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Podcast with Aaron Schurger on free will and readiness potential
Season 2019 · Episode 1

Podcast with Aaron Schurger on free will and readiness potential

How collaboration arrises and why it fails · Prof. Dr. Paul F.M.J. Verschure

March 15, 20261h 11m

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Show Notes

What if the most famous experiment against free will was measuring the wrong thing all along? Neuroscientist Aaron Schurger explains why the readiness potential, long interpreted as the brain's decision signal, may be nothing more than autocorrelated neural noise crossing a threshold, fundamentally undermining decades of conclusions drawn from the Libet experiment. Subscribe for more from the Convergent Science Network podcast series. Aaron Schurger joins Paul Verschure and Tony Prescott to dissect the neuroscience of volition, starting with a careful distinction between free will, conscious will, and agency. The conversation zeroes in on the readiness potential, a slow buildup of brain activity preceding voluntary movement that Benjamin Libet famously used to argue the brain decides before we are aware of deciding. Schurger's drift-diffusion model offers an alternative: the readiness potential emerges naturally from stochastic neural fluctuations accumulating toward a threshold, not from any preparatory decision process. The evidence spans multiple species and methods. Murakami's 2014 study found ramping activity in rat premotor cortex consistent with an accumulator model. Schurger's own experiments show that when subjects are cued to respond at random moments, fast and slow reaction times correspond to different levels of ongoing neural fluctuation , a difference that precedes the unpredictable cue and therefore cannot reflect preparation. The discussion also addresses the Soon and Fried studies that claimed to predict decisions seconds in advance, with Schurger arguing that slightly-better-than-chance classification of brain states is exactly what autocorrelated noise would produce. Key topics include why the Libet paradigm minimizes rather than tests conscious volition, the role of pink noise and temporal autocorrelation in neural circuits, methodological pitfalls of using classifiers on brain data, and what a brain-computer interface approach might reveal about the causal relationship between conscious intention and action. Part of the Convergent Science Network podcast series from the BCBT Summer School.