Brain Inspired

Maxim Raginsky joins Paul Middlebrooks to examine brains, AI and biological autonomy through control theory. They discuss what behaviour reveals about a system's internal organisation, analog and digital descriptions, the relationship between control and cybernetics, active inference and the limits of computational accounts. The publisher offers a public episode and supporter access to its full archive.

Hosted by Paul Middlebrooks

Andrea Gambarotto examines agency and intrinsic purpose in biological cognition, drawing on Hegel and contemporary theoretical biology. The conversation connects these ideas to enactivism and asks how living intelligence differs from artificial systems, including language models.

Hosted by Paul Middlebrooks

Daniel Levenstein discusses spontaneous activity in the hippocampus and cortex, especially during sleep, and its relationship to learning, memory and navigation. He explains how AI models can help investigate these dynamics, alongside questions about model systems, cognitive maps and the relationship between neuroscience experiments and theory.

Hosted by Paul Middlebrooks

Marco Facchin discusses how neuroscience and philosophy explain cognition, including embodied and enactive approaches, the importance of biological detail, and limits of computational accounts. The conversation also examines predictive processing, representation and the role of AI in understanding brains and minds.

Hosted by Paul Middlebrooks

Alison Barth explains how distinct neuron types contribute to cortical function and how learning can be used as an experimental window into the organization and plasticity of cortical circuits.

Kathryn Nave discusses how living systems acquire meaning and intelligence through organization, constraints, and active inference. The conversation connects the free-energy principle and organizational closure to questions about brains, cognition, agency, and the boundaries of intelligent life.

Paul Middlebrooks and Johannes Jaeger discuss agency in living systems, relevance realization, consciousness, energy efficiency and why biological organisms differ from artificial agents.

Cristopher Moore connects computational complexity to questions about cognition and artificial intelligence. The discussion considers what makes a problem difficult, how rugged landscapes shape computation, and what complexity theory can contribute to understanding learning and generalization in brains and machines.

Hosted by Paul Middlebrooks

Nedah Nemati examines how neuroscience defines behavior and why freely moving animals and naturalistic experiments matter. She discusses how tools, historical assumptions and researchers' own experience influence scientific questions, including what studies of sleep reveal about the relationship between observation and explanation.

Hosted by Paul Middlebrooks

James Harrison presents his proposed account of hypnosis as mental foraging, relating changes in attention and internal state to memory and prediction. The conversation explores interoception, engagement with the external world and memory reconsolidation as possible ways to explain hypnotic experience.

Hosted by Paul Middlebrooks

Ehud Ahissar explains active perception through closed loops linking movement and sensation, drawing on work with rodent whiskers. He introduces perceptual dualism as a proposed distinction between communication within the brain and interactions with the world, and explores its implications for consciousness and neural dynamics.

Hosted by Paul Middlebrooks

Liset de la Prida discusses hippocampal sharp-wave ripples and their relationship to replay and memory. The conversation connects different ripple patterns and neuron types to population activity, asking how particular cells help shape the lower-dimensional dynamics used to describe neural computation.

Hosted by Paul Middlebrooks

Romain Brette questions familiar computational and information-processing metaphors for the brain. Starting from behavior in organisms such as paramecia, he considers cognition as an activity of living systems, the autonomy of interacting cells, and the distinction between anticipation and prediction, with implications for artificial intelligence.

Hosted by Paul Middlebrooks

Juan Gallego discusses whether neural manifolds are real explanatory structures and how population activity relates to behaviour. Topics include causal interpretations, evolutionary claims, motor control and the limits of low-dimensional descriptions, along with work on restoring movement after spinal-cord injury.

Tom Griffiths discusses mathematical accounts of cognition through logic, neural networks and probability. The conversation draws on his book The Laws of Thought to examine how these approaches complement one another, the ideas and people behind them, and prospects for a unified theory of mind.

Matthieu de Wit, Luis Favela and Vicente Raja examine how neuroscience can use ecological psychology without losing its theoretical commitments. Topics include perception and action, organism–environment relations, affordances, dynamics and the challenges of explaining naturalistic neural data within a field dominated by computational and mechanistic approaches.

Jaan Aru examines biological mechanisms that may matter for consciousness, including dendritic integration and interactions between cortex and thalamus. The discussion connects these mechanisms to cognition and prospects for artificial consciousness, then explores insight and creativity across ordinary problem-solving and altered experiences.

Michael Shadlen develops an account of how thoughts become conscious, drawing on decision-making research and embodied and ecological perspectives. The conversation connects neural activity and drift-diffusion models with unconscious and conscious thought, aiming to identify tractable directions for experimental consciousness research.

Tomaso Poggio discusses principles that could explain learning and intelligence in brains and machines. Topics include the relationship between engineering and theory, levels of explanation, the role of learning, and compositional sparsity and genericity as potential explanations for the effectiveness of deep networks.

Alex Maier discusses consciousness through the lens of visual neurophysiology and integrated information theory. The conversation examines the appeal of a formal mathematical account, how it relates to experiments on perception and cortical organisation, and the challenges of developing laws for subjective experience.