Karl Friston: Neuroscience and the Free Energy Principle | Lex Fridman Podcast #99

The following is a conversation with Karl Friston, one of the greatest neuroscientists in history, cited over 245,000 times, known for many influential ideas in brain imaging, neuroscience, and theoretical neurobiology, including especially the fascinating idea of the free energy principle for action and perception. Karl's mix of humor, brilliance, and kindness, to me, are inspiring and captivating. This was a huge honor and a pleasure. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcasts, support on Patreon, or simply connect with me on Twitter @Lex Fridman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now, and never any ads in the middle that can break the flow of a conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App allows you to send and receive money digitally, let me mention a surprising fact related to physical money. Of all the currency in the world, roughly 8% of it is actual physical money. The other 92% of money only exists digitally. So again, if you get Cash App from the App Store or Google Play and use the code LEXPODCAST, you get $10 and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now here's my conversation with Karl Friston. How much of the human brain do we understand from the low level of neuronal communication, to the functional level, to the, uh, to the highest level, maybe the, the psychiatric disorder level?

Well, we're certainly in a better position than we were last century. (laughs) How far we've got to go, I think is almost an unanswerable question. So you'd have to set the parameters, you know, what constitutes understanding, what level of understanding do you want? I think we've made enormous progress in terms of broad-brush principles. Um, whether that affords a detailed cartography of the functional anatomy of the brain and what it does, and right down to the microcircuitry in the neurons, tha- tha- that's probably, um, out of reach at the present time.

So the cartography, so mapping the brain, do you think mapping of the brain, the detailed perfect imaging of it, does that get us closer to understanding of the mind, o- of the brain? So how far does it get us if we have that perfect cartography of the brain?

I think there are lower bounds on that. It's a really interesting question. Um, you, i- and it would determine the sort of scientific career you'd pursue. If you believe that, uh, knowing every dendritic connection, every sort of microscopic synaptic structure right down to the molecular level was gonna give you the right kind of information to understand the computational anatomy, then you'd choose to be a microscopist and you would, um, uh, study little, you know, cubic millimeters of brain for the rest of your life. If, on the other hand, you were interested in holistic functions and, um, a sort of functional anatomy of the sort that a neuropsychologist would understand, you'd study brain lesions and strokes, you know, just looking at the whole person. So again, it comes back to, uh, what level do you want understanding? I think there are principled reasons not to go too far. Um, if you commit to a view of the brain as a machine that's performing a form of inference and representing things, um, there are th- that understanding, that level of understanding is necessarily cast in terms of probability densities and ensemble densities, distributions. And what that tells you is that you don't really want to look at the atoms to understand the thermodynamics of, of probabilistic descriptions for how the brain works. So I personally wouldn't look at the molecules, or indeed the single neurons. In the same way, if I wanted to u- understand the thermodynamics of some non-equilibrium steady state of a gas or an active material, I wouldn't spend my life looking at the, the individual molecules that constitute that ensemble. I'd look at their collective behavior. On the other hand, if you go too coarse-grain, you're gonna miss some basic canonical principles of connectivity and architectures. I'm thinking here, um, it's a bit colloquial, but there's current excitement about high-field magnetic resonance imaging at seven tesla. Why? Well, it gives us, for the first time, the opportunity to look at the brain in action at the level of a few millimeters that distinguish between different layers of the cortex that may be very important in terms of, um, uh, evincing generic principles of co- canonical microcircuitry that are replicated, uh, throughout the brain, that may tell us something fundamental about message passing in the brain and these density dynamics of, or neuronal ensemble population dynamics, uh, that underwrite our, you know, our brain function. So somewhere between a millimeter and a meter.