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University of Cambridge > Talks.cam > Computational Neuroscience > Computational Neuroscience Journal Club
Computational Neuroscience Journal ClubAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Jake Stroud. Please join us for our fortnightly journal club online via zoom where two presenters will jointly present a topic together. The next topic is ‘Mental simulation for prediction and inference of physical systems’ presented by Kris Jensen and Marine Schimel. Zoom information: https://us02web.zoom.us/j/84958321096?pwd=dFpsYnpJYWVNeHlJbEFKbW1OTzFiQT09 Meeting ID: 849 5832 1096 Passcode: 506576 Summary: Humans and other animals have an impressive capacity for inferring and predicting physical phenomena, yet it remains unclear how the brain performs these complex computations from sensory input. We will provide an overview of work which models the understanding of ‘intuitive physics’ as a combination of noisy Bayesian inference and an internal ‘physics engine’ that approximates Newtonian mechanics. We will consider both how this framework can be used to predict the evolution of physical systems, and how it allows inference of the underlying physical parameters from observations of the temporal evolution of the world. Recommended reading: Battaglia et al. (PNAS 2013): “Simulation as an engine of physical scene understanding”. Hamrick et al. (Cognition 2016): “Inferring mass in complex scenes by mental simulation”. Schwettmann et al. (eLife 2019): “Invariant representations of mass in the human brain”. This talk is part of the Computational Neuroscience series. This talk is included in these lists:
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