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Brain Inspired

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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.

#210

BI 199 Hessam Akhlaghpour: Natural Universal Computation

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Hessam Akhlaghpour is a postdoctoral researcher at Rockefeller University in the Maimon lab. His experimental work is in fly neuroscience mostly studying spatial memories in fruit flies. However, we are going to be talking about a different (although somewhat related) side of his postdoctoral research. This aspect of his work involves theoretical explorations of molecular computation, which are deeply inspired by Randy Gallistel and Adam King's book Memory and the Computational Brain. Randy has been on the podcast before to discuss his ideas that memory needs to be stored in something more stable than the synapses between neurons, and how that something could be genetic material like RNA. When Hessam read this book, he was re-inspired to think of the brain the way he used to think of it before experimental neuroscience challenged his views. It re-inspired him to think of the brain as a computational system. But it also led to what we discuss today, the idea that RNA has the capacity for universal computation, and Hessam's development of how that might happen. So we discuss that background and story, why universal computation has been discovered in organisms yet since surely evolution has stumbled upon it, and how RNA might and combinatory logic could implement universal computation in nature. --- [Hessam's website] (https://www.akhlaghpour.info/) . --- [Maimon Lab] (https://maimonlab.rockefeller.edu/) . ---Twitter: [@theHessam] (https://x.com/theHessam) . ---Related papers ------ [An RNA-based theory of natural universal computation] (https://www.sciencedirect.com/science/article/pii/S0022519321004045) . ------ [The molecular memory code and synaptic plasticity: a synthesis] (https://arxiv.org/abs/2209.04923) . ------ [Lifelong persistence of nuclear RNAs in the mouse brain] (https://doi.org/10.1126/science.adf3481) . ------ [Cris Moore's conjecture #5 in this 1998 paper] (https://sites.santafe.edu/~moore/pubs/FlowsMaps.pdf) . ------(The Gallistel book): [Memory and the Computational Brain: Why Cognitive Science Will Transform Neuroscience] (https://onlinelibrary.wiley.com/doi/book/10.1002/9781444310498) . ---Related episodes ------ [BI 126 Randy Gallistel: Where Is the Engram?] (https://braininspired.co/podcast/126/) ------ [BI 172 David Glanzman: Memory All The Way Down] (https://braininspired.co/podcast/172/) 0:00 - Intro 4:44 - Hessam's background 11:50 - Randy Gallistel's book 14:43 - Information in the brain 17:51 - Hessam's turn to universal computation 35:30 - AI and universal computation 40:09 - Universal computation to solve intelligence 44:22 - Connecting sub and super molecular 50:10 - Junk DNA 56:42 - Genetic material for coding 1:06:37 - RNA and combinatory logic 1:35:14 - Outlook 1:42:11 - Reflecting on the molecular world ... Read more

26 Nov 2024

1 HR 49 MINS

1:49:07

26 Nov 2024

#209

BI 198 Tony Zador: Neuroscience Principles to Improve AI

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> 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] (https://www.thetransmitter.org/partners/) . Sign up for the “Brain Inspired” email alerts to be notified every time a new “Brain Inspired” episode is released: [https://www.thetransmitter.org/newsletters/] (https://www.thetransmitter.org/newsletters/) To explore more neuroscience news and perspectives, visit thetransmitter.org. Tony Zador runs the Zador lab at Cold Spring Harbor Laboratory. You've heard him on Brain Inspired a few times in the past, most recently in a panel discussion I moderated at this past COSYNE conference - a conference Tony co-founded 20 years ago. As you'll hear, Tony's current and past interests and research endeavors are of a wide variety, but today we focus mostly on his thoughts on NeuroAI. We're in a huge AI hype cycle right now, for good reason, and there's a lot of talk in the neuroscience world about whether neuroscience has anything of value to provide AI engineers - and how much value, if any, neuroscience has provided in the past. Tony is team neuroscience. You'll hear him discuss why in this episode, especially when it comes to ways in which development and evolution might inspire better data efficiency, looking to animals in general to understand how they coordinate numerous objective functions to achieve their intelligent behaviors - something Tony calls alignment - and using spikes in AI models to increase energy efficiency. --- [Zador Lab] (https://zadorlab.labsites.cshl.edu/) ---Twitter: [@TonyZador] (https://twitter.com/TonyZador) ---Previous episodes: ------ [BI 187: COSYNE 2024 Neuro-AI Panel] (https://braininspired.co/podcast/187/) . ------ [BI 125 Doris Tsao, Tony Zador, Blake Richards: NAISys] (https://braininspired.co/podcast/125/) ------ [BI 034 Tony Zador: How DNA and Evolution Can Inform AI] (https://braininspired.co/podcast/34/) ---Related papers ------ [Catalyzing next-generation Artificial Intelligence through NeuroAI] (https://zadorlab.labsites.cshl.edu/wp-content/uploads/sites/59/2024/08/Catalyzing-Next-Generation-Artificial-Intelligence-through-NeuroAI.pdf) . ------ [Encoding innate ability through a genomic bottleneck] (https://zadorlab.labsites.cshl.edu/wp-content/uploads/sites/59/2024/09/shuvaev-et-al-2024-Encoding-innate-ability-through-a-genomic-bottleneck-.pdf) . ---Essays ------ [NeuroAI: A field born from the symbiosis between neuroscience, AI] (https://www.thetransmitter.org/neuroai/neuroai-a-field-born-from-the-symbiosis-between-neuroscience-ai/) . ------ [What the brain can teach artificial neural networks] (https://www.thetransmitter.org/neuroai/what-the-brain-can-teach-artificial-neural-networks/) . Read the [transcript] (https://www.thetransmitter.org/wp-content/uploads/2024/11/BI-198-transcript-final-1.pdf) . 0:00 - Intro 3:28 - "Neuro-AI" 12:48 - Visual cognition history 18:24 - Information theory in neuroscience 20:47 - Necessary steps for progress 24:34 - Neuro-AI models and cognition 35:47 - Animals for inspiring AI 41:48 - What we want AI to do 46:01 - Development and AI 59:03 - Robots 1:25:10 - Catalyzing the next generation of AI ... Read more

11 Nov 2024

1 HR 35 MINS

1:35:04

11 Nov 2024

#208

BI 197 Karen Adolph: How Babies Learn to Move and Think

25 Oct 2024

1 HR 29 MINS

1:29:31

25 Oct 2024

#207

BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød

11 Oct 2024

1 HR 19 MINS

1:19:40

11 Oct 2024

#206

BI 195 Ken Harris and Andreas Tolias with Gaute Einevoll and Mikkel Lepperød

08 Oct 2024

1 HR 17 MINS

1:17:05

08 Oct 2024

#205

BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> https://youtu.be/lbKEOdbeqHo 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] (http://thetransmitter.org/) to explore the latest neuroscience news and perspectives, written by journalists and scientists. The Transmitter has provided a transcript for this episode. Vijay Namoodiri runs the Nam Lab at the University of California San Francisco, and Ali Mojebi is an assistant professor at the University of Wisconsin-Madison. Ali as been on the podcast before a few times, and he's interested in how neuromodulators like dopamine affect our cognition. And it was Ali who pointed me to Vijay, because of some recent work Vijay has done reassessing how dopamine might function differently than what has become the classic story of dopamine's function as it pertains to learning. The classic story is that dopamine is related to reward prediction errors. That is, dopamine is modulated when you expect reward and don't get it, and/or when you don't expect reward but do get it. Vijay calls this a "prospective" account of dopamine function, since it requires an animal to look into the future to expect a reward. Vijay has shown, however, that a retrospective account of dopamine might better explain lots of know behavioral data. This retrospective account links dopamine to how we understand causes and effects in our ongoing behavior. So in this episode, Vijay gives us a history lesson about dopamine, his newer story and why it has caused a bit of controversy, and how all of this came to be. I happened to be looking at the Transmitter the other day, after I recorded this episode, and low and behold, there was an article titles [Reconstructing dopamine’s link to reward] (https://www.thetransmitter.org/dopamine/reconstructing-dopamines-link-to-reward/) . Vijay is featured in the article among a handful of other thoughtful researchers who share their work and ideas about this very topic. Vijay wrote his own piece as well: [Dopamine and the need for alternative theories] (https://www.thetransmitter.org/dopamine/dopamine-and-the-need-for-alternative-theories/) . So check out those articles for more views on how the field is reconsidering how dopamine works. --- [Nam Lab] (https://www.namboodirilab.org/research) . --- [Mohebi & Associates (Ali's Lab)] (https://lab.mohebial.com/) . ---Twitter: ------ [@vijay_mkn] (https://x.com/vijay_mkn) ------ [@mohebial] (https://twitter.com/mohebial) ---Transmitter ------ [Dopamine and the need for alternative theories] (https://www.thetransmitter.org/dopamine/dopamine-and-the-need-for-alternative-theories/) . ------ [Reconstructing dopamine’s link to reward] (https://www.thetransmitter.org/dopamine/reconstructing-dopamines-link-to-reward/) . ---Related papers ------ [Mesolimbic dopamine release conveys causal associations] (https://www.science.org/stoken/author-tokens/ST-895/full) . ------ [Mesostriatal dopamine is sensitive to changes in specific cue-reward contingencies] (https://www.science.org/doi/full/10.1126/sciadv.adn4203) . ------ [What is the state space of the world for real animals?] (https://www.biorxiv.org/content/10.1101/2021.02.07.430001v1.abstract) ------ [The learning of prospective and retrospective cognitive maps within neural circuits] (https://www.sciencedirect.com/science/article/pii/S0896627321007078) ---Further reading ------(Ali's paper): [Dopamine transients follow a striatal gradient of reward time horizons.] (https://www.nature.com/articles/s41593-023-01566-3) ------Ali listed a bunch of work on local modulation of DA release: --------- [Local control of striatal dopamine release] (https://www.frontiersin.org/journals/behavioral-neuroscience/articles/10.3389/fnbeh.2014.00188/full) . --------- [Synaptic-like axo-axonal transmission from striatal cholinergic interneurons onto dopaminergic fibers] (https://pubmed.ncbi.nlm.nih.gov/35931070/) . --------- [Spatial and temporal scales of dopamine transmission] (https://pubmed.ncbi.nlm.nih.gov/33837376/) . --------- [Striatal dopamine neurotransmission: Regulation of release and uptake] (https://pubmed.ncbi.nlm.nih.gov/27141430/) . --------- [Striatal Dopamine Release Is Triggered by Synchronized Activity in Cholinergic Interneurons] (https://pubmed.ncbi.nlm.nih.gov/22794260/) . --------- [An action potential initiation mechanism in distal axons for the control of dopamine release] (https://www.science.org/doi/10.1126/science.abn0532) . [Read the transcript] (https://www.thetransmitter.org/wp-content/uploads/2024/09/BI-194-transcript-final.pdf) , produced by [The Transmitter] (http://thetransmitter.org/) . 0:00 - Intro 3:42 - Dopamine: the history of theories 32:54 - Importance of learning and behavior studies 39:12 - Dopamine and causality 1:06:45 - Controversy over Vijay's findings ... Read more

27 Sep 2024

1 HR 37 MINS

1:37:21

27 Sep 2024

#204

BI 193 Kim Stachenfeld: Enhancing Neuroscience and AI

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> 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] (http://thetransmitter.org/) to explore the latest neuroscience news and perspectives, written by journalists and scientists. Read more about [our partnership] (https://www.thetransmitter.org/partners/) . Check out this story: [Monkeys build mental maps to navigate new tasks] (https://www.thetransmitter.org/cognitive-neuroscience/monkeys-build-mental-maps-to-navigate-new-tasks/) Sign up for [“Brain Inspired” email alerts] (https://www.thetransmitter.org/newsletters/) to be notified every time a new “Brain Inspired” episode is released. To explore more neuroscience news and perspectives, visit [thetransmitter.org] (http://thetransmitter.org/) . Kim Stachenfeld embodies the original core focus of this podcast, the exploration of the intersection between neuroscience and AI, now commonly known as Neuro-AI. That's because she walks both lines. Kim is a Senior Research Scientist at Google DeepMind, the AI company that sprang from neuroscience principles, and also does research at the Center for Theoretical Neuroscience at Columbia University. She's been using her expertise in modeling, and reinforcement learning, and cognitive maps, for example, to help understand brains and to help improve AI. I've been wanting to have her on for a long time to get her broad perspective on AI and neuroscience. We discuss the relative roles of industry and academia in pursuing various objectives related to understanding and building cognitive entities She's studied the hippocampus in her research on reinforcement learning and cognitive maps, so we discuss what the heck the hippocampus does since it seems to implicated in so many functions, and how she thinks of reinforcement learning these days. Most recently Kim at Deepmind has focused on more practical engineering questions, using deep learning models to predict things like chaotic turbulent flows, and even to help design things like bridges and airplanes. And we don't get into the specifics of that work, but, given that I just spoke with Damian Kelty-Stephen, who thinks of brains partially as turbulent cascades, Kim and I discuss how her work on modeling turbulence has shaped her thoughts about brains. --- [Kim's website] (https://neurokim.com/) . ---Twitter: [@neuro_kim] (https://twitter.com/neuro_kim?ref_src=twsrc%5Etfw%7Ctwcamp%5Eembeddedtimeline%7Ctwterm%5Escreen-name%3Aneuro_kim%7Ctwcon%5Es2) . ---Related papers ------ [Scaling Laws for Neural Language Models] (https://arxiv.org/abs/2001.08361) . ------ [Emergent Abilities of Large Language Models] (https://arxiv.org/abs/2206.07682) . ------Learned simulators: --------- [Learned coarse models for efficient turbulence simulation] (https://arxiv.org/abs/2112.15275) . --------- [Physical design using differentiable learned simulators] (https://arxiv.org/pdf/2202.00728) . Check out [the transcript] (https://www.thetransmitter.org/wp-content/uploads/2024/09/kim-stachenfeld-transcript-final.pdf) , provided by The Transmitter. 0:00 - Intro 4:31 - Deepmind's original and current vision 9:53 - AI as tools and models 12:53 - Has AI hindered neuroscience? 17:05 - Deepmind vs academic work balance 20:47 - Is industry better suited to understand brains? 24?42 - Trajectory of Deepmind 27:41 - Kim's trajectory 33:35 - Is the brain a ML entity? 36:12 - Hippocampus 44:12 - Reinforcement learning 51:32 - What does neuroscience need more and less of? 1:02:53 - Neuroscience in a weird place? 1:06:41 - How Kim's questions have changed 1:16:31 - Intelligence and LLMs 1:25:34 - Challenges ... Read more

11 Sep 2024

1 HR 32 MINS

1:32:41

11 Sep 2024

#203

BI 192 Àlex Gómez-Marín: The Edges of Consciousness

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Àlex Gómez-Marín heads [The Behavior of Organisms Laboratory] (https://behavior-of-organisms.org/) at the Institute of Neuroscience in Alicante, Spain. He's one of those theoretical physicist turned neuroscientist, and he has studied a wide range of topics over his career. Most recently, he has become interested in what he calls the "edges of consciousness", which encompasses the many trying to explain what may be happening when we have experiences outside our normal everyday experiences. For example, when we are under the influence of hallucinogens, when have near-death experiences (as Alex has), paranormal experiences, and so on. So we discuss what led up to his interests in these edges of consciousness, how he now thinks about consciousness and doing science in general, how important it is to make room for all possible explanations of phenomena, and to leave our metaphysics open all the while. ---Alex's website: [The Behavior of Organisms Laboratory] (https://behavior-of-organisms.org/) . ---Twitter: [@behaviOrganisms] (https://twitter.com/behaviOrganisms) . ---Previous episodes: ------ [BI 168 Frauke Sandig and Eric Black w Alex Gomez-Marin: AWARE: Glimpses of Consciousness] (https://braininspired.co/podcast/168/) . ------ [BI 136 Michel Bitbol and Alex Gomez-Marin: Phenomenology] (https://braininspired.co/podcast/136/) . ---Related: ------ [The Consciousness of Neuroscience] (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10646881/) . ------ [Seeing the consciousness forest for the trees] (https://iai.tv/articles/seeing-the-consciousness-forest-for-the-trees-auid-2901?_auid=2020) . ------ [The stairway to transhumanist heaven] (https://www.nature.com/articles/d41586-024-02603-2.pdf) . 0:00 - Intro 4:13 - Evolving viewpoints 10:05 - Near-death experience 18:30 - Mechanistic neuroscience vs. the rest 22:46 - Are you doing science? 33:46 - Where is my. mind? 44:55 - Productive vs. permissive brain 59:30 - Panpsychism 1:07:58 - Materialism 1:10:38 - How to choose what to do 1:16:54 - Fruit flies 1:19:52 - AI and the Singularity ... Read more

28 Aug 2024

1 HR 30 MINS

1:30:34

28 Aug 2024

#202

BI 191 Damian Kelty-Stephen: Fractal Turbulent Cascading Intelligence

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Damian Kelty-Stephen is an experimental psychologist at State University of New York at New Paltz. Last episode with Luis Favela, we discussed many of the ideas from ecological psychology, and how Louie is trying to reconcile those principles with those of neuroscience. In this episode, Damian and I in some ways continue that discussion, because Damian is also interested in unifying principles of ecological psychology and neuroscience. However, he is approaching it from a different perspective that Louie. What drew me originally to Damian was a paper he put together with a bunch of authors offering their own alternatives to the computer metaphor of the brain, which has come to dominate neuroscience. And we discuss that some, and I'll link to the paper in the show notes. But mostly we discuss Damian's work studying the fractal structure of our behaviors, connecting that structure across scales, and linking it to how our brains and bodies interact to produce our behaviors. Along the way, we talk about his interests in cascades dynamics and turbulence to also explain our intelligence and behaviors. So, I hope you enjoy this alternative slice into thinking about how we think and move in our bodies and in the world. --- [Damian's website] (https://sites.google.com/site/foovian/) . ---Related papers ------ [In search for an alternative to the computer metaphor of the mind and brain] (https://arxiv.org/abs/2206.04603) . ------ [Multifractal emergent processes: Multiplicative interactions override nonlinear component properties] (https://arxiv.org/html/2401.05105v1) . 0:00 - Intro 2:34 - Damian's background 9:02 - Brains 12:56 - Do neuroscientists have it all wrong? 16:56 - Fractals everywhere 28:01 - Fractality, causality, and cascades 32:01 - Cascade instability as a metaphor for the brain 40:43 - Damian's worldview 46:09 - What is AI missing? 54:26 - Turbulence 1:01:02 - Intelligence without fractals? Multifractality 1:10:28 - Ergodicity 1:19:16 - Fractality, intelligence, life 1:23:24 - What's exciting, changing viewpoints ... Read more

15 Aug 2024

1 HR 27 MINS

1:27:51

15 Aug 2024

#201

BI 190 Luis Favela: The Ecological Brain

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Luis Favela is an Associate Professor at Indiana University Bloomington. He is part philosopher, part cognitive scientist, part many things, and on this episode we discuss his new book, [The Ecological Brain: Unifying the Sciences of Brain, Body, and Environment] (https://amzn.to/3LbSgrI) . In the book, Louie presents his NeuroEcological Nexus Theory, or NExT, which, as the subtitle says, proposes a way forward to tie together our brains, our bodies, and the environment; namely it has a lot to do with the complexity sciences and manifolds, which we discuss. But the book doesn't just present his theory. Among other things, it presents a rich historical look into why ecological psychology and neuroscience haven't been exactly friendly over the years, in terms of how to explain our behaviors, the role of brains in those explanations, how to think about what minds are, and so on. And it suggests how the two fields can get over their differences and be friends moving forward. And I'll just say, it's written in a very accessible manner, gently guiding the reader through many of the core concepts and science that have shaped ecological psychology and neuroscience, and for that reason alone I highly it. Ok, so we discuss a bunch of topics in the book, how Louie thinks, and Louie gives us some great background and historical lessons along the way. --- [Luis' website] (https://luishfavela.wixsite.com/luishfavela) . ---Book: ------ [The Ecological Brain: Unifying the Sciences of Brain, Body, and Environment] (https://amzn.to/3LbSgrI) 0:00 - Intro 7:05 - Louie's target with NEXT 20:37 - Ecological psychology and grid cells 22:06 - Why irreconcilable? 28:59 - Why hasn't ecological psychology evolved more? 47:13 - NExT 49:10 - Hypothesis 1 55:45 - Hypothesis 2 1:02:55 - Artificial intelligence and ecological psychology 1:16:33 - Manifolds 1:31:20 - Hypothesis 4: Body, low-D, Synergies 1:35:53 - Hypothesis 5: Mind emerges 1:36:23 - Hypothesis 6: ... Read more

31 Jul 2024

1 HR 41 MINS

1:41:03

31 Jul 2024

#200

BI 189 Joshua Vogelstein: Connectomes and Prospective Learning

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Jovo, as you'll learn, is theoretically oriented, and enjoys the formalism of mathematics to approach questions that begin with a sense of wonder. So after I learn more about his overall approach, the first topic we discuss is the world's currently largest map of an entire brain... the connectome of an insect, the fruit fly. We talk about his role in this collaborative effort, what the heck a connectome is, why it's useful and what to do with it, and so on. The second main topic we discuss is his theoretical work on what his team has called prospective learning. Prospective learning differs in a fundamental way from the vast majority of AI these days, which they call retrospective learning. So we discuss what prospective learning is, and how it may improve AI moving forward. At some point there's a little audio/video sync issues crop up, so we switched to another recording method and fixed it... so just hang tight if you're viewing the podcast... it'll get better soon. 0:00 - Intro 05:25 - Jovo's approach 13:10 - Connectome of a fruit fly 26:39 - What to do with a connectome 37:04 - How important is a connectome? 51:48 - Prospective learning 1:15:20 - Efficiency 1:17:38 - AI doomerism ... Read more

29 Jun 2024

1 HR 27 MINS

1:27:19

29 Jun 2024

#199

BI 188 Jolande Fooken: Coordinating Action and Perception

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Jolande Fooken is a post-postdoctoral researcher interested in how we move our eyes and move our hands together to accomplish naturalistic tasks. Hand-eye coordination is one of those things that sounds simple and we do it all the time to make meals for our children day in, and day out, and day in, and day out. But it becomes way less seemingly simple as soon as you learn how we make various kinds of eye movements, and how we make various kinds of hand movements, and use various strategies to do repeated tasks. And like everything in the brain sciences, it's something we don't have a perfect story for yet. So, Jolande and I discuss her work, and thoughts, and ideas around those and related topics. --- [Jolande's website] (https://ookenfooken.github.io/) . ---Twitter: [@ookenfooken] (https://twitter.com/Ookenfooken) . ---Related papers ------ [I am a parent. I am a scientist] (https://thefemalescientist.com/article/jolande-fooken/3262/i-am-a-parent-i-am-a-scientist/) . ------ [Eye movement accuracy determines natural interception strategies] (https://ookenfooken.github.io/files/FookenEtal.JoV.2016.pdf) . ------ [Perceptual-cognitive integration for goal-directed action in naturalistic environments] (https://ookenfooken.github.io/files/FookenEtAl.JNeurosci.2023.pdf) . 0:00 - Intro 3:27 - Eye movements 8:53 - Hand-eye coordination 9:30 - Hand-eye coordination and naturalistic tasks 26:45 - Levels of expertise 34:02 - Yarbus and eye movements 42:13 - Varieties of experimental paradigms, varieties of viewing the brain 52:46 - Career vision 1:04:07 - Evolving view about the brain 1:10:49 - Coordination, robots, and AI ... Read more

27 May 2024

1 HR 28 MINS

1:28:14

27 May 2024

#198

BI 187: COSYNE 2024 Neuro-AI Panel

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Recently I was invited to moderate a panel at the annual Computational and Systems Neuroscience, or COSYNE, conference. This year was the 20th anniversary of COSYNE, and we were in Lisbon Porturgal. The panel goal was to discuss the relationship between neuroscience and AI. The panelists were Tony Zador, Alex Pouget, Blaise Aguera y Arcas, Kim Stachenfeld, Jonathan Pillow, and Eva Dyer. And I'll let them introduce themselves soon. Two of the panelists, Tony and Alex, co-founded COSYNE those 20 years ago, and they continue to have different views about the neuro-AI relationship. Tony has been on the podcast before and will return soon, and I'll also have Kim Stachenfeld on in a couple episodes. I think this was a fun discussion, and I hope you enjoy it. There's plenty of back and forth, a wide range of opinions, and some criticism from one of the audience questioners. This is an edited audio version, to remove long dead space and such. There's about 30 minutes of just panel, then the panel starts fielding questions from the audience. --- [COSYNE] (https://www.cosyne.org/) . ... Read more

20 Apr 2024

1 HR 03 MINS

1:03:35

20 Apr 2024

#197

BI 186 Mazviita Chirimuuta: The Brain Abstracted

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Mazviita Chirimuuta is a philosopher at the University of Edinburgh. Today we discuss topics from her new book, [The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience] (https://mitpress.mit.edu/9780262548045/the-brain-abstracted/) . She largely argues that when we try to understand something complex, like the brain, using models, and math, and analogies, for example - we should keep in mind these are all ways of simplifying and abstracting away details to give us something we actually can understand. And, when we do science, every tool we use and perspective we bring, every way we try to attack a problem, these are all both necessary to do the science and limit the interpretation we can claim from our results. She does all this and more by exploring many topics in neuroscience and philosophy throughout the book, many of which we discuss today. --- [Mazviita's University of Edinburgh page] (https://www.ed.ac.uk/profile/mazviita-chirimuuta) . --- [The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience] (https://mitpress.mit.edu/9780262548045/the-brain-abstracted/) . ---Previous Brain Inspired episodes: ------ [BI 072 Mazviita Chirimuuta: Understanding, Prediction, and Reality] (https://braininspired.co/podcast/72/) ------ [BI 114 Mark Sprevak and Mazviita Chirimuuta: Computation and the Mind] (https://braininspired.co/podcast/114/) 0:00 - Intro 5:28 - Neuroscience to philosophy 13:39 - Big themes of the book 27:44 - Simplifying by mathematics 32:19 - Simplifying by reduction 42:55 - Simplification by analogy 46:33 - Technology precedes science 55:04 - Theory, technology, and understanding 58:04 - Cross-disciplinary progress 58:45 - Complex vs. simple(r) systems 1:08:07 - Is science bound to study stability? 1:13:20 - 4E for philosophy but not neuroscience? 1:28:50 - ANNs as models 1:38:38 - Study of mind ... Read more

25 Mar 2024

1 HR 43 MINS

1:43:34

25 Mar 2024

#196

BI 185 Eric Yttri: Orchestrating Behavior

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> As some of you know, I recently got back into the research world, and in particular I work in Eric Yttris' lab at Carnegie Mellon University. Eric's lab studies the relationship between various kinds of behaviors and the neural activity in a few areas known to be involved in enacting and shaping those behaviors, namely the motor cortex and basal ganglia. And study that, he uses tools like optogentics, neuronal recordings, and stimulations, while mice perform certain tasks, or, in my case, while they freely behave wandering around an enclosed space. We talk about how Eric got here, how and why the motor cortex and basal ganglia are still mysteries despite lots of theories and experimental work, Eric's work on trying to solve those mysteries using both trained tasks and more naturalistic behavior. We talk about the valid question, "What is a behavior?", and lots more. [Yttri Lab] (https://labs.bio.cmu.edu/yttri/) ---Twitter: [@YttriLab] (https://twitter.com/YttriLab) ---Related papers ------ [Opponent and bidirectional control of movement velocity in the basal ganglia] (https://pubmed.ncbi.nlm.nih.gov/27135927/) . ------ [B-SOiD, an open-source unsupervised algorithm for identification and fast prediction of behaviors] (https://www.nature.com/articles/s41467-021-25420-x?proof=tr) . 0:00 - Intro 2:36 - Eric's background 14:47 - Different animal models 17:59 - ANNs as models for animal brains 24:34 - Main question 25:43 - How circuits produce appropriate behaviors 26:10 - Cerebellum 27:49 - What do motor cortex and basal ganglia do? 49:12 - Neuroethology 1:06:09 - What is a behavior? 1:11:18 - Categorize behavior (B-SOiD) 1:22:01 - Real behavior vs. ANNs 1:33:09 - Best era in neuroscience ... Read more

06 Mar 2024

1 HR 44 MINS

1:44:50

06 Mar 2024

#195

BI 184 Peter Stratton: Synthesize Neural Principles

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Peter Stratton is a research scientist at Queensland University of Technology. I was pointed toward Pete by a patreon supporter, who sent me a sort of perspective piece Pete wrote that is the main focus of our conversation, although we also talk about some of his work in particular - for example, he works with spiking neural networks, like my last guest, [Dan Goodman] (https://braininspired.co/podcast/183/) . What Pete argues for is what he calls a sideways-in approach. So a bottom-up approach is to build things like we find them in the brain, put them together, and voila, we'll get cognition. A top-down approach, the current approach in AI, is to train a system to perform a task, give it some algorithms to run, and fiddle with the architecture and lower level details until you pass your favorite benchmark test. Pete is focused more on the principles of computation brains employ that current AI doesn't. If you're familiar with David Marr, this is akin to his so-called "algorithmic level", but it's between that and the "implementation level", I'd say. Because Pete is focused on the synthesis of different kinds of brain operations - how they intermingle to perform computations and produce emergent properties. So he thinks more like a systems neuroscientist in that respect. Figuring that out is figuring out how to make better AI, Pete says. So we discuss a handful of those principles, all through the lens of how challenging a task it is to synthesize multiple principles into a coherent functioning whole (as opposed to a collection of parts). Buy, hey, evolution did it, so I'm sure we can, too, right? --- [Peter's website] (http://neuro-ai.info/index.html) . ---Related papers ------ [Convolutionary, Evolutionary, and Revolutionary: What’s Next for Brains, Bodies, and AI?] (https://link.springer.com/article/10.1007/s12559-023-10181-0) ------ [Making a Spiking Net Work: Robust brain-like unsupervised machine learning] (https://arxiv.org/abs/2208.01204) . ------ [Global segregation of cortical activity and metastable dynamics] (https://www.frontiersin.org/articles/10.3389/fnsys.2015.00119/full) . ------ [Unlocking neural complexity with a robotic key] (https://physoc.onlinelibrary.wiley.com/doi/am-pdf/10.1113/jp271444) 0:00 - Intro 3:50 - AI background, neuroscience principles 8:00 - Overall view of modern AI 14:14 - Moravec's paradox and robotics 20:50 -Understanding movement to understand cognition 30:01 - How close are we to understanding brains/minds? 32:17 - Pete's goal 34:43 - Principles from neuroscience to build AI 42:39 - Levels of abstraction and implementation 49:57 - Mental disorders and robustness 55:58 - Function vs. implementation 1:04:04 - Spiking networks 1:07:57 - The roadmap 1:19:10 - AGI 1:23:48 - The terms AGI and AI 1:26:12 - Consciousness ... Read more

20 Feb 2024

1 HR 30 MINS

1:30:47

20 Feb 2024

#194

BI 183 Dan Goodman: Neural Reckoning

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> You may know my guest as the co-founder of Neuromatch, the excellent online computational neuroscience academy, or as the creator of the Brian spiking neural network simulator, which is freely available. I know him as a spiking neural network practitioner extraordinaire. Dan Goodman runs the Neural Reckoning Group at Imperial College London, where they use spiking neural networks to figure out how biological and artificial brains reckon, or compute. All of the current AI we use to do all the impressive things we do, essentially all of it, is built on artificial neural networks. Notice the word "neural" there. That word is meant to communicate that these artificial networks do stuff the way our brains do stuff. And indeed, if you take a few steps back, spin around 10 times, take a few shots of whiskey, and squint hard enough, there is a passing resemblance. One thing you'll probably still notice, in your drunken stupor, is that, among the thousand ways ANNs differ from brains, is that they don't use action potentials, or spikes. From the perspective of neuroscience, that can seem mighty curious. Because, for decades now, neuroscience has focused on spikes as the things that make our cognition tick. We count them and compare them in different conditions, and generally put a lot of stock in their usefulness in brains. So what does it mean that modern neural networks disregard spiking altogether? Maybe spiking really isn't important to process and transmit information as well as our brains do. Or maybe spiking is one among many ways for intelligent systems to function well. Dan shares some of what he's learned and how he thinks about spiking and SNNs and a host of other topics. --- [Neural Reckoning Group] (https://neural-reckoning.org/) . ---Twitter: [@neuralreckoning] (https://twitter.com/neuralreckoning) . ---Related papers ------ [Neural heterogeneity promotes robust learning] (https://www.nature.com/articles/s41467-021-26022-3.pdf) . ------ [Dynamics of specialization in neural modules under resource constraints] (https://arxiv.org/abs/2106.02626) . ------ [Multimodal units fuse-then-accumulate evidence across channels] (https://neural-reckoning.org/pub_multimodal.html) . ------ [Visualizing a joint future of neuroscience and neuromorphic engineering] (https://www.dropbox.com/s/942rf97l80wyya5/snufa-meeting-report.pdf?dl=1) . 0:00 - Intro 3:47 - Why spiking neural networks, and a mathematical background 13:16 - Efficiency 17:36 - Machine learning for neuroscience 19:38 - Why not jump ship from SNNs? 23:35 - Hard and easy tasks 29:20 - How brains and nets learn 32:50 - Exploratory vs. theory-driven science 37:32 - Static vs. dynamic 39:06 - Heterogeneity 46:01 - Unifying principles vs. a hodgepodge 50:37 - Sparsity 58:05 - Specialization and modularity 1:00:51 - Naturalistic experiments 1:03:41 - Projects for SNN research 1:05:09 - The right level of abstraction 1:07:58 - Obstacles to progress 1:12:30 - Levels of explanation 1:14:51 - What has AI taught neuroscience? 1:22:06 - How has neuroscience helped AI? ... Read more

06 Feb 2024

1 HR 28 MINS

1:28:54

06 Feb 2024

#193

BI 182: John Krakauer Returns… Again

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> [Check out my free video series about what's missing in AI and Neuroscience] (https://braininspired.co/open/) <a href="https://braininspired.co/open/" target="_blank" rel="noreferrer noopener"></a> John Krakauer has been on the podcast multiple times (see links below). Today we discuss some topics framed around what he's been working on and thinking about lately. Things like ---Whether brains actually reorganize after damage ---The role of brain plasticity in general ---The path toward and the path not toward understanding higher cognition ---How to fix motor problems after strokes ---AGI ---Functionalism, consciousness, and much more. Relevant links: --- [John's Lab.] (http://blam-lab.org) ---Twitter: [@blamlab] (https://twitter.com/blamlab) ---Related papers ------ [What are we talking about? Clarifying the fuzzy concept of representation in neuroscience and beyond] (https://www.thetransmitter.org/representation/what-are-we-talking-about-clarifying-the-fuzzy-concept-of-representation-in-neuroscience-and-beyond/) . ------ [Against cortical reorganisation] (https://elifesciences.org/articles/84716) . ---Other episodes with John: ------ [BI 025 John Krakauer: Understanding Cognition] (https://braininspired.co/podcast/25/) ------ [BI 077 David and John Krakauer: Part 1] (https://braininspired.co/podcast/77/) ------ [BI 078 David and John Krakauer: Part 2] (https://braininspired.co/podcast/78/) ------ [BI 113 David Barack and John Krakauer: Two Views On Cognition] (https://braininspired.co/podcast/113/) Time stamps 0:00 - Intro 2:07 - It's a podcast episode! 6:47 - Stroke and Sherrington neuroscience 19:26 - Thinking vs. moving, representations 34:15 - What's special about humans? 56:35 - Does cortical reorganization happen? 1:14:08 - Current era in neuroscience ... Read more

19 Jan 2024

1 HR 25 MINS

1:25:42

19 Jan 2024

#192

BI 181 Max Bennett: A Brief History of Intelligence

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> [Check out my free video series about what's missing in AI and Neuroscience] (https://braininspired.co/open/) <a href="https://braininspired.co/open/" target="_blank" rel="noreferrer noopener"></a> By day, Max Bennett is an entrepreneur. He has cofounded and CEO'd multiple AI and technology companies. By many other countless hours, he has studied brain related sciences. Those long hours of research have payed off in the form of this book, [A Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains.] (https://amzn.to/3RSy0iQ) Three lines of research formed the basis for how Max synthesized knowledge into the ideas in his current book: findings from comparative psychology (comparing brains and minds of different species), evolutionary neuroscience (how brains have evolved), and artificial intelligence, especially the algorithms developed to carry out functions. We go through I think all five of the breakthroughs in some capacity. A recurring theme is that each breakthrough may explain multiple new abilities. For example, the evolution of the neocortex may have endowed early mammals with the ability to simulate or imagine what isn't immediately present, and this ability might further explain mammals' capacity to engage in vicarious trial and error (imagining possible actions before trying them out), the capacity to engage in counterfactual learning (what would have happened if things went differently than they did), and the capacity for episodic memory and imagination. The book is filled with unifying accounts like that, and it makes for a great read. Strap in, because Max gives a sort of masterclass about many of the ideas in his book. ---Twitter: ------ [@maxsbennett] (https://twitter.com/maxsbennett) ---Book: ------ [A Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains] (https://amzn.to/3RSy0iQ) . 0:00 - Intro 5:26 - Why evolution is important 7:22 - Maclean's triune brain 14:59 - Breakthrough 1: Steering 29:06 - Fish intelligence 40:38 - Breakthrough 3: Mentalizing 52:44 - How could we improve the human brain? 1:00:44 - What is intelligence? 1:13:50 - Breakthrough 5: Speaking ... Read more

25 Dec 2023

1 HR 27 MINS

1:27:30

25 Dec 2023

#191

BI 180 Panel Discussion: Long-term Memory Encoding and Connectome Decoding

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Welcome to another special panel discussion episode. I was recently invited to moderate at discussion amongst 6 people at the annual Aspirational Neuroscience meetup. Aspirational Neuroscience is a nonprofit community run by Kenneth Hayworth. Ken has been on the podcast before [on episode 103] (https://braininspired.co/podcast/103/) . Ken helps me introduce the meetup and panel discussion for a few minutes. The goal in general was to discuss how current and developing neuroscience technologies might be used to decode a nontrivial memory from a static connectome - what the obstacles are, how to surmount those obstacles, and so on. There isn't video of the event, just audio, and because we were all sharing microphones and they were being passed around, you'll hear some microphone type noise along the way - but I did my best to optimize the audio quality, and it turned out mostly quite listenable I believe. --- [Aspirational Neuroscience] (https://aspirationalneuroscience.org/) ---Panelists: ------ [Anton Arkhipov] (https://alleninstitute.org/person/anton-arkhipov/) , Allen Institute for Brain Science. --------- [@AntonSArkhipov] (https://twitter.com/AntonSArkhipov) ------ [Konrad Kording] (http://koerding.com/) , University of Pennsylvania. --------- [@KordingLab] (https://twitter.com/KordingLab) ------ [Tomás Ryan] (https://www.tcd.ie/research/profiles/?profile=tryan6) , Trinity College Dublin. --------- [@TJRyan_77] (https://twitter.com/TJRyan_77) ------ [Srinivas Turaga] (https://www.janelia.org/people/srinivas-turaga) , Janelia Research Campus. ------ [Dong Song] (https://viterbi.usc.edu/directory/faculty/Song/Dong) , University of Southern California. --------- [@dongsong] (https://twitter.com/dongsong) ------ [Zhihao Zheng] (https://pni.princeton.edu/people/zhihao-zheng) , Princeton University. --------- [@zhihaozheng] (https://twitter.com/zhihaozheng) 0:00 - Intro 1:45 - Ken Hayworth 14:09 - Panel Discussion ... Read more

11 Dec 2023

1 HR 29 MINS

1:29:27

11 Dec 2023

#190

BI 179 Laura Gradowski: Include the Fringe with Pluralism

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> [Check out my free video series about what's missing in AI and Neuroscience] (https://braininspired.co/open/) <a href="https://braininspired.co/open/" target="_blank" rel="noreferrer noopener"></a> Laura Gradowski is a philosopher of science at the University of Pittsburgh. Pluralism is roughly the idea that there is no unified account of any scientific field, that we should be tolerant of and welcome a variety of theoretical and conceptual frameworks, and methods, and goals, when doing science. Pluralism is kind of a buzz word right now in my little neuroscience world, but it's an old and well-trodden notion... many philosophers have been calling for pluralism for many years. But how pluralistic should we be in our studies and explanations in science? Laura suggests we should be very, very pluralistic, and to make her case, she cites examples in the history of science of theories and theorists that were once considered "fringe" but went on to become mainstream accepted theoretical frameworks. I thought it would be fun to have her on to share her ideas about fringe theories, mainstream theories, pluralism, etc. We discuss a wide range of topics, but also discuss some specific to the brain and mind sciences. Laura goes through an example of something and someone going from fringe to mainstream - the Garcia effect, named after John Garcia, whose findings went agains the grain of behaviorism, the dominant dogma of the day in psychology. But this overturning only happened after Garcia had to endure a long scientific hell of his results being ignored and shunned. So, there are multiple examples like that, and we discuss a handful. This has led Laura to the conclusion we should accept almost all theoretical frameworks, We discuss her ideas about how to implement this, where to draw the line, and much more. <li> [Laura's page] (https://www.centerphilsci.pitt.edu/fellows/gradowski-laura/) at the Center for the Philosophy of Science at the University of Pittsburgh. </li> <li> [Facing the Fringe] (https://www.proquest.com/docview/2726491918?pq-origsite=gscholar&fromopenview=true) .</li> <li>Garcia's reflections on his troubles: [Tilting at the Paper Mills of Academe] (https://www.appstate.edu/~steelekm/classes/psy5150/Documents/Garcia1981-tilting-at.pdf) </li> 0:00 - Intro 3:57 - What is fringe? 10:14 - What makes a theory fringe? 14:31 - Fringe to mainstream 17:23 - Garcia effect 28:17 - Fringe to mainstream: other examples 32:38 - Fringe and consciousness 33:19 - Words meanings change over time 40:24 - Pseudoscience 43:25 - How fringe becomes mainstream 47:19 - More fringe characteristics 50:06 - Pluralism as a solution 54:02 - Progress 1:01:39 - Encyclopedia of theories 1:09:20 - When to reject a theory 1:20:07 - How fringe becomes fringe 1:22:50 - Marginilization 1:27:53 - Recipe for fringe theorist ... Read more

27 Nov 2023

1 HR 39 MINS

1:39:06

27 Nov 2023

#189

BI 178 Eric Shea-Brown: Neural Dynamics and Dimensions

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> [Check out my free video series about what's missing in AI and Neuroscience] (https://braininspired.co/open/) <a href="https://braininspired.co/open/" target="_blank" rel="noreferrer noopener"></a> Eric Shea-Brown is a theoretical neuroscientist and principle investigator of the working group on neural dynamics at the University of Washington. In this episode, we talk a lot about dynamics and dimensionality in neural networks... how to think about them, why they matter, how Eric's perspectives have changed through his career. We discuss a handful of his specific research findings about dynamics and dimensionality, like how dimensionality changes when one is performing a task versus when you're just sort of going about your day, what we can say about dynamics just by looking at different structural connection motifs, how different modes of learning can rely on different dimensionalities, and more.We also talk about how he goes about choosing what to work on and how to work on it. You'll hear in our discussion how much credit Eric gives to those surrounding him and those who came before him - he drops tons of references and names, so get ready if you want to follow up on some of the many lines of research he mentions. --- [Eric's website] (http://faculty.washington.edu/etsb/) . ---Related papers ------ [Predictive learning as a network mechanism for extracting low-dimensional latent space representations] (https://www.nature.com/articles/s41467-021-21696-1) . ------ [A scale-dependent measure of system dimensionality] (https://www.cell.com/patterns/pdf/S2666-3899(22)00160-X.pdf) . ------ [From lazy to rich to exclusive task representations in neural networks and neural codes] (https://www.sciencedirect.com/science/article/pii/S0959438823001058) . ------ [Feedback through graph motifs relates structure and function in complex networks] (http://arxiv.org/abs/1605.09073) . 0:00 - Intro 4:15 - Reflecting on the rise of dynamical systems in neuroscience 11:15 - DST view on macro scale 15:56 - Intuitions 22:07 - Eric's approach 31:13 - Are brains more or less impressive to you now? 38:45 - Why is dimensionality important? 50:03 - High-D in Low-D 54:14 - Dynamical motifs 1:14:56 - Theory for its own sake 1:18:43 - Rich vs. lazy learning 1:22:58 - Latent variables 1:26:58 - What assumptions give you most pause? ... Read more

13 Nov 2023

1 HR 35 MINS

1:35:31

13 Nov 2023

#188

BI 177 Special: Bernstein Workshop Panel

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> 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?] (https://bernstein-network.de/bernstein-conference/program/satellite-workshops/machine-learning/) Below are the panelists. I hope you enjoy the discussion! ---Program: [How can machine learning be used to generate insights and theories in neuroscience?] (https://bernstein-network.de/bernstein-conference/program/satellite-workshops/machine-learning/) ---Panelists: ------Katrin Franke --------- [Lab website] (https://www.eye-tuebingen.de/franke/) . ---------Twitter: [@kfrankelab] (https://twitter.com/kfrankelab) . ------Ralf Haefner --------- [Haefner lab] (https://www2.bcs.rochester.edu/sites/haefnerlab/index.html) . ---------Twitter: [@haefnerlab] (https://twitter.com/haefnerlab) . ------Martin Hebart --------- [Hebart Lab] (https://hebartlab.com/) . ---------Twitter: [@martin_hebart] (https://twitter.com/martin_hebart) . ------Johannes Jaeger --------- [Yogi's website] (http://www.johannesjaeger.eu/) . ---------Twitter: [@yoginho] (https://twitter.com/yoginho) . ------Fred Wolf --------- [Fred's university webpage] (https://www.uni-goettingen.de/en/58058.html) . Organizers: ---Alexander Ecker | University of Göttingen, Germany ---Fabian Sinz | University of Göttingen, Germany ---Mohammad Bashiri, Pavithra Elumalai, Michaela Vystrcilová | University of Göttingen, Germany ... Read more

30 Oct 2023

1 HR 13 MINS

1:13:54

30 Oct 2023

#187

BI 176 David Poeppel Returns

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> David runs [his lab at NYU] (http://psych.nyu.edu/clash/poeppellab/) , where they stud`y auditory cognition, speech perception, language, and music. On the heels of the [episode with David Glanzman] (https://braininspired.co/podcast/172/) , we discuss the ongoing mystery regarding how memory works, how to study and think about brains and minds, and the reemergence (perhaps) of the language of thought hypothesis. David has been on the podcast a few times... [once by himself] (https://braininspired.co/podcast/46/) , and [again with Gyorgy Buzsaki] (https://braininspired.co/podcast/84/) . --- [Poeppel lab] (http://psych.nyu.edu/clash/poeppellab/) ---Twitter: [@davidpoeppel] (https://twitter.com/davidpoeppel) . ---Related papers ------ [We don’t know how the brain stores anything, let alone words] (https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(22)00206-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1364661322002066%3Fshowall%3Dtrue) . ------ [Memory in humans and deep language models: Linking hypotheses for model augmentation.] (https://arxiv.org/pdf/2210.01869.pdf) ------ [The neural ingredients for a language of thought are available.] (https://www.sciencedirect.com/science/article/abs/pii/S1364661323001936) 0:00 - Intro 11:17 - Across levels 14:598 - Nature of memory 24:12 - Using the right tools for the right question 35:46 - LLMs, what they need, how they've shaped David's thoughts 44:55 - Across levels 54:07 - Speed of progress 1:02:21 - Neuroethology and mental illness - patreon 1:24:42 - Language of Thought ... Read more

14 Oct 2023

1 HR 23 MINS

1:23:57

14 Oct 2023

#186

BI 175 Kevin Mitchell: Free Agents

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> [Check out my free video series about what's missing in AI and Neuroscience] (https://braininspired.co/open/) <a href="https://braininspired.co/open/" target="_blank" rel="noreferrer noopener"></a> Kevin Mitchell is professor of genetics at Trinity College Dublin. He's [been on the podcast before] (https://braininspired.co/podcast/111/) , and we talked a little about his previous book, Innate – How the Wiring of Our Brains Shapes Who We Are. He's back today to discuss his new book [Free Agents: How Evolution Gave Us Free Will] (https://amzn.to/3thGq9V) . The book is written very well and guides the reader through a wide range of scientific knowledge and reasoning that undergirds Kevin's main take home: our free will comes from the fact that we are biological organisms, biological organisms have agency, and as that agency evolved to become more complex and layered, so does our ability to exert free will. We touch on a handful of topics in the book, like the idea of agency, how it came about at the origin of life, and how the complexity of kinds of agency, the richness of our agency, evolved as organisms became more complex. We also discuss Kevin's reliance on the indeterminacy of the universe to tell his story, the underlying randomness at fundamental levels of physics. Although indeterminacy isn't necessary for ongoing free will, it is responsible for the capacity for free will to exist in the first place. We discuss the brain's ability to harness its own randomness when needed, creativity, whether and how it's possible to create something new, artificial free will, and lots more. --- [Kevin's website] (https://www.kjmitchell.com/) . ---Twitter: [@WiringtheBrain] (https://twitter.com/WiringTheBrain?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor) ---Book: [Free Agents: How Evolution Gave Us Free Will] (https://amzn.to/3thGq9V) 4:27 - From Innate to Free Agents 9:14 - Thinking of the whole organism 15:11 - Who the book is for 19:49 - What bothers Kevin 27:00 - Indeterminacy 30:08 - How it all began 33:08 - How indeterminacy helps 43:58 - Libet's free will experiments 50:36 - Creativity 59:16 - Selves, subjective experience, agency, and free will 1:10:04 - Levels of agency and free will 1:20:38 - How much free will can we have? 1:28:03 - Hierarchy of mind constraints 1:36:39 - Artificial agents and free will 1:42:57 - Next book? ... Read more

03 Oct 2023

1 HR 46 MINS

1:46:32

03 Oct 2023

#185

BI 174 Alicia Juarrero: Context Changes Everything

[Check out my free video series about what's missing in AI and Neuroscience] (https://braininspired.co/open/) <a href="https://braininspired.co/open/" target="_blank" rel="noreferrer noopener"></a> [Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> Alicia Juarrero is a philosopher and has been interested in complexity since before it was cool. In this episode, we discuss many of the topics and ideas in her new book, [Context Changes Everything: How Constraints Create Coherence] (https://mitpress.mit.edu/9780262545662/context-changes-everything/) , which makes the thorough case that constraints should be given way more attention when trying to understand complex systems like brains and minds - how they're organized, how they operate, how they're formed and maintained, and so on. Modern science, thanks in large part to the success of physics, focuses on a single kind of causation - the kind involved when one billiard ball strikes another billiard ball. But that kind of causation neglects what Alicia argues are the most important features of complex systems the constraints that shape the dynamics and possibility spaces of systems. Much of Alicia's book describes the wide range of types of constraints we should be paying attention to, and how they interact and mutually influence each other. I highly recommend the book, and you may want to read it before, during, and after our conversation. That's partly because, if you're like me, the concepts she discusses still aren't comfortable to think about the way we're used to thinking about how things interact. Thinking across levels of organization turns out to be hard. You might also want her book handy because, hang on to your hats, we jump around a lot among those concepts. Context Changes everything comes about 25 years after her previous classic, Dynamics In Action, which we also discuss and which I also recommend if you want more of a primer to her newer more expansive work. Alicia's work touches on all things complex, from self-organizing systems like whirlpools, to ecologies, businesses, societies, and of course minds and brains. ---Book: ------ [Context Changes Everything: How Constraints Create Coherence] (https://mitpress.mit.edu/9780262545662/context-changes-everything/) 0:00 - Intro 3:37 - 25 years thinking about constraints 8:45 - Dynamics in Action and eliminativism 13:08 - Efficient and other kinds of causation 19:04 - Complexity via context independent and dependent constraints 25:53 - Enabling and limiting constraints 30:55 - Across scales 36:32 - Temporal constraints 42:58 - A constraint cookbook? 52:12 - Constraints in a mechanistic worldview 53:42 - How to explain using constraints 56:22 - Concepts and multiple realizabillity 59:00 - Kevin Mitchell question 1:08:07 - Mac Shine Question 1:19:07 - 4E 1:21:38 - Dimensionality across levels 1:27:26 - AI and constraints 1:33:08 - AI and life ... Read more

13 Sep 2023

1 HR 45 MINS

1:45:00

13 Sep 2023

#184

BI 173 Justin Wood: Origins of Visual Intelligence

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> In the intro, I mention the Bernstein conference workshop I'll participate in, called [How can machine learning be used to generate insights and theories in neuroscience?] (https://bernstein-network.de/bernstein-conference/program/satellite-workshops/machine-learning/) . Follow that link to learn more, and [register for the conference here] (https://bernstein-network.de/bernstein-conference/registration/) . Hope to see you there in late September in Berlin! Justin Wood runs the Wood Lab at Indiana University, and his lab's tagline is "building newborn minds in virtual worlds." In this episode, we discuss his work comparing the visual cognition of newborn chicks and AI models. He uses a controlled-rearing technique with natural chicks, whereby the chicks are raised from birth in completely controlled visual environments. That way, Justin can present designed visual stimuli to test what kinds of visual abilities chicks have or can immediately learn. Then he can building models and AI agents that are trained on the same data as the newborn chicks. The goal is to use the models to better understand natural visual intelligence, and use what we know about natural visual intelligence to help build systems that better emulate biological organisms. We discuss some of the visual abilities of the chicks and what he's found using convolutional neural networks. Beyond vision, we discuss his work studying the development of collective behavior, which compares chicks to a model that uses CNNs, reinforcement learning, and an intrinsic curiosity reward function. All of this informs the age-old nature (nativist) vs. nurture (empiricist) debates, which Justin believes should give way to embrace both nature and nurture. --- [Wood lab] (http://buildingamind.com/) . ---Related papers: ------ [Controlled-rearing studies of newborn chicks and deep neural networks] (https://arxiv.org/abs/2112.06106) . ------ [Development of collective behavior in newborn artificial agents] (https://arxiv.org/abs/2111.03796) . ------ [A newborn embodied Turing test for view-invariant object recognition] (https://arxiv.org/abs/2306.05582) . ---Justin mentions these papers: ------ [Untangling invariant object recognition (Dicarlo & Cox 2007)] (https://www.cns.nyu.edu/~tony/vns/readings/dicarlo-cox-2007.pdf) 0:00 - Intro 5:39 - Origins of Justin's current research 11:17 - Controlled rearing approach 21:52 - Comparing newborns and AI models 24:11 - Nativism vs. empiricism 28:15 - CNNs and early visual cognition 29:35 - Smoothness and slowness 50:05 - Early biological development 53:27 - Naturalistic vs. highly controlled 56:30 - Collective behavior in animals and machines 1:02:34 - Curiosity and critical periods 1:09:05 - Controlled rearing vs. other developmental studies 1:13:25 - Breaking natural rules 1:16:33 - Deep RL collective behavior 1:23:16 - Bottom-up and top-down ... Read more

30 Aug 2023

1 HR 35 MINS

1:35:45

30 Aug 2023

#183

BI 172 David Glanzman: Memory All The Way Down

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> David runs his lab at UCLA where he's also a distinguished professor. David used to believe what is currently the mainstream view, that our memories are stored in our synapses, those connections between our neurons. So as we learn, the synaptic connections strengthen and weaken until their just right, and that serves to preserve the memory. That's been the dominant view in neuroscience for decades, and is the fundamental principle that underlies basically all of deep learning in AI. But because of his own and others experiments, which he describes in this episode, David has come to the conclusion that memory must be stored not at the synapse, but in the nucleus of neurons, likely by some epigenetic mechanism mediated by RNA molecules. If this sounds familiar, I had Randy Gallistel on the the podcast on episode 126 to discuss similar ideas, and David discusses where he and Randy differ in their thoughts. This episode starts out pretty technical as David describes the series of experiments that changed his mind, but after that we broaden our discussion to a lot of the surrounding issues regarding whether and if his story about memory is true. And we discuss meta-issues like how old discarded ideas in science often find their way back, what it's like studying non-mainstream topic, including challenges trying to get funded for it, and so on. --- [David's Faculty Page] (https://www.ibp.ucla.edu/faculty/david-glanzman/) . ---Related papers ------ [The central importance of nuclear mechanisms in the storage of memory] (https://www.sciencedirect.com/science/article/abs/pii/S0006291X21007518) . ------David mentions Arc and virus-like transmission: --------- [The Neuronal Gene Arc Encodes a Repurposed Retrotransposon Gag Protein that Mediates Intercellular RNA Transfer] (https://www.cell.com/cell/fulltext/S0092-8674(17)31504-0) . --------- [Structure of an Arc-ane virus-like capsid] (https://pubmed.ncbi.nlm.nih.gov/31953526/) . ---David mentions many of the ideas from the [Pushing the Boundaries: Neuroscience, Cognition, and Life] (https://2023symposium.ibp.ucla.edu/) Symposium. ---Related episodes: ------ [BI 126 Randy Gallistel: Where Is the Engram?] (https://braininspired.co/podcast/126/) ------ [BI 127 Tomás Ryan: Memory, Instinct, and Forgetting] (https://braininspired.co/podcast/127/) ... Read more

07 Aug 2023

1 HR 30 MINS

1:30:58

07 Aug 2023

#182

BI 171 Mike Frank: Early Language and Cognition

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> [Check out my free video series about what's missing in AI and Neuroscience] (https://braininspired.co/open/) <a href="https://braininspired.co/open/" target="_blank" rel="noreferrer noopener"></a> My guest is Michael C. Frank, better known as Mike Frank, who runs the Language and Cognition lab at Stanford. Mike's main interests center on how children learn language - in particular he focuses a lot on early word learning, and what that tells us about our other cognitive functions, like concept formation and social cognition. We discuss that, his love for developing open data sets that anyone can use, The dance he dances between bottom-up data-driven approaches in this big data era, traditional experimental approaches, and top-down theory-driven approaches How early language learning in children differs from LLM learning Mike's rational speech act model of language use, which considers the intentions or pragmatics of speakers and listeners in dialogue. --- [Language & Cognition Lab] (https://langcog.stanford.edu/) ---Twitter: [@mcxfrank] (https://twitter.com/mcxfrank) . ------I mentioned Mike's [tweet thread] (https://twitter.com/mcxfrank/status/1643296168276033538) about saying LLMs "have" cognitive functions: ---Related papers: ------ [Pragmatic language interpretation as probabilistic inference.] (http://langcog.stanford.edu/papers_new/goodman-2016-tics.pdf) ------ [Toward a “Standard Model” of Early Language Learning.] (https://psyarxiv.com/yhrb4) ------ [The pervasive role of pragmatics in early language.] (https://psyarxiv.com/v8e56/) ------ [The Structure of Developmental Variation in Early Childhood.] (https://psyarxiv.com/95erq) ------ [Relational reasoning and generalization using non-symbolic neural networks.] (https://arxiv.org/pdf/2006.07968.pdf) ------ [Unsupervised neural network models of the ventral visual stream.] (https://www.pnas.org/doi/10.1073/pnas.2014196118) ... Read more

22 Jul 2023

1 HR 24 MINS

1:24:40

22 Jul 2023

#181

BI 170 Ali Mohebi: Starting a Research Lab

[Support the show] (https://www.patreon.com/braininspired) to get full episodes and join the Discord community. <a href="https://www.patreon.com/braininspired"></a> [Check out my free video series about what's missing in AI and Neuroscience] (https://braininspired.co/open/) <a href="https://braininspired.co/open/" target="_blank" rel="noreferrer noopener"></a> In this episode I have a casual chat with Ali Mohebi about his new faculty position and his plans for the future. --- [Ali's website] (https://mohebial.com/) . ---Twitter: [@mohebial] (https://twitter.com/mohebial) ... Read more

11 Jul 2023

1 HR 17 MINS

1:17:15

11 Jul 2023

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#210

BI 199 Hessam Akhlaghpour: Natural Universal Computation

#209

BI 198 Tony Zador: Neuroscience Principles to Improve AI

#208

BI 197 Karen Adolph: How Babies Learn to Move and Think

#207

BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød

#206

BI 195 Ken Harris and Andreas Tolias with Gaute Einevoll and Mikkel Lepperød

#205

BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting

#204

BI 193 Kim Stachenfeld: Enhancing Neuroscience and AI

#203

BI 192 Àlex Gómez-Marín: The Edges of Consciousness

#202

BI 191 Damian Kelty-Stephen: Fractal Turbulent Cascading Intelligence

#201

BI 190 Luis Favela: The Ecological Brain

#200

BI 189 Joshua Vogelstein: Connectomes and Prospective Learning

#199

BI 188 Jolande Fooken: Coordinating Action and Perception

#198

BI 187: COSYNE 2024 Neuro-AI Panel

#197

BI 186 Mazviita Chirimuuta: The Brain Abstracted

#196

BI 185 Eric Yttri: Orchestrating Behavior

#195

BI 184 Peter Stratton: Synthesize Neural Principles

#194

BI 183 Dan Goodman: Neural Reckoning

#193

BI 182: John Krakauer Returns… Again

#192

BI 181 Max Bennett: A Brief History of Intelligence

#191

BI 180 Panel Discussion: Long-term Memory Encoding and Connectome Decoding

#190

BI 179 Laura Gradowski: Include the Fringe with Pluralism

#189

BI 178 Eric Shea-Brown: Neural Dynamics and Dimensions

#188

BI 177 Special: Bernstein Workshop Panel

#187

BI 176 David Poeppel Returns

#186

BI 175 Kevin Mitchell: Free Agents

#185

BI 174 Alicia Juarrero: Context Changes Everything

#184

BI 173 Justin Wood: Origins of Visual Intelligence

#183

BI 172 David Glanzman: Memory All The Way Down

#182

BI 171 Mike Frank: Early Language and Cognition

#181

BI 170 Ali Mohebi: Starting a Research Lab