Brain Inspired

The podcast discusses synthesizing neural principles for better AI, focusing on a 'sideways-in' approach for computational brains. It explores integrating diverse brain operations, the challenges in achieving general-purpose AI, advancements in robotics inspired by biological principles, and the complexities of spiking neural networks for artificial general intelligence.

Dan Goodman, co-founder of Neuromatch and creator of the Brian spiking neural network simulator, discusses the importance of spikes in intelligent systems and the curious choice of modern neural networks to disregard spiking. They delve into the intricacies of spiking neural networks, the transition from math to neuroscience, the creation of complex tasks for neural networks, and the challenges in training them. They also explore the impact of advanced technology on human intelligence.

Neuroscientist and author John Krakauer returns to discuss brain reorganization, plasticity, motor problems after strokes, and artificial general intelligence. They explore the misconception of brain reorganization, the challenges in studying behavioral outcomes after a stroke, and the need to critically analyze scientific papers and challenge established ideas.

Max Bennett, an entrepreneur and author, discusses the breakthroughs in brain evolution and their impact on intelligence. Topics covered include the role of the neocortex in simulating and imagining, counterfactual learning, episodic memory, and the challenges of building human-like AI systems.

Panel discussion on using neuroscience technologies to decode memory from connectomes, featuring a group of experts including Kenneth Hayworth. Topics include advancements in connectomics, decoding memory and connectomes, analyzing connectome complexity, the role of molecules, deep learning parallelism, studying connectome data with cultured neurons, understanding neuronal interactions, and the rules of connectome interpretation.

Laura Gradowski, a philosopher of science at the University of Pittsburgh, discusses the importance of scientific pluralism and the inclusion of fringe theories in science. She cites historical examples, including the Garcia effect, that challenge mainstream theories and highlight the need for tolerance and diversity in scientific research. The podcast explores various topics such as the transition of fringe ideas to mainstream acceptance, the validation of traditional ecological knowledge, and the role of constraints in generating movement and thoughts. It also delves into the concept of the 'no end principle' and the continuous exploration of new ideas in science.

Eric Shea-Brown, a theoretical neuroscientist, discusses dynamics and dimensionality in neural networks, exploring how they change during tasks. He highlights research findings on structural connection motifs and dimensionalities related to different modes of learning. The podcast also covers the impact of model architectures on neural dynamics, the complexity of the biological brain, and the concept of rich brain vs lazy brain. The chapter on paths and motifs in neural networks showcases a student's prediction abilities. Finally, the guest expresses desires for advancements in neuroscience and support for the podcast.

Support the show to get full episodes, full archive, and join the Discord community. I was recently invited to moderate a panel at the Annual Bernstein conference - this one was in Berlin Germany. The panel I moderated was at a satellite workshop at the conference called How can machine learning be used to generate insights and theories in neuroscience? Below are the panelists. I hope you enjoy the discussion! Program: How can machine learning be used to generate insights and theories in neuroscience? Panelists: Katrin Franke Lab website. Twitter: @kfrankelab. Ralf Haefner Haefner lab. Twitter: @haefnerlab. Martin Hebart Hebart Lab. Twitter: @martin_hebart. Johannes Jaeger Yogi's website. Twitter: @yoginho. Fred Wolf Fred's university webpage. Organizers: Alexander Ecker | University of Göttingen, Germany Fabian Sinz | University of Göttingen, Germany Mohammad Bashiri, Pavithra Elumalai, Michaela Vystrcilová | University of Göttingen, Germany

David Poeppel, researcher studying auditory cognition, speech perception, language, and music at NYU, returns to discuss the mysteries of memory storage, the language of thought hypothesis, and the pace of scientific progress in understanding the brain. They explore the challenges of studying memory, the implementation requirements for language processing, and the potential combination of symbolic computation and dynamics in the brain. They also delve into the downside of unprincipled data mining and the re-emergence of the language of thought hypothesis in cognitive organization.

Kevin Mitchell, Professor of genetics at Trinity College Dublin, discusses his new book 'Free Agents: How Evolution Gave Us Free Will'. Topics include the origin of agency, complexity of free will, indeterminacy in the universe, harnessing brain's randomness, creativity, and artificial free will.