
Brain Inspired
Paul Middlebrooks

2 Listeners
All episodes
Best episodes
Top 10 Brain Inspired Episodes
Goodpods has curated a list of the 10 best Brain Inspired episodes, ranked by the number of listens and likes each episode have garnered from our listeners. If you are listening to Brain Inspired for the first time, there's no better place to start than with one of these standout episodes. If you are a fan of the show, vote for your favorite Brain Inspired episode by adding your comments to the episode page.

BI 171 Mike Frank: Early Language and Cognition
Brain Inspired
07/22/23 • 84 min
Support the show to get full episodes, full archive, and join the Discord community.
Check out my free video series about what's missing in AI and Neuroscience
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
- Twitter: @mcxfrank.
- I mentioned Mike's tweet thread about saying LLMs "have" cognitive functions:
- Related papers:
- Pragmatic language interpretation as probabilistic inference.
- Toward a “Standard Model” of Early Language Learning.
- The pervasive role of pragmatics in early language.
- The Structure of Developmental Variation in Early Childhood.
- Relational reasoning and generalization using non-symbolic neural networks.
- Unsupervised neural network models of the ventral visual stream.

1 Listener

BI 077 David and John Krakauer: Part 1
Brain Inspired
07/14/20 • 93 min
David, John, and I discuss the role of complexity science in the study of intelligence. In this first part, we talk about complexity itself, its role in neuroscience, emergence and levels of explanation, understanding, epistemology and ontology, and really quite a bit more.
Notes:
- David’s page at the Santa Fe Institute.
- John’s BLAM lab website.
- Follow SFI on twitter: @sfiscience.
- BLAM on Twitter: @blamlab
- Related Krakauer stuff:
- At the limits of thought. An Aeon article by David
- Complex Time: Cognitive Regime Shift II - When/Why/How the Brain Breaks. A video conversation with both John and David.
- Complexity Podcast.
- Books mentioned:
- Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, ed. David Krakauer.
- Understanding Scientific Understanding by Henk de Regt.
- The Idea of the Brain by Matthew Cobb.
- New Dark Age: Technology and the End of the Future by James Bridle.
- The River of Consciousness by Oliver Sacks.
1 Listener

BI 074 Ginger Campbell: Are You Sure?
Brain Inspired
06/16/20 • 82 min
Ginger and I discuss her book Are You Sure? The Unconscious Origins of Certainty, which summarizes Richard Burton's work exploring the experience and phenomenal origin of feeling confident, and how the vast majority of our brain processing occurs outside our conscious awareness.
1 Listener

BI 079 Romain Brette: The Coding Brain Metaphor
Brain Inspired
07/27/20 • 79 min
Romain and I discuss his theoretical/philosophical work examining how neuroscientists rampantly misuse the word "code" when making claims about information processing in brains. We talk about the coding metaphor, various notions of information, the different roles and facets of mental representation, perceptual invariance, subjective physics, process versus substance metaphysics, and the experience of writing a Behavior and Brain Sciences article (spoiler: it's a demanding yet rewarding experience).
- Romain's website.
- Twitter: @RomainBrette.
- The papers we discuss or mention:.
- Related works
- The Ecological Approach to Visual Perception by James Gibson.
- Why Red Doesn't Sound Like a Bell by Kevin O’Reagan.
1 Listener

BI 078 David and John Krakauer: Part 2
Brain Inspired
07/17/20 • 74 min
In this second part of our conversation David, John, and I continue to discuss the role of complexity science in the study of intelligence, brains, and minds. We also get into functionalism and multiple realizability, dynamical systems explanations, the role of time in thinking, and more. Be sure to listen to the first part, which lays the foundation for what we discuss in this episode.
Notes:
- David’s page at the Santa Fe Institute.
- John’s BLAM lab website.
- Follow SFI on twitter: @sfiscience.
- BLAM on Twitter: @blamlab
- Related Krakauer stuff:
- At the limits of thought. An Aeon article by David
- Complex Time: Cognitive Regime Shift II - When/Why/How the Brain Breaks. A video conversation with both John and David.
- Complexity Podcast.
- Books mentioned:
- Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, ed. David Krakauer.
- Understanding Scientific Understanding by Henk de Regt.
- The Idea of the Brain by Matthew Cobb.
- New Dark Age: Technology and the End of the Future by James Bridle.
- The River of Consciousness by Oliver Sacks.
1 Listener

BI 073 Megan Peters: Consciousness and Metacognition
Brain Inspired
06/10/20 • 85 min
Megan and I discuss her work using metacognition as a way to study subjective awareness, or confidence. We talk about using computational and neural network models to probe how decisions are related to our confidence, the current state of the science of consciousness, and her newest project using fMRI decoded neurofeedback to induce particular brain states in subjects so we can learn about conscious and unconscious brain processing.
Notes:
- Visit Megan's cognitive & neural computation lab.
- Twitter: @meganakpeters
- The papers we discuss or mention:
1 Listener

BI 076 Olaf Sporns: Network Neuroscience
Brain Inspired
07/04/20 • 105 min
Olaf and I discuss the explosion of network neuroscience, which uses network science tools to map the structure (connectome) and activity of the brain at various spatial and temporal scales. We talk about the possibility of bridging physical and functional connectivity via communication dynamics, and about the relation between network science and artificial neural networks and plenty more.
Notes:
1 Listener

05/07/21 • 110 min
What is creativity? How do we measure it? How do our brains implement it, and how might AI?Those are some of the questions John, David, and I discuss. The neuroscience of creativity is young, in its "wild west" days still. We talk about a few creativity studies they've performed that distinguish different creative processes with respect to different levels of expertise (in this case, in jazz improvisation), and the underlying brain circuits and activity, including using transcranial direct current stimulation to alter the creative process. Related to creativity, we also discuss the phenomenon and neuroscience of insight (the topic of John's book, The Eureka Factor), unconscious automatic type 1 processes versus conscious deliberate type 2 processes, states of flow, creative process versus creative products, and a lot more.
- John Kounios.
- Secret Chord Laboratories (David's company).
- Twitter: @JohnKounios; @NeuroBassDave.
- John's book (with Mark Beeman) on insight and creativity.
- The papers we discuss or mention:
- All You Need to Do Is Ask? The Exhortation to Be Creative Improves Creative Performance More for Nonexpert Than Expert Jazz Musicians
- Anodal tDCS to Right Dorsolateral Prefrontal Cortex Facilitates Performance for Novice Jazz Improvisers but Hinders Experts
- Dual-process contributions to creativity in jazz improvisations: An SPM-EEG study.
Timestamps 0:00 - Intro 16:20 - Where are we broadly in science of creativity? 18:23 - Origins of creativity research 22:14 - Divergent and convergent thought 26:31 - Secret Chord Labs 32:40 - Familiar surprise 38:55 - The Eureka Factor 42:27 - Dual process model 52:54 - Creativity and jazz expertise 55:53 - "Be creative" behavioral study 59:17 - Stimulating the creative brain 1:02:04 - Brain circuits underlying creativity 1:14:36 - What does this tell us about creativity? 1:16:48 - Intelligence vs. creativity 1:18:25 - Switching between creative modes 1:25:57 - Flow states and insight 1:34:29 - Creativity and insight in AI 1:43:26 - Creative products vs. process

BI 122 Kohitij Kar: Visual Intelligence
Brain Inspired
12/12/21 • 93 min
Support the show to get full episodes and join the Discord community.
Ko and I discuss a range of topics around his work to understand our visual intelligence. Ko was a postdoc in James Dicarlo's lab, where he helped develop the convolutional neural network models that have become the standard for explaining core object recognition. He is starting his own lab at York University, where he will continue to expand and refine the models, adding important biological details and incorporating models for brain areas outside the ventral visual stream. He will also continue recording neural activity, and performing perturbation studies to better understand the networks involved in our visual cognition.
- VISUAL INTELLIGENCE AND TECHNOLOGICAL ADVANCES LAB
- Twitter: @KohitijKar.
- Related papers
- BI 075 Jim DiCarlo: Reverse Engineering Vision
0:00 - Intro 3:49 - Background 13:51 - Where are we in understanding vision? 19:46 - Benchmarks 21:21 - Falsifying models 23:19 - Modeling vs. experiment speed 29:26 - Simple vs complex models 35:34 - Dorsal visual stream and deep learning 44:10 - Modularity and brain area roles 50:58 - Chemogenetic perturbation, DREADDs 57:10 - Future lab vision, clinical applications 1:03:55 - Controlling visual neurons via image synthesis 1:12:14 - Is it enough to study nonhuman animals? 1:18:55 - Neuro/AI intersection 1:26:54 - What is intelligence?

BI 075 Jim DiCarlo: Reverse Engineering Vision
Brain Inspired
06/24/20 • 76 min
Jim and I discuss his reverse engineering approach to visual intelligence, using deep models optimized to perform object recognition tasks. We talk about the history of his work developing models to match the neural activity in the ventral visual stream, how deep learning connects with those models, and some of his recent work: adding recurrence to the models to account for more difficult object recognition, using unsupervised learning to account for plasticity in the visual stream, and controlling neural activity by creating specific images for subjects to view.
Notes:
- The DiCarlo Lab at MIT.
- Related papers:
- Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks.
- Fast recurrent processing via ventral prefrontal cortex is needed by the primate ventral stream for robust core visual object recognition.
- Unsupervised changes in core object recognition behavioral performance are accurately predicted by unsupervised neural plasticity in inferior temporal cortex.
- Neural population control via deep image synthesis.
Show more best episodes

Show more best episodes
Featured in these lists
FAQ
How many episodes does Brain Inspired have?
Brain Inspired currently has 219 episodes available.
What topics does Brain Inspired cover?
The podcast is about Natural Sciences, Podcasts, Technology and Science.
What is the most popular episode on Brain Inspired?
The episode title 'BI 073 Megan Peters: Consciousness and Metacognition' is the most popular.
What is the average episode length on Brain Inspired?
The average episode length on Brain Inspired is 83 minutes.
How often are episodes of Brain Inspired released?
Episodes of Brain Inspired are typically released every 10 days, 2 hours.
When was the first episode of Brain Inspired?
The first episode of Brain Inspired was released on Aug 2, 2018.
Show more FAQ

Show more FAQ