Headshot of Eric Kandel.

Eric Kandel

University professor emeritus
Columbia University

Eric R. Kandel is university professor emeritus and professor emeritus of physiology and cellular biophysics, psychiatry, biochemistry, molecular biophysics and neuroscience at Columbia University. He is founding co-director of Columbia University’s Zuckerman Institute, founding director of Columbia’s Kavli Institute for Brain Science, and Sagol Professor Emeritus of Brain Science at the Zuckerman Institute. He was also a senior investigator at the Howard Hughes Medical Institute from 1984 to 2022. In 2000, Kandel was awarded the Nobel Prize in Physiology or Medicine for his studies of learning and memory. He has been awarded 24 honorary degrees. Kandel is the author of “In Search of Memory: The Emergence of a New Science of Mind” (2006), “The Age of Insight: The Quest to Understand the Unconscious in Art, Mind and Brain, from Vienna 1900 to the Present” (2012), “Reductionism in Art and Brain Science: Bridging the Two Cultures” (Columbia, 2016), “The Disordered Mind: What Unusual Brains Tell Us About Ourselves” (2018), and “There Is Life After the Nobel Prize” (Columbia, 2022). He is also a co-author of “Principles of Neural Science” (2021), the standard textbook in the field of neuroscience.

From this contributor

Explore more from The Transmitter

Video catches microglia in the act of synaptic pruning

Live cell imaging reveals the clearest picture yet of this elusive process. Whether it’s something these cells do regularly remains up for debate.

By RJ Mackenzie
26 March 2025 | 0 min watch

Gabriele Scheler reflects on the interplay between language, thought and AI

She discusses how verbal thought shapes cognition, why inner speech is foundational to human intelligence and what current artificial-intelligence models get wrong about language.

By Paul Middlebrooks
26 March 2025 | 96 min listen
Data streams into a transparent box.

Accepting “the bitter lesson” and embracing the brain’s complexity

To gain insight into complex neural data, we must move toward a data-driven regime, training large models on vast amounts of information. We asked nine experts on computational neuroscience and neural data analysis to weigh in.

By Eva Dyer, Blake Richards
26 March 2025 | 8 min read