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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

01:26:18

BI 055 Thomas Naselaris: Seeing Versus Imagining

Brain Inspired ·

2019/12/09

Thomas and I talk about what happens in the brain’s visual system when you see something versus imagine it. He uses generative encoding and decoding models and brain signals like fMRI and EEG to test the nature of mental imagery. We also discuss the huge fMRI dataset of natural images he’s collected to infer models of the entire visual system, how we’ve still not tapped the potential of fMRI, and more. Thomas's lab website. Papers we discuss or mention: Resolving Ambiguities of MVPA Using

en-US

01:15:24

BI 054 Kanaka Rajan: How Do We Switch Behaviors?

Brain Inspired ·

2019/11/27

Support the Podcast Kanaka and I discuss a few different ways she uses recurrent neural networks to understand how brains give rise to behaviors. We talk about her work showing how neural circuits transition from active to passive coping behavior in zebrafish, and how RNNs could be used to understand how we switch tasks in general and how we multi-task. Plus the usual fun speculation, advice, and more. Kanaka’s google scholar profile. Follow her on twitter: @rajankdr. Papers we discuss:

en-US

01:33:24

BI 053 Jon Brennan: Linguistics in Minds and Machines

Brain Inspired ·

2019/11/17

Support the Podcast Jon and I discuss understanding the syntax and semantics of language in our brains. He uses linguistic knowledge at the level of sentence and words, neuro-computational models, and neural data like EEG and fMRI to figure out how we process and understand language while listening to the natural language found in everyday conversations and stories. I also get his take on the current state of natural language processing and other AI advances, and how linguistics,

en-US

01:25:48

BI 052 Andrew Saxe: Deep Learning Theory

Brain Inspired ·

2019/11/06

Support the Podcast Andrew and I discuss his work exploring how various facets of deep networks contribute to their function, i.e. deep network theory. We talk about what he’s learned by studying linear deep networks and asking how depth and initial weights affect learning dynamics, when replay is appropriate (and when it’s not), how semantics develop, and what it all might tell us about deep learning in brains. Show notes: Visit Andrew's website. The papers we discuss or mention: Are

en-US

01:28:21

BI 051 Jess Hamrick: Mental Simulation and Construction

Brain Inspired ·

2019/10/27

Support the Podcast Jess and I discuss construction using graph neural networks. She makes AI agents that build structures to solve tasks in a simulated blocks and glue world using graph neural networks and deep reinforcement learning. We also discuss her work modeling mental simulation in humans and how it could be implemented in machines, and plenty more. Show notes: Jess’s website. Follow her on twitter: @jhamrick The papers we discuss or mention: Analogues of mental simulation and

en-US

01:36:02

BI 050 Kyle Dunovan: Academia to Industry

Brain Inspired ·

2019/10/17

Kyle and I talk about his work modeling the basal ganglia and its circuitry to control whether we take an action and how we select among alternative actions. We also reflect on his experiences in academia, the larger picture of what it’s like in graduate school and after - at least in a computational neuroscience program - why he left, what he’s doing now, and how it all fits together. Show notes: Kyle’s website. Follow him on twitter: @dunovank Examples of his work on basal ganglia and

en-US

01:24:45

BI 049 Phillip Alvelda: Trustworthy Brain Machines

Brain Inspired ·

2019/10/06

Support the Podcast Phillip and I discuss his company Brainworks, which uses the latest neuroscience to build AI into its products. We talk about their first product, Ambient Biometrics, that measures vital signs using your smartphone's camera. We also dive into entrepreneurship in the AI startup world, ethical issues in AI and social media companies, his early days using neural networks at NASA, where he thinks this is all headed, and more. Show notes: His company, Brainworks.Follow

en-US

01:24:37

BI 048 Liz Spelke: What Makes Us Special?

Brain Inspired ·

2019/09/25

Support the Podcast Liz and I discuss her work on cognitive development, specially in infants, and what it can tell us about what makes human cognition different from other animals, what core cognitive abilities we’re born with, and how those abilities may form the foundation for much of our other cognitive abilities to develop. We also talk about natural language as the potential key faculty that synthesizes our early core abilities into the many higher cognitive functions that make us

en-US

00:48:12

BI 047 David Poeppel: Wrong in Interesting Ways

Brain Inspired ·

2019/09/15

In this second part of our conversation, (listen to the first part) David and I discuss his thoughts about current language and speech techniques in AI, his thoughts about the prospects of artificial general intelligence, the challenge of mapping the parts of linguistics onto the parts of neuroscience, the state of graduate training, and more. Visit David's lab websiteat NYU. He’s also a director atMax Planck Institute for Empirical Aesthetics. Follow him on twitter: @davidpoeppel. Some of the

en-US

01:37:12

BI 046 David Poeppel: From Sounds to Meanings

Brain Inspired ·

2019/09/08

Support the Podcast David and I talk about his work to understand how sound waves floating in the air get transformed into meaningful concepts in your mind. He studies speech processing and production, language, music, and everything in between, approaching his work with steadfast principles to help frame what it means to understand something scientifically. We discuss many of the hurdles to understanding how our brains work and making real progress in science, plus a ton more. Show

en-US

01:16:52

BI 045 Raia Hadsell: Robotics and Deep RL

Brain Inspired ·

2019/08/28

Support the Podcast Show notes: Raia and I discuss her work at DeepMind figuring out how to build robots using deep reinforcement learning to do things like navigate cities and generalize intelligent behaviors across different tasks. We also talk about challenges specific for embodied AI (robots), how much of it takes inspiration from neuroscience, and lots more. Raia’s website. Follow her on Twitter:@RaiaHadsell Papers relevant to our discussion: Learning to Navigate in Cities without

en-US

01:15:33

BI 044 Talia Konkle: Turning Vision On Its Side

Brain Inspired ·

2019/08/18

Talia and I discuss her work on how our visual system is organized topographically, and divides into three main categories: big inanimate things, small inanimate things, and animals. Her work is unique in that it focuses not on the classic hierarchical processing of vision (though she does that, too), but what kinds of things are represented along that hierarchy. She also uses deep networks to learn more about the visual system. We also talk about her keynote talk at the Cognitive Computational

en-US

01:30:30

BI 043 Anna Schapiro: Learning in Hippocampus and Cortex

Brain Inspired ·

2019/08/07

How does knowledge in the world get into our brains and integrated with the rest of our knowledge and memories? Anna and I talk about the complementary learning systems theory introduced in 1995 that posits a fast episodic hippopcampal learning system and a slower statistical cortical learning system. We then discuss her work that advances and adds missing pieces to the CLS framework, and explores how sleep and sleep cycles contribute to the process. We also discuss how her work might contribute to

en-US

00:59:35

BI 042 Brad Aimone: Brains at the Funeral of Moore’s Law

Brain Inspired ·

2019/07/28

This is part 2 of my conversation with Brad (listen to part 1 here). We discuss how Moore’s law is on its last legs, and his ideas for how neuroscience - in particular neural algorithms - may help computing continue to scale in a post-Moore’s law world. We also discuss neuromporphics in general, and more. Brad's homepage.Follow Brad on Twitter: @jbimaknee.The paper we discuss:Neural Algorithms and Computing Beyond Moore's Law.Check out the Neuro Inspired Computing Elements (NICE) workshop - lots

en-US

01:06:33

BI 041 Brad Aimone: Neurogenesis and Spiking in Deep...

Brain Inspired ·

2019/07/19

In this first part of our discussion, Brad and I discuss the state of neuromorphics and its relation to neuroscience and artificial intelligence. He describes his work adding new neurons to deep learning networks during training, called neurogenesis deep learning, inspired by how neurogenesis in the dentate gyrus of the hippocampus helps learn new things while keeping previous memories intact. We also talk about his method to transform deep learning networks into spiking neural networks so they can

en-US

01:02:19

BI 040 Nando de Freitas: Enlightenment, Compassion,...

Brain Inspired ·

2019/07/09

Show Notes: Nando’s CIFAR page.Follow Nando on Twitter: @NandoDF He's giving a keynote address at Cognitive Computational Neuroscience Meeting 2020.Check out his famous machine learning lectures on Youtube. Papers we (more allude to than) discuss: Neural Programmer-Interpreters. Learning to learn by gradient descent by gradient descent. Dueling Network Architectures for Deep Reinforcement Learning.Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. One-Shot

en-US

01:19:09

BI 039 Anne Churchland: Decisions, Lapses, and Fidgets

Brain Inspired ·

2019/06/29

Show notes: Check out Anne's lab website.Follow her on twitter: @anne_churchlandAnne's List, the list of female systems neuroscientists to invite as speakers.The papers we discuss: Single-trial neural dynamics are dominated by richly varied movements.Lapses in perceptual judgments reflect exploration.Complexity vs Stimulus-Response Compatibility vs Stimulus-response ethological validity.Perceptual Decision-Making: A Field in the Midst of a Transformation.

en-US

01:18:37

BI 038 Máté Lengyel: Probabilistic Perception and...

Brain Inspired ·

2019/06/19

Show notes: Máté's Cambridge website.He's part of the Computational Learning and Memory Group there.Here's his webpage at Central European University.A review to introduce his subsequent work:Statistically optimal perception and learning: from behavior to neural representations.Related recent talks:Bayesian models of perception, cognition and learning - CCCN 2017. Sampling: coding, dynamics, and computation in the cortex (Cosyne 2018).

en-US

01:29:52

BI 037 Nathaniel Daw: Thinking the Right Thoughts

Brain Inspired ·

2019/06/09

Show notes: Nathaniel will deliver a keynote address at the upcoming CCN conference.Check out his lab website.Follow him on Twitter: @nathanieldaw.The paper we discuss:Prioritized memory access explains planning and hippocampal replayOr see a related talk: Rational planning using prioritized experience replay.

en-US

01:11:08

BI 036 Roshan Cools: Cognitive Control and Dopamine

Brain Inspired ·

2019/05/30

Show notes: Roshan will deliver a keynote address at the upcoming CCN conference.Roshan's Motivational and Cognitive Control lab.Follow her on Twitter: @CoolsControl.Her TED Talk on Trusting Science.Papers related to the research we discuss:The costs and benefits of brain dopamine for cognitive control.Or see her variety of related works.

en-US

235 results

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