show episodes
 
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 n ...
 
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show series
 
This month's episode of Brain Science is an interview with neuroscientists E. Bruce Goldstein, author of "The Mind: Consciousness, Prediction, and the Brain." We review some key ideas about how the brain creates the Mind, the important role of unconscious processes and prediction. It is a great starter episode for new listeners and a concise review…
 
It’s generally agreed machine learning and AI provide neuroscience with tools for analysis and theoretical principles to test in brains, but there is less agreement about what neuroscience can provide AI. Should computer scientists and engineers care about how brains compute, or will it just slow them down, for example? Chris, Sam, and I discuss ho…
 
Alison and I discuss her work to accelerate learning and thus improve AI by studying how children learn, as Alan Turing suggested in his famous 1950 paper. The ways children learn are via imitation, by learning abstract causal models, and active learning by implementing a high exploration/exploitation ratio. We also discuss child consciousness, psy…
 
Dileep and I discuss his theoretical account of how the thalamus and cortex work together to implement visual inference. We talked previously about his Recursive Cortical Network (RCN) approach to visual inference, which is a probabilistic graph model that can solve hard problems like CAPTCHAs, and more recently we talked about using his RCNs with …
 
It's time for our 14th Annual Review Episode! Despite the challenges of 2020, it has been an outstanding year for Brain Science: the show passed 11 million downloads and Dr. Campbell released of second edition of Are You Sure? The Unconscious Origins of Certainty. This episode is also a great introduction for new listeners. It can be enjoyed even i…
 
Russ and I discuss cognitive ontologies – the “parts” of the mind and their relations – as an ongoing dilemma of how to map onto each other what we know about brains and what we know about minds. We talk about whether we have the right ontology now, how he uses both top-down and data-driven approaches to analyze and refine current ontologies, and h…
 
Carsen and I discuss how she uses 2-photon calcium imaging data from over 10,000 neurons to understand the information processing of such large neural population activity. We talk about the tools she makes and uses to analyze the data, and the type of high-dimensional neural activity structure they found, which seems to allow efficient and robust i…
 
This month's episode of Brain Science features neuroscientist Peter Sterling sharing the key ideas for his new book What Is Health? Allostasis and the Evolution of Human Design. In recent years neuroscientists have developed a growing appreciation of the predictive functions of the brain. Sterling takes this principle to the next level by asking wh…
 
Chris and I discuss his Spaun large scale model of the human brain (Semantic Pointer Architecture Unified Network), as detailed in his book How to Build a Brain. We talk about his philosophical approach, how Spaun compares to Randy O’Reilly’s Leabra networks, the Applied Brain Research Chris co-founded, and I have guest questions from Brad Aimone, …
 
Matt and I discuss how cognition and behavior drifts over the course of minutes and hours, and how global brain activity drifts with it. How does the brain continue to produce steady perception and action in the midst of such drift? We also talk about how to think about variability in neural activity. How much of it is noise and how much of it is h…
 
Randy and I discuss his LEABRA cognitive architecture that aims to simulate the human brain, plus his current theory about how a loop between cortical regions and the thalamus could implement predictive learning and thus solve how we learn with so few examples. We also discuss what Randy thinks is the next big thing neuroscience can contribute to A…
 
When a waiter hands me the bill, how do I know whether to pay it myself or let my date pay? On this episode, I get a progress update from Dileep on his company, Vicarious, since Dileep’s last episode. We also talk broadly about his experience running Vicarious to develop AGI and robotics. Then we turn to his latest brain-inspired AI efforts using c…
 
Bernard Baars is a pioneer in the neuroscience of consciousness. He first proposed Global Workspace Theory back in 1980, which was before consciousness was considered an acceptable topic of scientific research. His approach inspired others including the current Global Neuronal Workspace Theory, which I discussed briefly in episode 160. This episode…
 
Ken and I discuss open-endedness, the pursuit of ambitious goals by seeking novelty and interesting products instead of advancing directly toward defined objectives. We talk about evolution as a prime example of an open-ended system that has produced astounding organisms, Ken relates how open-endedness could help advance artificial intelligence and…
 
Ida and I discuss the current landscape of reinforcement learning in both natural and artificial intelligence, and how the old story of two RL systems in brains – model-free and model-based – is giving way to a more nuanced story of these two systems constantly interacting and additional RL strategies between model-free and model-based to drive the…
 
This is my fifth interview with molecular biologist and neuroscientist Dr. Seth Grant from The University of Edinburgh. Dr. Grant was recently recognized for his pioneering work by the Federation of European Neuroscientists. He continues to make fundamental discoveries about the structure and function of the synapse and this month we discuss the di…
 
David, Gyuri, and I discuss the issues they argue for in their back and forth commentaries about the importance of neuroscience and psychology, or implementation-level and computational-level, to advance our understanding of brains and minds – and the names we give to the things we study. Gyuri believes it’s time we use what we know and discover ab…
 
Jane and I discuss the relationship between AI and neuroscience (cognitive science, etc), from her perspective at Deepmind after a career researching natural intelligence. We also talk about her meta-reinforcement learning work that connects deep reinforcement learning with known brain circuitry and processes, and finally we talk about her recent w…
 
This extremely timely episode of Brain Science features an interview with Dr. Carol Tavris, co-author of the newly released third edition of Mistakes Were Made (but Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts. Cognitive Dissonance was actually discovered back in 1956 and it is one of the most well-replicated phenomen…
 
Steve and I discuss his long and productive career as a theoretical neuroscientist. We cover his tried and true method of taking a large body of psychological behavioral findings, determining how they fit together and what’s paradoxical about them, developing design principles, theories, and models from that body of data, and using experimental neu…
 
Pieter and I discuss his ongoing quest to figure out how the brain implements learning that solves the credit assignment problem, like backpropagation does for neural networks. We also talk about his work to understand how we perceive individual objects in a crowded scene, his neurophysiological recordings in support of the global neuronal workspac…
 
Daeyeol and I discuss his book Birth of Intelligence: From RNA to Artificial Intelligence, which argues intelligence is a function of and inseparable from life, bound by self-replication and evolution. The book covers a ton of neuroscience related to decision making and learning, though we focused on a few theoretical frameworks and ideas like divi…
 
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, proce…
 
BS 174 is an interview with neuroscientist and philosopher Georg Northoff about his fascinating book "The Spontaneous Brain: From the Mind–Body to the World–Brain Problem." We explore the significance of the growing evidence that most of the brain's activity occurs independently of external stimuli with a focus on the implications of this finding f…
 
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 foundati…
 
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. Fol…
 
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 a…
 
In this special episode of Brain Science host Dr Ginger Campbell reads an excerpt from her bestseller "Are You Sure? The Unconscious Origin of Certainty." While it might seem ironic to talk about certainty during these extremely uncertain times, understanding how our brain generates the feeling of knowing or certainty is actually more relevant than…
 
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…
 
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. Are You Sure? The Unconscious Origins of Certainty. Brain Science Podc…
 
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 brai…
 
Mazviita and I discuss the growing divide between prediction and understanding as neuroscience models and deep learning networks become bigger and more complex. She describes her non-factive account of understanding, which among other things suggests that the best predictive models may deliver less understanding. We also discuss the brain as a comp…
 
Patrick and I mostly discuss his path from a technician in the then nascent Jim DiCarlo lab, through his graduate school and two postdoc experiences, and finally landing a faculty position, plus the culture and issues in academia in general. We also cover plenty of science, like the role of eye movements in the study of vision, the neuroscience (an…
 
In this episode I talk with neuroscientist György Buzsáki about his new book The Brain from Inside Out. We explore how abandoning what he calls the "Outside In" approach to understanding the brain can lead to surprising new insights. Links and References: Buzsaki's Lab The Brain from Inside Out by György Buzsáki MD PhD Rhythms of the Brain by Györg…
 
Brad and I discuss his battle-tested, age-defying cognitive model for how we learn and store concepts by forming and rearranging clusters, how the model maps onto brain areas, and how he’s using deep learning models to explore how attention and sensory information interact with concept formation. We also discuss the cognitive modeling approach, Mar…
 
David and I discuss the latest efforts he and his Elemental Cognition team have made to create machines that can understand stories the way humans can and do. The long term vision is to create what David calls “thought partners”, which are virtual assistants that can learn and synthesize a massive amount of information for us when we need that info…
 
Rodrigo and I discuss concept cells and his latest book, NeuroScience Fiction. The book is a whirlwind of many of the big questions in neuroscience, each one framed by of one of Rodrigo’s favorite science fiction films and buttressed by tons of history, literature, and philosophy. We discuss a few of the topics in the book, like AI, identity, free …
 
This episode of Brain Science is an interview with neuroscientist Matthew Cobb author of "The Idea of the Brain: The Past and Future of Neuroscience." Cobb approaches the history of neuroscience from a different perspective than previous writers. He writes from the perspective of a working scientist with a deep interest in the history of ideas and …
 
In this second part of my conversion with Paul (listen to the first part), we continue our discussion about how to understand brains as feedback control mechanisms – controlling our internal state and extending that control into the world – and how Paul thinks the key to understanding intelligence is to trace our evolutionary past through phylogene…
 
In this first part of our conversation, Paul and I discuss his approach to understanding how the brain (and intelligence) works. Namely, he believes we are fundamentally action and movement oriented – all of our behavior and cognition is based on controlling ourselves and our environment through feedback control mechanisms, and basically all neural…
 
Thomas and I discuss the role of recurrence in visual cognition: how brains somehow excel with so few “layers” compared to deep nets, how feedback recurrence can underlie visual reasoning, how LSTM gate-like processing could explain the function of canonical cortical microcircuits, the current limitations of deep learning networks like adversarial …
 
Galit and I discuss the independent roles of prediction and explanation in scientific models, their history and eventual separation in the philosophy of science, how they can inform each other, and how statisticians like Galit view the current deep learning explosion. Galit’s website. Follow her on twitter: @gshmueli. The papers we discuss or menti…
 
BS 170 is an interview with Andreas Nieder, author of "A Brain for Numbers: The Biology of the Number Instinct." We talk about the surprising discovery that a wide variety of animals have a number instinct, which is called the approximate number system. This appears to provide the basis for the more abstract mathematical abilities that are seen in …
 
Uri and I discuss his recent perspective that conceives of brains as super-over-parameterized models that try to fit everything as exactly as possible rather than trying to abstract the world into usable models. He was inspired by the way artificial neural networks overfit data when they can, and how evolution works the same way on a much slower ti…
 
This episode is an exploration of glial cells with R Douglas Fields, author of "The Other Brain: The Scientific and Medical Breakthroughs That Will Heal Our Brains and Revolutionize Our Health." Glial Cells outnumber the neurons in our nervous system, but until the last few years they were thought to merely support cells. Dr. Fields takes us throug…
 
Stefan and I discuss creativity and constraint in artificial and biological intelligence. We talk about his Asimov Institute and its goal of artificial creativity and constraint, different types and functions of creativity, the neuroscience of creativity and its relation to intelligence, how constraint is an essential factor in all creative process…
 
BS 168 is an interview with psychologist Cecilia Heyes from Oxford University in the UK. We talk about her fascinating book "Cognitive Gadgets: The Cultural Evolution of Thinking." Our focus is on exploring the evidence that several cognitive skills that appear to be unique to humans are learned from other people rather than being inherited genetic…
 
Jörn, Niko and I continue the discussion of mental representation from last episode with Michael Rescorla, then we discuss their review paper, Peeling The Onion of Brain Representations, about different ways to extract and understand what information is represented in measured brain activity patterns. Show notes: Jörn’s lab website. Niko’s lab webs…
 
This is an interview with Stanislas Dehaene about his new book How We Learn: Why Brains Learn Better Than Any Machine . . . for Now. According to neuroscientist Dehaene neuroscience has revealed that human babies are incredible "learning machines" whose abilities exceed those of the best current artificial intelligence. We explore why this is so an…
 
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