This week on the show: Are we ready to create digital models of the human brain?

Last month, Stanford researcher Andreas Tolias and colleagues created a "digital twin" of the mouse visual cortex. The researchers used the same foundation model approach that powers ChatGPT, but instead of training the model on text, the team trained in on brain activity recorded while mice watched action movies. The result? A digital model that can predict how neurons would respond to entirely new visual inputs.

This landmark study is a preview of the unprecedented research possibilities made possible by foundation models of the brain—models which replicate the fundamental algorithms of brain activity, but can be studied with complete control and replicated across hundreds of laboratories.

But it raises a profound question: Are we ready to create digital models of the human brain?

This week we talk with Wu Tsai Neuro Faculty Scholar Dan Yamins, who has been exploring just this question with a broad range of Stanford colleagues and collaborators. We talk about what such human brain simulations might look like, how they would work, and what they might teach us about the fundamental algorithms of perception and cognition.

Learn more

AI models of the brain could serve as 'digital twins' in research (Stanford Medicine, 2025)

An Advance in Brain Research That Was Once Considered Impossible (New York Times, 2025)

The co-evolution of neuroscience and AI (Wu Tsai Neuro, 2024)

Neuroscientists use AI to simulate how the brain makes sense of the visual world (Wu Tsai Neuro, 2024)

How Artificial Neural Networks Help Us Understand Neural Networks in the Human Brain (Stanford Institute for Human-Centered AI (HAI), 2021)

Related research

A Task-Optimized Neural Network Replicates Human Auditory Behavior... (PNAS, 2014)

Vector-based navigation using grid-like representations in artificial agents (Nature, 2018)

The neural architecture of language: Integrative modeling converges on predictive processing (PNAS, 2021)

Using deep reinforcement learning to reveal how the brain encodes abstract state-space representations... (Neuron, 2021)

We want to hear from your neurons! Email us at at neuronspodcast@stanford.edu.

Send us a text!

Thanks for listening! If you're enjoying our show, please take a moment to give us a review on your podcast app of choice and share this episode with your friends. That's how we grow as a show and bring the stories of the frontiers of neuroscience to a wider audience.

Learn more about the Wu Tsai Neurosciences Institute at Stanford and follow us on Twitter, Facebook, and LinkedIn.

If you spend any time chatting with a modern AI chatbot, you've probably been amazed at just how human it sounds, how much it feels like you're talking to a real person. Much ink has been spilled explaining how these systems are not actually conversing, not actually understanding — they're statistical algorithms trained to predict the next likely word.

But today on the show, let's flip our perspective on this. What if instead of thinking about how these algorithms are not like the human brain, we talked about how similar they are? What if we could use these large language models to help us understand how our own brains process language to extract meaning?

There's no one better positioned to take us through this than returning guest Laura Gwilliams, a faculty scholar at the Wu Tsai Neurosciences Institute and Stanford Data Science Institute, and a member of the department of psychology here at Stanford.

Learn more:

Gwilliams' Laboratory of Speech Neuroscience

Fireside chat on AI and Neuroscience at Wu Tsai Neuro's 2024 Symposium (video)

The co-evolution of neuroscience and AI (Wu Tsai Neuro, 2024)

How we understand each other (From Our Neurons to Yours, 2023)

Q&A: On the frontiers of speech science (Wu Tsai Neuro, 2023)

Computational Architecture of Speech Comprehension in the Human Brain (Annual Review of Linguistics, 2025)

Hierarchical dynamic coding coordinates speech comprehension in the human brain (PMC Preprint, 2025)

Behind the Scenes segment:

By re-creating neural pathway in dish, Sergiu Pasca's research may speed pain treatment (Stanford Medicine, 2025)

Bridging nature and nurture: The brain's flexible foundation from birth (Wu Tsai Neuro, 2025)

Get in touch

We want to hear from your neurons! Email us at at neuronspodcast@stanford.edu if you'd be willing to help out with some listener research, and we'll be in touch with some follow-up questions.

Episode Credits

This episode was produced by Michael Osborne at 14th Street Studios, with sound design by Morgan Honaker. Our logo is by Aimee Garza. The show is hosted by Nicholas Weiler at Stanford's

Send us a text!

Thanks for listening! If you're enjoying our show, please take a moment to give us a review on your podcast app of choice and share this episode with your friends. That's how we grow as a show and bring the stories of the frontiers of neuroscience to a wider audience.

Learn more about the Wu Tsai Neurosciences Institute at Stanford and follow us on Twitter, Facebook, and LinkedIn.

We've talked about glia and sleep. We've talked about glia and neuroinflammation. We've talked about glia in the brain fog that can accompany COVID or chemotherapy. We've talked about the brain's quiet majority of non–neuronal cells in so many different contexts that it felt like it was high time for us to take a step back and look at the bigger picture. After all, glia science was founded here at Stanford in the lab of the late, great Ben Barres.

No one is better suited to take us through this history and lead us to the frontiers of the field than today's guest, Brad Zuchero.

A former Barres lab postdoc, and now an emerging leader in this field in his own right, Brad gives us an overview of our growing understanding of the various different kinds of glia and their roles in brain function, and shares the exciting discoveries emerging from his lab — including growing evidence of a role for myelin in Alzheimers disease.

Learn More

• Neuroscientist Ben Barres, who identified crucial roles of glial cells, dies at 63 (Stanford Medicine, 2017)
• How exciting! Study reveals neurons rely on glial cells to become electrically excitable (Stanford Neurosurgery, 2024)
• Unlocking the secrets of myelin repair (Wu Tsai Neurosciences Institute, 2024)
• Q&A: Linking sleep, brain insulation, and neurological disease with postdoc Daniela Rojo (Knight Initiative for Brain Resilience, 2023)
• From angel to demon: Why some brain cells go ‘bad’ (Scope Blog, 2021)

Get in touch

We want to hear from your neurons! Email us at at neuronspodcast@stanford.edu if you'd be willing to help out with some listener research, and we'll be in touch with some follow-up questions.

Episode Credits

This episode was produced by Michael Osborne at 14th Street Studios, with production assistance by Morgan Honaker. Our logo is by Aimee Garza. The show is hosted by Nicholas Weiler at Stanford's Wu Tsai Neurosciences Institute and supported in part by the Knight Initiative for Brain Resilience at Wu Tsai Neuro.

Send us a text!

Thanks for listening! If you're enjoying our show, please take a moment to give us a review on your podcast app of choice and share this episode with your friends. That's how we grow as a show and bring the stories of the frontiers of neuroscience to a wider audience.

Learn more about the Wu Tsai Neurosciences Institute at Stanford and follow us on Twitter, Facebook, and LinkedIn.