All Episodes
BI 217 Jennifer Prendki: Consciousness, Life, AI, and Quantum Physics
Do AI engineers need to emulate some processes and features found only in living organisms at the moment, like how brains are inextricably integrated with bodies? Is consciousness necessary for AI entities if we want them to play nice with us?
BI 216 Woodrow Shew and Keith Hengen: The Nature of Brain Criticality
Woodrow Shew and Keith Hengen on critical brain dynamics and cognition, learning, and development.
BI 215 Xiao-Jing Wang: Theoretical Neuroscience Comes of Age
Xiao-Jing was born and grew up in China, spent 8 years in Belgium studying theoretical physics like nonlinear dynamical systems and deterministic chaos.
BI 214 Nicole Rust: How To Actually Fix Brains and Minds
Elusive Cures: Why Neuroscience Hasn’t Solved Brain Disorders―and How We Can Change That. Nicole Rust runs the Visual Memory laboratory at UPenn, University of Pennsylvania. Her interests have expanded now to include mood and feelings, as you’ll hear. And she wrote this book, which contains a plethora of ideas about how we can pave a way forward in neuroscience to help treat mental and brain disorders. We talk about a small plethora of those ideas from her book. which also contains the story partially which will hear of her own journey in thinking about these things from working early on in visual neuroscience to where she is now.
BI 213 Representations in Minds and Brains
What do neuroscientists mean when they use the term representation? That’s part of what Luis Favela and Edouard Machery set out to answer a couple years ago by surveying lots of folks in the cognitive sciences, and they concluded that as a field the term is used in a confused and unclear way.
BI 212 John Beggs: Why Brains Seek the Edge of Chaos
You may have heard of the critical brain hypothesis. It goes something like this: brain activity operates near a dynamical regime called criticality, poised at the sweet spot between too much order and too much chaos, and this is a good thing because systems at criticality are optimized for computing, they maximize information transfer, they maximize the time range over which they operate, and a handful of other good properties.
BI 211 COGITATE: Testing Theories of Consciousness
Rony Hirschhorn, Alex Lepauvre, and Oscar Ferrante on testing integrated information and global neuronal workspace theories of consciousness.
BI 210 Dean Buonomano: Consciousness, Time, and Organotypic Dynamics
Dean Buonomano on time in neuroscience vs. physics, integrated information theory, testing timing dynamics in organotypic brain slices, and how AI doesn’t need neuroscience to continue to progress.
BI 209 Aran Nayebi: The NeuroAI Turing Test
Aran Nayebi on NeuroAgents, reverse-engineering brains to build autonomous agents, and an update to the Turing test for NeuroAI.
BI 208 Gabriele Scheler: From Verbal Thought to Neuron Computation
Gabriele Scheler co-founded the Carl Correns Foundation for Mathematical Biology. In fact, Carl Correns was her great grandfather, one of the early pioneers in genetics. Gabriele is a computational neuroscientist, whose goal is to build models of cellular computation, and much of her focus is on neurons.
BI 207 Alison Preston: Schemas in our Brains and Minds
Ali Preston on how the neuroscience of schemas, which help us form memories, integrate and differentiate information, and make predictions.
Quick Announcement: Complexity Group
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BI 206 Ciara Greene: Memories Are Useful, Not Accurate
Ciara Greene discusses how human episodic memory works, and why our common assumptions about the role of memory
BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think
Dmitri Chklovskii believes all your neurons are smart controller agents, and understanding this will transform neuroscience and how we build artificial intelligence.
BI 204 David Robbe: Your Brain Doesn’t Measure Time
My guest today, neuroscientist David Robbe, believes we don’t rely on clocks in our brains, or measure time internally, or really that we measure time at all. Rather, our estimation of time emerges through our interactions with the world around us and/or the world within us as we behave.
BI 203 David Krakauer: How To Think Like a Complexity Scientist
David Krakauer is the president of the Santa Fe Institute, where their mission is officially “Searching for Order in the Complexity of Evolving Worlds.” When I think of the Santa Fe institute, I think of complexity science, because that is the common thread across the many subjects people study at SFI, like societies, economies, brains, machines, and evolution. David has been on before, and I invited him back to discuss some of the topics in his new book The Complex World: An Introduction to the Fundamentals of Complexity Science.
BI 202 Eli Sennesh: Divide-and-Conquer to Predict
Eli Sennesh on bridging predictive coding and NeuroAI
BI 201 Rajesh Rao: From Predictive Coding to Brain Co-Processors
Rajesh Rao shares his updated theory on how the cortex could implement active predictive coding. Predictive coding shares theoretical roots with predictive processing, the bayesian brain, active inference, and the free energy principle, all of which are general theories of brain function.