
We are in an exciting time in the cross-fertilization of the neurotech industry and the cognitive sciences. My guest today is Chris Rozell, who sits in that space that connects neurotech and brain research. Chris runs the Structured Information for Precision Neuroengineering Lab at Georgia Tech University, and he was just named the inaugural director of Georgia Tech’s Institute for Neuroscience, Neurotechnology, and Society.