À PROPOS DE CET ÉPISODE
Active Inference Insights 013 is all about modelling: not only how we model our lived world, but also how we might scientifically model that modelling process ourselves. With neuro-computationalist Ryan Smith at the helm, expect to learn about the difference between empirical computational psychiatry and in-silico simulations, the role of aberrant precision-weighting in neuropsychological disorders and how a little parameter called ‘gamma’ might hold the key to a life of wellbeing.
Anglais
États-Unis
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RECHERCHER LES ÉPISODES PASSÉS
Rechercher les épisodes précédents de Active Inference Insights.
AUTRES ÉPISODES DANS CE PODCAST
In this episode of Active Inference Insights, Darius invites philosopher and machine learning expert Alex Kiefer onto the show. Together, they tackle the big issues, from the role of representations in Active Inference to Bayesian structural realism, Helmholtz machines to POMDPs.
This week’s Active Inference Insights is a rollercoaster of all things cognitive, brought to you by Darius and philosopher / neurophenomenologist Julian Kiverstein. Over three hours you can expect to learn about non-representational cognition, affordances, the irreducibility of phenomena, self-mode…
Amygdala lovers unite: this one is for you. This week, Darius and neuroscientist Ronald Sladky explore the wonderful and wacky world of subcortical structures, with a special focus on the mysterious, infamous amygdala. This conversation also details developments in brain imaging, and attempts to br…
In this episode of Active Inference Insights, we welcome our first mathematician onto the show: Lance Da Costa. If you’re into Langevins, Fokker-Plancks, solenoidals and Fisher information metric tensors, this one is for you. However, if all that terrifies you to high heaven, don’t fret; Lance and …
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