Long interviews with neuroscientists and philosophers on consciousness, decision-making, and whether AI is anything like a brain.
Brain Inspired works in the overlap between brain science and artificial intelligence. Its conversations linger over computation, affordances, consciousness, memory, learning, and the uneasy assumptions scientists inherit when they describe minds as machines.
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Brain Inspired is a single-host interview show: Paul Middlebrooks speaks with one guest researcher (occasionally two, in a panel-style conversation) per episode, working through their specific papers, models, and career background rather than covering general science news. Episodes are long and technically dense, often exceeding 90 minutes, and assume listener familiarity with terms like drift-diffusion models, dynamical systems, and computational neuroscience. Recurring subject areas include theories of consciousness and how a 'thought' becomes reportable, decision-making research built on drift-diffusion and evidence-accumulation models, dynamical-systems approaches that trace brain activity from single neurons to whole networks, cellular and molecular accounts of memory that extend beyond neurons, and philosophy-of-mind topics including ecological psychology and affordance theory. A parallel theme running through many episodes is a critical comparison between biological cognition and artificial intelligence, with guests frequently pushing back on claims that large language models are conscious or intelligent in a brain-like sense. Guests are drawn from academic neuroscience, cognitive science, and philosophy departments, including figures affiliated with Columbia University, NYU's Center for Neural Science, the University of Tartu, and other research institutions. The show references recurring intellectual touchstones such as James Gibson's ecological psychology and Merleau-Ponty, and guests often discuss their own career trajectories and mentors alongside their research. The tone is discursive and academic rather than promotional, with the host asking clarifying and probing questions rather than delivering pre-packaged explainers. Listeners who want summarized takeaways rather than full technical discussion would need to rely on show notes rather than the conversations themselves. The show supports itself in part through Patreon.
Made for: Listeners with a background or serious interest in neuroscience, cognitive science, or philosophy of mind who want technical, single-guest research conversations rather than pop-science summaries.
What sets it apart: Unlike broader science-interview shows, Brain Inspired stays narrowly focused on the neuroscience-AI-philosophy interface, with episodes built around one guest's specific research program and models rather than general science news or multi-topic panels.
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, cr…
Based on 6 episodes we listened to · September 2026
Brain Inspired tests how well computational, biological and philosophical accounts can explain thought, perception and consciousness.
Brain Inspired keeps returning to a difficult question: what kind of explanation can genuinely account for a mind? In interviews led by Paul, consciousness, reasoning and perception become problems to examine from several levels at once.
A kidney cell remembers, and your neat little theory of mind starts sweating.
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Short reviews from the PlayNext desk, based on the episodes we processed.
A careful argument about thought, limitation, and the parts that clean models leave out.
Tom Griffiths treats thought as something with a shared grammar: logic, probability, and decision theory. The more interesting question sits lower down, in how those tools get built into human minds and AI systems.
A careful defense of ecological neuroscience that treats affordances as part of explanation, not a slogan.
It treats ecological psychology as more than a vocabulary set, and that focus gives the discussion real shape. Affordances, organism-environment coupling, and the Gibsonian claim about what counts as explanation are handled as connected ideas, not loose themes.
A patient, brain-first challenge to easy talk about consciousness and AI.
Brain Inspired takes up Jan Aru's argument that consciousness may be a computation, but only one grounded in biological tissue and far beyond what large language models can make credible.
A measured argument about when thought becomes conscious.
Shadlen frames consciousness less as a puzzle than as a way of asking what can be said to another mind like one's own. Paul keeps that line active through Gibsonian affordances, decision-making, and a path that runs through Merleau-Ponty, Dreyfus, and Heidegger, so the…
Kukushkin traces consciousness back to molecular meaning -- and the puzzle, he argues, disappears when you do.
Nikolai Kukushkin comes to this episode with a specific claim -- that kidney cells form memories the same way neurons do -- and backs it up, walking from molecular biology into philosophy of mind with the confidence of someone who has spent years in both.
A patient look at how neuroscience tries to connect neurons, networks, and whole brain dynamics.
Brain Inspired treats a familiar neuroscience question as something larger: what changes, and what stays stable, as activity moves from single neurons to local populations to whole brains?
Lulu Miller and Latif Nasser build single reported stories around one scientific question.
Flora Lichtman interviews scientists, from gut-health researchers to Queen's Brian May.
Steven Novella and a rotating panel dissect weekly science news and debunk pseudoscience claims.
Bob McDonald anchors weekly multi-segment interviews on new research, from cricket courtship to moon missions.
APA's Kim Mills interviews psychology researchers on tipping, crying, and extremism.
A host and three academics dissect one topic weekly, from archaea to the Tudors.
The conversation starts with universality: if intelligent beings face the same kinds of problems, Griffiths says there may be ideal solutions.
Affordance is doing more than dressing up the argument.
Jan Aru, a co-principal investigator at the University of Tartu’s Natural and Artificial Intelligence Lab, argues that consciousness may be a computation but that it is "a freaking complex computation" rooted in biological tissue, not current large language models.
BI 230 of Brain Inspired features Michael Shadlen discussing his account of how a thought becomes conscious through reporting and interrogation.
This episode features Tomasso Poggio discussing principles of intelligence and learning, including theories of brain simulation and cognitive science.
This episode features Alex Maier discussing the shift from metaphorical theories to mathematical formalism in understanding consciousness and its mapping to brain activity.
This episode explores the challenge of decoding non-trivial memories from a complete brain connectome, using models of hippocampal systems like place and grid cells to frame experimental approaches.
This episode features Tatiana Engel discussing her research on connecting cognitive dynamics with neural network connectivity and exploring high- and low-dimensional brain activity.
This episode explores the nature of scientific understanding, discussing whether it is merely a feeling or a skill involving theory-based explanations and qualitative predictions.
An interview with philosopher Dan Nicholson about Erwin Schrodinger's book 'What is Life?' and its impact on molecular biology.
An interview with Vicente Raja discussing ecological neuroscience and the role of body and environment in cognition.
Memory gets pushed past neurons here.
Interview with Ann Kennedy about her research on subcortical brain areas like the hypothalamus and the role of neuromodulators in behavior and motivation.
Dynamics does the heavy lifting here.
Interview with theoretical neuroscientist Zach Pitko discussing principles of learning and the gap between brain and AI learning algorithms.
An interview with researchers about the role of criticality in brain function and learning.
Interview with Nicole Rust discussing the challenges of treating mental disorders and the neuroscience of feelings.
An interview exploring the challenge of linking psychological concepts like schemas to brain computation, using large language models to understand memory and prediction.
An interview discussing how memory is reconstructed and why perceived flaws are actually fundamental to how memory works.
An interview exploring the concept of 'smart neurons' and the challenge of linking different levels of analysis in neuroscience and AI.
David Krakauer discusses the origins and fundamentals of complexity science, exploring how concepts like agency and emergence define this interdisciplinary field and its distinction from fundamental physics.
Interview with Kieran Adolph about how studying infant motor development informs understanding of intelligence and inspires robot design.
This episode features a conversation from a neuro-AI workshop in Norway with researchers Cristina Savin and Tim Vogels, discussing theoretical neuroscience and model validation.
This episode features conversations recorded at a neuro-AI workshop in Norway, introduced by podcasters Paul and Gaute discussing their academic podcasting experiences.
An interview with Damien Kelty-Steven discussing fractal structure in behavior and unifying ecological psychology with neuroscience.
Interview with Joshua Vogelstein about the fruit fly connectome and his theoretical work on prospectivity in AI and neuroscience.
An interview with Yolanda Fukin about her research on hand-eye coordination and the coordination of eye and hand movements in naturalistic tasks.
A panel discussion at the COSYNE conference on the relationship between neuroscience and AI, featuring experts with diverse views.
Interview with Dan Goodman about spiking neural networks and the intersection of neuroscience and AI.
A discussion on higher cognition and the role of large language models in AI, critiquing formalism and the irony of using human language data.
Interview with Max Bennett about his book synthesizing comparative psychology, evolutionary neurobiology, and AI to propose five breakthroughs in brain evolution.
A panel discussion on using neuroscience technologies to decode memories from static connectomes.
Philosopher Laura Grodowski advocates for extreme pluralism in science, arguing for the inclusion of fringe theories as a permanent approach rather than just hedging bets.
A panel discussion on how machine learning can generate insights and theories in neuroscience, recorded at the Bernstein conference.