From Our Neurons to Yours

In this episode, we explore the fascinating neuroscience behind how children learn to read with Bruce McCandliss, director of the Stanford Educational Neuroscience Initiative.Key topics include:• How our brains "recycle" visual and language circuits to create reading expertise• The crucial threshold when reading shifts from effortful to automatic• Why some children struggle more than others to develop reading fluency• How teachers can tailor instruction to help struggling readers• The profound ways literacy reshapes our brains and cognitionJoin us  for a mind-expanding look at one of humanity's most transformative technologies - written language - and how mastering it quite literally changes our brains.Learn MoreLearn about the Stanford Educational Neuroscience Initiative at Stanford's Graduate School of EducationLearn about Palo Alto Synapse School's "brainwave learning center"Watch McCandliss present his work at Wu Tsai Neuro's 10th anniversary SymposiumRecent Academic Articles & News CoverageTan LH, Perfetti CA, Ziegler JC, McCandliss B. "Editorial: Neural bases of reading acquisition and reading disability." Frontiers in Neuroscience (2023).This editorial highlights advances in the neuroscience of reading, focusing on the brain mechanisms underlying reading development and disabilities. The authors summarize key themes across international research, including neuroimaging insights and educational applications.Stanford News. "Stanford-led study links school environment to brain development" (2024) Researchers found that children who attend higher-performing schools have accelerated white matter development, including in an area of the brain closely associated with reading skills.Stanford News. "Stanford study on brain waves shows how different teaching methods affect reading development" (2015)Stanford Professor Bruce McCandliss found that beginning readers who focus on letter-sound relationships, or phonics, increase activity in the area of their brains best wired for reading.We want to hear from your neurons! Email us at at neuronspodcast@stanford.eduSend 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.

Recognizing a familiar voice is one of the brain’s earliest social feats. But what are the brain circuits that let a newborn pick out mom in a crowded nursery? How do they change as kids turn toward friends and the wider world? And what are we learning about why this instinct fails to develop in the autistic brain?This week, host Nicholas Weiler joins Stanford neuroscientist Dan Abrams on the quest to understand the neural “hub” that links our brains' hearing centers to the networks that tag voices as rewarding, social, and worth our attention. The findings could reshape early-intervention strategies for kids on the spectrum.Learn MoreStanford Speech and Social Neuroscience LabParticipate in a StudyCommunity Support ResourcesPublicationsUnderconnectivity between voice-selective cortex and reward circuitry in children with autism (PNAS, 2013) Neural circuits underlying mother’s voice perception predict social communication abilities in children (PNAS, 2016) Impaired voice processing in reward and salience circuits predicts social communication in children with autism (eLife, 2019)  A Neurodevelopmental Shift in Reward Circuitry from Mother's to Nonfamilial Voices in Adolescence (Journal of Neuroscience, 2022)Stanford Coverage"The teen brain tunes in less to Mom's voice, more to unfamiliar voices, study finds" (Stanford Medicine, 2022)"Brain wiring explains why autism hinders grasp of vocal emotion, says Stanford Medicine study" (Stanford Medicine, 2023)We want to hear from your neurons! Email us at at neuronspodcast@stanford.eduSend 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.

Explore the extraordinary life of Stephen Hawking, who not only defied ALS but also reshaped our understanding of black holes. Discover how his unique ability to make complex physics accessible captivated audiences worldwide. Delve into deep philosophical questions about existence and the nature of the universe. The conversation intertwines humor, the challenges of fame, and the emotional impact of living with a serious condition, highlighting the duality of life's struggles and triumphs.

Join Keith Humphreys, the Esther Ting Memorial Professor at Stanford Medicine and co-director of the Stanford Network on Addiction Policy, as he dives into the intersection of neuroscience and addiction policy. He dismantles the myth of addiction as a moral failing, emphasizing its biological roots and how understanding these can improve treatment. The discussion also highlights the need for compassionate policy, the importance of prevention, and how innovative therapies could reshape our future approach to addiction, making it more humane and effective.

In this captivating discussion, Marion Buckwalter, a physician scientist at Stanford specializing in neurocritical care, shares her insights on the remarkable evolution of stroke treatment. She reveals how recent advancements, from AI-enabled imaging to innovative thrombolytic therapies, have drastically changed patient outcomes. Buckwalter stresses the importance of ongoing investment in basic science research to prevent stagnation in breakthroughs and highlights the exciting future that could await us if we maintain our focus on these foundational studies.

Dr. Martin Angst, a Stanford anesthesiology professor, delves into why some surgical patients face cognitive decline while others recover seamlessly. He discusses groundbreaking research following cardiac surgery patients, analyzing blood biomarkers and cognitive performance. Martin emphasizes the importance of personalized pre-surgical assessments and highlights how interventions, like young plasma infusion, might enhance resilience. The insights could lead to improved recovery strategies and better patient outcomes.

Jaimie Henderson, a Stanford neurosurgeon at the forefront of brain-machine interfaces, discusses the groundbreaking potential of neural prosthetics for those with brain and spinal cord injuries. He shares inspiring stories of individuals regaining abilities previously thought lost, including communication and movement. The conversation highlights advancements like deep brain stimulation devices and silicon microelectrode arrays that decode brain activity. Henderson also honors the legacy of Krishna Shenoy, emphasizing the power of collaboration in revolutionizing neuroscience.

Join Beth Mormino and Anthony Wagner, experts from Stanford's Aging and Memory Study, as they delve into the secrets of resilient aging. They share insights on how cognitive health can endure into old age, unraveling the complexities of Alzheimer's and the potential for early detection through innovative research. The discussion also touches on the impact of stereotypes on cognitive performance and how lifestyle choices, like social engagement, can enhance brain health. Their exciting research holds promise for healthier, longer lives.

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 moreAI 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 researchA 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 NeuroscienceFireside 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 touchWe 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 CreditsThis 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.