Brain Inspired
Paul Middlebrooks
Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.
Episodes
Mentioned books
Oct 8, 2024 • 1h 17min
BI 195 Ken Harris and Andreas Tolias with Gaute Einevoll and Mikkel Lepperød
Mikkel Lepperød, an organizer of the NeuroAI workshop, joins neuroscientists Ken Harris and Andreas Tolias to explore AI's influence on neuroscience. They delve into the intersection of neural modeling and AI, discussing the balance between predictive accuracy and interpretability. The conversation highlights the role of deep learning in understanding cognition, the potential pitfalls of AI in research, and the philosophical implications of modern models. They also share insights on validating scientific ideas and the evolving productivity landscape in academia.
Sep 27, 2024 • 1h 37min
BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting
Vijay Namboodiri, who runs the Nam Lab at UCSF, teams up with Ali Mohebi, an assistant professor at UW-Madison, to dive deep into the intricacies of dopamine. They challenge the classic narrative of dopamine's role in reward prediction, proposing a retrospective view that redefines how we understand causal relationships. Their discussions cover sign tracking versus goal tracking in learning, the implications for addiction, and the need for new models that integrate temporal differences. They also touch on how our past experiences inform current decisions, shaping our understanding of learning.
4 snips
Sep 11, 2024 • 1h 33min
BI 193 Kim Stachenfeld: Enhancing Neuroscience and AI
Kim Stachenfeld, a Senior Research Scientist at Google DeepMind and a researcher at Columbia's Center for Theoretical Neuroscience, dives into the captivating world of neuroscience and AI. She discusses the critical role of neural networks in emulating human cognition and their applications in understanding the brain. Kim explores the nuances of reinforcement learning, the intersection of academia and industry, and insights into memory and intelligence. She also challenges traditional model hierarchies, emphasizing the need for predictive and interpretable models in AI.
Aug 28, 2024 • 1h 31min
BI 192 Àlex Gómez-Marín: The Edges of Consciousness
Àlex Gómez-Marín, a theoretical physicist turned neuroscientist, heads The Behavior of Organisms Laboratory in Alicante, Spain. He explores the "edges of consciousness," discussing experiences like hallucinogens and near-death episodes. Àlex shares profound insights from his own near-death experience, challenging conventional scientific approaches and embracing a pluralistic view of consciousness. He highlights the importance of open-mindedness in understanding anomalies and discusses the philosophical implications of consciousness in today's technological age.
5 snips
Aug 15, 2024 • 1h 28min
BI 191 Damian Kelty-Stephen: Fractal Turbulent Cascading Intelligence
Damian Kelty-Stephen, an experimental psychologist at SUNY New Paltz, explores the boundaries of ecological psychology and neuroscience. He challenges the conventional computer metaphor of the brain and discusses fractal behaviors linking brain and body. The conversation delves into cascade dynamics and turbulence as key elements of intelligence. Damian advocates for a richer understanding of cognition through multifractal frameworks, emphasizing the complexity of self-organization in both natural and artificial systems.
6 snips
Jul 31, 2024 • 1h 41min
BI 190 Luis Favela: The Ecological Brain
Luis Favela, an Associate Professor at Indiana University Bloomington and expert in cognitive science and philosophy, dives into the complexities of the mind and environment. He introduces his NeuroEcological Nexus Theory, advocating for a fusion between ecological psychology and neuroscience. The discussion spans historical rifts, the conceptualization of intelligence, and the philosophical implications of perception. Favela also questions traditional views on AI, emphasizing the role of embodied cognition. His insights promise a refreshing perspective on brain-body-environment interactions.
10 snips
Jun 29, 2024 • 1h 27min
BI 189 Joshua Vogelstein: Connectomes and Prospective Learning
Joshua Vogelstein discusses the world's largest connectome, focusing on a fruit fly's brain. He explains the concept of prospective learning in AI compared to retrospective learning, highlighting its potential. The podcast covers audio/video sync issues, data cleaning challenges, and the importance of anatomy in understanding brain function.
May 27, 2024 • 1h 28min
BI 188 Jolande Fooken: Coordinating Action and Perception
Jolande Fooken, a post-postdoctoral researcher, discusses hand-eye coordination and naturalistic tasks. Topics include various eye movements, levels of expertise, Yarbus' work, experimental paradigms for the brain, evolving views about the brain, and the intersection of coordination, robots, and AI.
Apr 20, 2024 • 1h 4min
BI 187: COSYNE 2024 Neuro-AI Panel
Neuroscientists and AI experts discuss the relationship between neuroscience and AI at the COSYNE conference. They explore historical influences, evolving research approaches, and the need for interdisciplinary collaboration for progress. Topics include the shift in priorities from neuroscience to AI, the intersection of neuroscience and AI, and predictions for the future of neuro-AI in 2044.
19 snips
Mar 25, 2024 • 1h 44min
BI 186 Mazviita Chirimuuta: The Brain Abstracted
Philosopher Mazviita Chirimuuta discusses simplification in neuroscience, highlighting the use of models, math, and analogies to understand the complex brain. She explores the intersection of neuroscience and philosophy, delves into simplification strategies in science, and emphasizes the interplay of technology and scientific understanding. The discussion touches on the challenges of interpreting scientific results, the limitations of reductionism, and the importance of maintaining a critical mindset in scientific pursuits.
