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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

01:22:30

BI 026 Kendrick Kay: A Model By Any Other Name

Brain Inspired ·

2019/01/31

Image courtesy of Kendrick Kay:Brain art Show notes: Check out Kendrick’s lab website: CVN lab. Follow him on twitter: @cvnlab. The papers we discuss: Bottom-up and top-down computations in word- and face-selective cortex. Principles for models of neural information processing. Appreciating diversity of goals in computational neuroscience. A nice talk about the model we discuss:Bottom Up and Top Down Computations in Word- and Face-Selective Cortex Cognitive Computational

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01:46:16

BI 025 John Krakauer: Understanding Cognition

Brain Inspired ·

2019/01/25

Show notes BLAM (Brain, Learning, Animation, and Movement) Lab homepage:http://blam-lab.org/ BLAM on Twitter: @blamlab Papers we discuss: Neuroscience Needs Behavior: Correcting a Reductionist Bias. John and his brother David’s interview in Current Biology: John and David Krakauer Mark Humphries’ piece on John’s “Neuroscience Needs Behavior” paper. Tinbergen’s 4 Questions. John’s book on stroke recovery:Broken Movement: The Neurobiology of Motor Recovery after Stroke (The MIT

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01:09:27

BI 024 Tim Behrens: Cognitive Maps

Brain Inspired ·

2019/01/15

Show notes: Tim’s Neuroscience homepage: Follow Tim on Twitter: @behrenstim. Edward Tolman’s cognitive maps work: Cognitive maps in rats and men. Place Cells and Grid Cells: O’Keefe early place cell paper: The Hippocampus as a Spatial Map. O’Keefe’s book about the work: The Hippocampus as a Cognitive Map. Mosers and their students discover grid cells:Microstructure of a spatial map in the entorhinal cortex. Overview. Here’s a good talk Tim gives on the subject: Building models

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01:04:05

BI 023 Marcel van Gerven: Mind Decoding with GANs

Brain Inspired ·

2018/12/28

Show notes: Donders Institute for Brain, Cognition and Behaviour Artificial Cognitive Systems on Twitter. Artificial Cognitive Systems research group. The paper we discuss: Generative adversarial networks for reconstructing natural images from brain activity. Read their Mindcodec blog. Nice overview of GANs (appropriately titled):Generative Adversarial Networks: An Overview.

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00:59:22

BI 022 Melanie Mitchell: Complexity, and AI Shortcomings

Brain Inspired ·

2018/12/18

Show notes: Follow Melanie on Twitter: @MelMitchell1. Learn more about what she does at her homepage. Here is her New York Times Op-Ed about AI. And here is a talk which goes into more depth: AI and the Barrier of Meaning. Her book, Complexity: A Guided Tour, has won awards. Check out all the free coures and tutorials at Complexity Explorer. Here’s a talk she gave: Introduction to Complexity. Melanie’s PhD advisor was Douglas Hofstadter, author of Godel, Escher, Bach: The Eternal

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01:19:39

BI 021 Matt Botvinick: Neuroscience and AI at DeepMind

Brain Inspired ·

2018/12/11

Show notes: DeepMind. The papers we discuss: Neuroscience-Inspired Artificial Intelligence. A nice summary of the meta-reinforcement learning work. Learning to reinforcement learn. Prefrontal cortex as a meta-reinforcement learning system. Machine Theory of Mind. Reinforcement learning.

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01:09:04

BI 020 Anna Wexler: Stimulate Your Brain?

Brain Inspired ·

2018/11/29

Show notes: Anna’s website: annawexler.com. Follow Anna on Twitter: @anna_wexler. Check out her documentary Unorthodox. The papers we discuss: Recurrent themes in the history of the home use of electrical stimulation: Transcranial direct current stimulation (tDCS) and the medical battery (1870–1920). The Social Context of “Do-It-Yourself” Brain Stimulation: Neurohackers, Biohackers, and Lifehackers. Who Uses Direct-to-Consumer Brain Stimulation Products, and Why? A Study of Home Users of

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00:53:14

BI 019 Julie Grollier: Spintronic Neuromorphic...

Brain Inspired ·

2018/11/22

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01:06:03

BI 018 Dean Buonomano: Time in Brains and AI

Brain Inspired ·

2018/11/15

Show notes: Follow Dean on Twitter: @deanbuonoVisit his lab website at UCLA.The review we discuss: The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions The two books we discuss:

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00:57:14

BI 017 Jeff Hawkins: Location, Location, Location

Brain Inspired ·

2018/11/08

Follow Jeff and Numenta on twitter: @JeffCHawkins and @Numenta. The Numenta website- access all the previous papers leading up to this point. The paper we discuss: A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex. His influential and excellent book On Intelligence: How a New Understanding of the Brain Will Lead to the Creation of Truly Intelligent Machines

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00:55:36

BI 016 Ryota Kanai: Artificial Consciousness

Brain Inspired ·

2018/11/01

Show notes: Ryota founded the company Araya. Follow him on twitter: @kanair. Integrated Information Theory. Pansychism. The paper we discuss: A unified strategy for implementing curiosity and empowerment driven reinforcement learning. An excellent article by Ryota in Nautilus.. We Need Conscious Robots. Higher order theories of consciousness. The hard problem of consciousness. The free energy principle.

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00:49:34

BI 015 Terrence Sejnowski: How to Start a Deep...

Brain Inspired ·

2018/10/25

Show notes: His new book, The Deep Learning Revolution: His Computational Neurobiology Laboratory at the Salk Institute. His faculty page at UCSD. His first book, The Computational Brain. His online course with Barbara Oakley, Learning How To Learn. Steven Johnson’s book Where Good Ideas Come From.

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00:41:34

BI 014 Konrad Kording: Regulators, Mount Up!

Brain Inspired ·

2018/10/18

Show Notes: Follow Konrad on Twitter: @KordingLab. Konrad’s lab website. The paper we discuss: Bioscience-scale automated detection of figure element reuse.

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00:52:27

BI 013 Dileep George: Vicarious Robot AI

Brain Inspired ·

2018/10/11

Dileep’s homepage. Dileep on Twitter: @dileeplearning Vicarious, the general AI robotics company Dileep cofounded. Vicarious on Twitter: @vicariousai. The papers we discuss: A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs. Cortical Microcircuits from a Generative Vision Model Probabilistic graphical models. Hierarchical temporal memory. HTM School on Youtube. Dileep’s earlier paper with Jeff Hawkins of Numenta:Towards a

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01:06:25

BI 012 Niko Kriegeskorte: Black Box, White Box

Brain Inspired ·

2018/10/05

Mentioned in the show: Follow Niko on twitter @KriegeskorteLab. Visit his lab website. The Cognitive Computational Neuroscience Conference. The review papers we base the conversation on: Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing. Cognitive computational neuroscience. Deep Neural Networks in Computational Neuroscience. Want a thorough breakdown of recent research articles? Try his blog. Not mentioned in the show, but check

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00:50:30

BI 011 Grace Lindsay: Visual Attention in CNNs

Brain Inspired ·

2018/09/27

Mentioned in the show: The paper we discuss:How biological attention mechanisms improve task performance in a large-scale visual system model. Follow Grace on Twitter: @neurograce. She co-hosts the AI/Neuroscience/Science podcast, Unsupervised Thinking. Her excellent blog Neurdiness. The CNN blog post I highly recommend for a deeper dive:Deep Convolutional Neural Networks as Models of the Visual System: Q&A. Or listen to my interview with Dan Yamins. The podcast that inspired

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01:04:46

BI 010 Adam Marblestone: Brain Cost Functions

Brain Inspired ·

2018/09/20

Mentioned in the show Adam’s Website. Follow him on Twitter. He made Technology Review’s 35 Innovators Under 35. The paper we discuss: Toward an Integration of DeepLearning and Neuroscience Some of the peripheral things we discussed: Cortical microcircuits: here’s an example paper. Autoencodersare unsupervised learning methods to reconstruct their input. A nice introduction to Generative Adversarial Networks. Marvin Minsky’s classicSociety of Mind. Some of his talks

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01:11:00

BI 009 Blake Richards: Deep Learning in the Brain

Brain Inspired ·

2018/09/13

Mentioned in the show Follow Blake on twitter: @tyrell_turing Blake’s Learning in Neural Circuits (LiNC) Laboratory. He’s a Fellow with the Learning in Machines and Brains Program of the Canadian Institute for Advanced Research (CIFAR). The paper we discuss: Towards Deep Learning With Segregated Dendrites. Code to run the model on Github. If you’d rather watch a talk, here’s the same topic in a great talk by Blake. The idea of approaching neuroscience from the perspective there are

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00:53:34

BI 008 Joshua Glaser: Supervised ML for Neuroscience

Brain Inspired ·

2018/09/07

Mentioned in the show The two papers we discuss: The Roles of Supervised Machine Learning in Systems Neuroscience Machine learning for neural decoding Kording lab, where Josh did his PhD work

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01:01:48

BI 007 Daniel Yamins: Infant AI and CNNs

Brain Inspired ·

2018/09/02

Mentioned in the show: Dan’s Stanford Neuroscience and Artificial Intelligence Laboratory: The 2 papers we discuss Performance-optimized hierarchical models predict neural responses in higher visual cortex Learning to Play with Intrinsically-Motivated Self-Aware Agents ImageNetas one of the most important things to stimulate research in AI, developed by these folks. Ventral visual stream (as opposed to the Dorsal stream). Retinotopy Convolutional neural networks were inspired

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