This week on the show, we're have our sights set on healthy aging. What would it mean to be able to live to 80, 90 or 100 with our cognitive abilities intact and able to maintain an independent lifestyle right to the end of our days?

We're joined by Beth Mormino and Anthony Wagner who lead the Stanford Aging and Memory Study, which recruits cognitively healthy older adults to understand what makes their brains particularly resilient — and how more of us could join them in living the dream of healthy aging.

Learn More

• Stanford Aging and Memory Study (SAMS)
• Stanford Memory Lab
• Mormino Lab

Further Reading

• Alzheimer's 'resilience signature' predicts who will develop dementia—and how fast (Knight Initiative for Brain Resilience, 2025)
• Latest Alzheimer's lab tests focus on memory loss, not brain plaques (NPR, 2025)

References

• Trelle, A. N., ... & Wagner, A. D. (2020). Hippocampal and cortical mechanisms at retrieval explain variability in episodic remembering in older adults. eLife, 9:e55335. doi: 10.7554/eLife.55335 PDF | PMID:32469308
• Trelle, A. N., ..., Wagner, A. D., Mormino, E. C., & Wilson, E. N. (2025). Plasma Aβ42/Aβ40 is sensitive to early cerebral amyloid accumulation and predicts risk of cognitive decline across the Alzheimer’s disease spectrum. Alzheimer’s & Dementia, 21:e14442. PDF | PMID:39713875
• Sheng, J., ..., Mormino, E., & Wagner, A. D. (submitted). Top-down attention and Alzheimer's pathology impact cortical selectivity during learning, influencing episodic memory in older adults. Preprint

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 Wu Tsai Neurosciences Institute and supported in part by the Knight Iniative for Brain Resilience.

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 r

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.

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.