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Brain Inspired

Brain Inspired

Written by: Paul Middlebrooks
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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.© 2019 Brain-Inspired Science
Episodes
  • BI 228 Alex Maier: Laws of Consciousness
    Dec 31 2025

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    Alex is an associate professor of psychology at Vanderbilt University where he heads the Maier Lab. His work in neuroscience spans vision, visual perception, and cognition, studying the neurophysiology of cortical columns, and other related topics. Today, he is here to discuss where his focus has shifted over the past few years, the neuroscience of consciousness. I should say shifted back, since that was his original love, which you'll hear about.

    I've known Alex since my own time at Vanderbilt, where I was a postdoc and he was a new faculty member, and I remember being impressed with him then. I was at a talk he gave - job talk or early talk - where it was immediately obvious how passionate and articulate he is about what he does, and I remember he even showed off some of his telescope photography - good pictures of the moon, I remember. Anyway, we always had fun interactions, even if sometimes it was a quick hello as he ran up stairs and down hallways to get wherever he was going, always in a hurry.

    Today we discuss why Alex sees integration information theory as the most viable current prospect for explaining consciousness. That is mainly because IIT has developed a formalized mathematical account that hopes to do for consciousness what other math has done for physics, that is, give us what we know as laws of nature. So basically our discussion revolves around everything related to that, like philosophy of science, distinguishing mathematics from "the mathematical", some of the tools he is finding valuable, like category theory, and some of his work measuring the level of consciousness IIT says a whole soccer team has, not just the individuals that comprise the team.

    • Maier Lab
    • Astonishing Hypothesis (Alex's youtube channel)
    • Twitter:
    • Sensation and Perception textbook (in-the-making)
    • Related papers
      • Linking the Structure of Neuronal Mechanisms to the Structure of Qualia
      • Information integration and the latent consciousness of human groups
      • Neural mechanisms of predictive processing: a collaborative community experiment through the OpenScope program
    • Various things Alex mentioned:
      • “An Antiphilosophy of Mathematics,” Peter J. Freyd youtube video about "the mathematical".
      • David Kaiser's playlist on modern physics.

    0:00 - Intro...

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    1 hr and 58 mins
  • BI 227 Decoding Memories: Aspirational Neuroscience 2025
    Dec 17 2025

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    The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists.

    Read more about our partnership.

    Sign up for Brain Inspired email alerts to be notified every time a new Brain Inspired episode is released.

    To explore more neuroscience news and perspectives, visit thetransmitter.org.

    Can you look at all the synaptic connections of a brain, and tell me one nontrivial memory from the organism that has that brain? If so, you shall win the $100,000 prize from the Aspirational Neuroscience group.

    I was recently invited for the second time to chair a panel of experts to discuss that question and all the issues around that question - how to decode a non-trivial memory from a static map of synaptic connectivity.

    Before I play that recording, let me set the stage a bit more.

    Aspirational Neuroscience is a community of neuroscientists run by Kenneth Hayworth, with the goal, from their website, to "balance aspirational thinking with respect to the long-term implications of a successful neuroscience with practical realism about our current state of ignorance and knowledge." One of those aspirations is to decoding things - memories, learned behaviors, and so on - from static connectomes. They hold satellite events at the SfN conference, and invite experts in connectomics from academia and from industry to share their thoughts and progress that might advance that goal.

    In this panel discussion, we touch on multiple relevant topics. One question is what is the right experimental design or designs that would answer whether we are decoding memory - what is a benchmark in various model organisms, and for various theoretical frameworks? We discuss some of the obstacles in the way, both technologically and conceptually. Like the fact that proofreading connectome connections - manually verifying and editing them - is a giant bottleneck, or like the very definition of memory, what counts as a memory, let alone a "nontrivial" memory, and so on. And they take lots of questions from the audience as well.

    I apologize the audio is not crystal clear in this recording. I did my best to clean it up, and I take full blame for not setting up my audio recorder to capture the best sound. So, if you are a listener, I'd encourage you to check out the video version, which also has subtitles throughout for when the language isn't clear.

    Anyway, this is a fun and smart group of people, and I look forward to another one next year I hope.

    The last time I did this was episode 180, BI 180, which I link to in the show notes. Before that I had on Ken Hayworth, whom I mentioned runs Aspirational Neuroscience, and Randal Koene, who is on the panel this time. They were on to talk about the future possibility of uploading minds to computers based on connectomes. That was episode 103.

    • Aspirational Neuroscience
    • Panel
      • Michał Januszewski
        • @michalwj.bsky.social
        • Research scientist (connectomics) with Google Research, automated neural trac...
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    1 hr and 15 mins
  • BI 226 Tatiana Engel: The High and Low Dimensional Brain
    Dec 3 2025

    Support the show to get full episodes, full archive, and join the Discord community.

    The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists.

    Read more about our partnership.

    Sign up for Brain Inspired email alerts to be notified every time a new Brain Inspired episode is released.

    To explore more neuroscience news and perspectives, visit thetransmitter.org.

    Tatiana Engel runs the Engel lab at Princeton University in the Princeton Neuroscience Institute. She's also part of the International Brain Laboratory, a massive across-lab, across-world, collaboration which you'll hear more about. My main impetus for inviting Tatiana was to talk about two projects she's been working on. One of those is connecting the functional dynamics of cognition with the connectivity of the underlying neural networks on which those dynamics unfold. We know the brain is high-dimensional - it has lots of interacting connections, we know the activity of those networks can often be described by lower-dimensional entities called manifolds, and Tatiana and her lab work to connect those two processes with something they call latent circuits. So you'll hear about that, you'll also hear about how the timescales of neurons across the brain are different but the same, why this is cool and surprising, and we discuss many topics around those main topics.

    • Engel Lab.
    • @engeltatiana.bsky.social.
    • International Brain Laboratory.
    • Related papers:
      • Latent circuit inference from heterogeneous neural responses during cognitive tasks
      • The dynamics and geometry of choice in the premotor cortex.
      • A unifying perspective on neural manifolds and circuits for cognition
      • Brain-wide organization of intrinsic timescales at single-neuron resolution
      • Single-unit activations confer inductive biases for emergent circuit solutions to cognitive tasks.

    0:00 - Intro 3:03 - No central executive 5:01 - International brain lab 15:57 - Tatiana's background 24:49 - Dynamical systems 17:48 - Manifolds 33:10 - Latent task circuits 47:01 - Mixed selectivity 1:00:21 - Internal and external dynamics 1:03:47 - Modern vs classical modeling 1:14:30 - Intrinsic timescales 1:26:05 - Single trial dynamics 1:29:59 - Future of manifolds

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    1 hr and 36 mins
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