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PODCAST

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

science natural sciences

All Episodes

01:21:01

BI 129 Patryk Laurent: Learning from the Real World

Brain Inspired ·

2022/03/02

Support the show to get full episodes and join the Discord community. Patryk and I discuss his wide-ranging background working in both the neuroscience and AI worlds, and his resultant perspective on what's needed to move forward in AI, including some principles of brain processes that are more and less important. We also discuss his own work using some of those principles to help deep learning generalize to better capture how humans behave in and perceive the world. Patryk's

en-US

01:25:40

BI 128 Hakwan Lau: In Consciousness We Trust

Brain Inspired ·

2022/02/20

Support the show to get full episodes and join the Discord community. Hakwan and I discuss many of the topics in his new book, In Consciousness we Trust: The Cognitive Neuroscience of Subjective Experience. Hakwan describes his perceptual reality monitoring theory of consciousness, which suggests consciousness may act as a systems check between our sensory perceptions and higher cognitive functions. We also discuss his latest thoughts on mental quality space and how it relates to perceptual

en-US

01:42:39

BI 127 Tomás Ryan: Memory, Instinct, and Forgetting

Brain Inspired ·

2022/02/10

Support the show to get full episodes and join the Discord community. Tomás and I discuss his research and ideas on how memories are encoded (the engram), the role of forgetting, and the overlapping mechanisms of memory and instinct. Tomás uses otpogenetics and other techniques to label and control neurons involved in learning and memory, and has shown that forgotten memories can be restored by stimulating "engram cells" originally associated with the forgotten memory. This line of research

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01:19:57

BI 126 Randy Gallistel: Where Is the Engram?

Brain Inspired ·

2022/01/31

Support the show to get full episodes and join the Discord community. Randy and I discuss his long-standing interest in how the brain stores information to compute. That is, where is the engram, the physical trace of memory in the brain? Modern neuroscience is dominated by the view that memories are stored among synaptic connections in populations of neurons. Randy believes a more reasonable and reliable way to store abstract symbols, like numbers, is to write them into code within

en-US

01:11:05

BI 125 Doris Tsao, Tony Zador, Blake Richards: NAISys

Brain Inspired ·

2022/01/19

Support the show to get full episodes and join the Discord community. Doris, Tony, and Blake are the organizers for this year's NAISys conference, From Neuroscience to Artificially Intelligent Systems (NAISys), at Cold Spring Harbor. We discuss the conference itself, some history of the neuroscience and AI interface, their current research interests, and a handful of topics around evolution, innateness, development, learning, and the current and future prospects for using neuroscience to

en-US

01:39:27

BI 124 Peter Robin Hiesinger: The Self-Assembling Brain

Brain Inspired ·

2022/01/05

Support the show to get full episodes and join the Discord community. Robin and I discuss many of the ideas in his book The Self-Assembling Brain: How Neural Networks Grow Smarter. The premise is that our DNA encodes an algorithmic growth process that unfolds information via time and energy, resulting in a connected neural network (our brains!) imbued with vast amounts of information from the "start". This contrasts with modern deep learning networks, which start with minimal initial

en-US

01:18:59

BI 123 Irina Rish: Continual Learning

Brain Inspired ·

2021/12/26

Support the show to get full episodes and join the Discord community. Irina is a faculty member at MILA-Quebec AI Institute and a professor at Université de Montréal. She has worked from both ends of the neuroscience/AI interface, using AI for neuroscience applications, and using neural principles to help improve AI. We discuss her work on biologically-plausible alternatives to back-propagation, using "auxiliary variables" in addition to the normal connection weight updates. We also discuss

en-US

01:33:18

BI 122 Kohitij Kar: Visual Intelligence

Brain Inspired ·

2021/12/12

Support the show to get full episodes and join the Discord community. Ko and I discuss a range of topics around his work to understand our visual intelligence. Ko was a postdoc in James Dicarlo's lab, where he helped develop the convolutional neural network models that have become the standard for explaining core object recognition. He is starting his own lab at York University, where he will continue to expand and refine the models, adding important biological details and incorporating

en-US

01:43:12

BI 121 Mac Shine: Systems Neurobiology

Brain Inspired ·

2021/12/02

Support the show to get full episodes and join the Discord community. Mac and I discuss his systems level approach to understanding brains, and his theoretical work suggesting important roles for the thalamus, basal ganglia, and cerebellum, shifting the dynamical landscape of brain function within varying behavioral contexts. We also discuss his recent interest in the ascending arousal system and neuromodulators. Mac thinks the neocortex has been the sole focus of too much neuroscience

en-US

01:40:02

BI 120 James Fitzgerald, Andrew Saxe, Weinan Sun:...

Brain Inspired ·

2021/11/21

Support the show to get full episodes and join the Discord community. James, Andrew, and Weinan discuss their recent theory about how the brain might use complementary learning systems to optimize our memories. The idea is that our hippocampus creates our episodic memories for individual events, full of particular details. And through a complementary process, slowly consolidates those memories within our neocortex through mechanisms like hippocampal replay. The new idea in their work

en-US

01:06:36

BI 119 Henry Yin: The Crisis in Neuroscience

Brain Inspired ·

2021/11/11

Support the show to get full episodes and join the Discord community. Henry and I discuss why he thinks neuroscience is in a crisis (in the Thomas Kuhn sense of scientific paradigms, crises, and revolutions). Henry thinks our current concept of the brain as an input-output device, with cognition in the middle, is mistaken. He points to the failure of neuroscience to successfully explain behavior despite decades of research. Instead, Henry proposes the brain is one big hierarchical set of

en-US

01:36:08

BI 118 Johannes Jäger: Beyond Networks

Brain Inspired ·

2021/11/01

Support the show to get full episodes and join the Discord community. Johannes (Yogi) is a freelance philosopher, researcher & educator. We discuss many of the topics in his online course, Beyond Networks: The Evolution of Living Systems. The course is focused on the role of agency in evolution, but it covers a vast range of topics: process vs. substance metaphysics, causality, mechanistic dynamic explanation, teleology, the important role of development mediating genotypes, phenotypes,

en-US

01:32:09

BI 117 Anil Seth: Being You

Brain Inspired ·

2021/10/19

Support the show to get full episodes and join the Discord community. Anil and I discuss a range of topics from his book, BEING YOU A New Science of Consciousness. Anil lays out his framework for explaining consciousness, which is embedded in what he calls the "real problem" of consciousness. You know the "hard problem", which was David Chalmers term for our eternal difficulties to explain why we have subjective awareness at all instead of being unfeeling, unexperiencing machine-like

en-US

01:31:20

BI 116 Michael W. Cole: Empirical Neural Networks

Brain Inspired ·

2021/10/12

Support the show to get full episodes and join the Discord community. Mike and I discuss his modeling approach to study cognition. Many people I have on the podcast use deep neural networks to study brains, where the idea is to train or optimize the model to perform a task, then compare the model properties with brain properties. Mike's approach is different in at least two ways. One, he builds the architecture of his models using connectivity data from fMRI recordings. Two, he doesn't train

en-US

01:23:41

BI 115 Steve Grossberg: Conscious Mind, Resonant Brain

Brain Inspired ·

2021/10/02

Support the show to get full episodes and join the Discord community. Steve and I discuss his book Conscious Mind, Resonant Brain: How Each Brain Makes a Mind. The book is a huge collection of his models and their predictions and explanations for a wide array of cognitive brain functions. Many of the models spring from his Adaptive Resonance Theory (ART) framework, which explains how networks of neurons deal with changing environments while maintaining self-organization and retaining

en-US

01:38:07

BI 114 Mark Sprevak and Mazviita Chirimuuta:...

Brain Inspired ·

2021/09/22

Support the show to get full episodes and join the Discord community. Mark and Mazviita discuss the philosophy and science of mind, and how to think about computations with respect to understanding minds. Current approaches to explaining brain function are dominated by computational models and the computer metaphor for brain and mind. But there are alternative ways to think about the relation between computations and brain function, which we explore in the discussion. We also talk about the

en-US

01:30:38

BI 113 David Barack and John Krakauer: Two Views On...

Brain Inspired ·

2021/09/12

Support the show to get full episodes and join the Discord community. David and John discuss some of the concepts from their recent paper Two Views on the Cognitive Brain, in which they argue the recent population-based dynamical systems approach is a promising route to understanding brain activity underpinning higher cognition. We discuss mental representations, the kinds of dynamical objects being used for explanation, and much more, including David's perspectives as a practicing

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00:57:25

BI ViDA Panel Discussion: Deep RL and Dopamine

Brain Inspired ·

2021/09/02

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01:13:56

BI 112 Ali Mohebi and Ben Engelhard: The Many Faces...

Brain Inspired ·

2021/08/26

BI 112: Ali Mohebi and Ben Engelhard The Many Faces of Dopamine Announcement: Ben has started his new lab and is recruiting grad students. Check out his lab here and apply! Engelhard Lab Ali and Ben discuss the ever-expanding discoveries about the roles dopamine plays for our cognition. Dopamine is known to play a role in learning – dopamine (DA) neurons fire

en-US

01:20:32

BI NMA 06: Advancing Neuro Deep Learning Panel

Brain Inspired ·

2021/08/19

en-US

240 results

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