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Probabilistic Inference in Neural Circuits: From Humans to Insects

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Air date: Monday, December 6, 2010, 12:00:00 PM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 71 * This only includes stats from October 2011 and forward.
Category: Neuroscience
Runtime: 00:57:14
Description: Neuroscience Seminar Series

A wide range of behaviors can be formalized as instances of probabilistic inferences. This includes odor recognition in insects, navigation in rodents, motor control, decision making in primates, simple arithmetic in children and monkeys, and causal reasoning in humans, to name just a few. In all cases, the probabilistic inferences involve products of distributions and marginalization. Dr. Pouget's lab will show that, given the type of variability reported in neural responses, products of distributions can be implemented through linear operations over firing rates, while marginalization over Gaussian random variables requires a particular nonlinearity known as quadratic divisive normalization. Both operations are conspicuous in many neural circuits raising the possibility that seemingly unrelated behaviors could in fact rely on very similar neural mechanisms across different species.

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NLM Title: Probabilistic inference in neural circuits : from humans to insects [electronic resource] / Alexandre Pouget.
Series: NIH neuroscience seminar series
Author: Pouget, Alexandre.
National Institutes of Health (U.S.)
Publisher:
Other Title(s): NIH neuroscience seminar series
Abstract: (CIT): A wide range of behaviors can be formalized as instances of probabilistic inferences. This includes odor recognition in insects, navigation in rodents, motor control, decision making in primates, simple arithmetic in children and monkeys, and causal reasoning in humans, to name just a few. In all cases, the probabilistic inferences involve products of distributions and marginalization. Dr. Pouget's lab will show that, given the type of variability reported in neural responses, products of distributions can be implemented through linear operations over firing rates, while marginalization over Gaussian random variables requires a particular nonlinearity known as quadratic divisive normalization. Both operations are conspicuous in many neural circuits raising the possibility that seemingly unrelated behaviors could in fact rely on very similar neural mechanisms across different species.
Subjects: Behavior--physiology
Models, Statistical
Nerve Net--physiology
Probability Learning
Probability Theory
Publication Types: Lectures
Webcasts
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NLM Classification: WL 102
NLM ID: 101556007
CIT Live ID: 9776
Permanent link: https://videocast.nih.gov/launch.asp?16318

 

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