About: Bayesian approaches to brain function

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Bayesian approaches to brain function investigate the capacity of the nervous system to operate in situations of uncertainty in a fashion that is close to the optimal prescribed by Bayesian statistics. This term is used in behavioural sciences and neuroscience and studies associated with this term often strive to explain the brain's cognitive abilities based on statistical principles. It is frequently assumed that the nervous system maintains internal probabilistic models that are updated by neural processing of sensory information using methods approximating those of Bayesian probability.

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rdfs:label	Bayesian approaches to brain function (en)
rdfs:comment	Bayesian approaches to brain function investigate the capacity of the nervous system to operate in situations of uncertainty in a fashion that is close to the optimal prescribed by Bayesian statistics. This term is used in behavioural sciences and neuroscience and studies associated with this term often strive to explain the brain's cognitive abilities based on statistical principles. It is frequently assumed that the nervous system maintains internal probabilistic models that are updated by neural processing of sensory information using methods approximating those of Bayesian probability. (en)
rdfs:seeAlso	Bayesian inference Motor learning
dct:subject	Probabilistic models Cognitive neuroscience Computational neuroscience Bayesian statistics
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Wikipage revision ID	1068716430 (xsd:integer)
Link from a Wikipage to another Wikipage	Bayesian cognitive science Bayesian probability Bayesian statistics Probabilistic models Predictive coding Priming (psychology) Psychology Cognitive neuroscience Human brain Peter Dayan Richard Threlkeld Cox Mental model Quantum cognition Edwin Thompson Jaynes Geoffrey Hinton Thermodynamic free energy Thomas Bayes Machine learning Computational neuroscience Helmholtz machine Michael S. Landy Computational neuroscience Kalman filter Harold Jeffreys Hierarchical temporal memory Jeff Hawkins Bayesian statistics Cognitive architecture Pierre-Simon Laplace Free energy principle The free energy principle Michael Shadlen New Scientist Markov chain Neural computation Neuroscience Experimental psychology Unsupervised learning Karl Friston Mismatch negativity 2IFC Variational Bayes Probabilistic model Hermann Helmholtz
Link from a Wikipage to an external page	http://www.universaldarwinism.com/Friston%20Karl.htm https://web.archive.org/web/20200207175240/http:/www.universaldarwinism.com/Friston%20Karl.htm
sameAs	Bayesian approaches to brain function Bayesian approaches to brain function Bayesian approaches to brain function Bayesian approaches to brain function Bayesian approaches to brain function
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date	2020-02-07 (xsd:date)
url	https://web.archive.org/web/20200207175240/http:/www.universaldarwinism.com/Friston%20Karl.htm
has abstract	Bayesian approaches to brain function investigate the capacity of the nervous system to operate in situations of uncertainty in a fashion that is close to the optimal prescribed by Bayesian statistics. This term is used in behavioural sciences and neuroscience and studies associated with this term often strive to explain the brain's cognitive abilities based on statistical principles. It is frequently assumed that the nervous system maintains internal probabilistic models that are updated by neural processing of sensory information using methods approximating those of Bayesian probability. (en)
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is Link from a Wikipage to another Wikipage of	Bayesian cognitive science Bayesian inference Bayesian inference in motor learning Schizophrenia Biological neuron model Visual perception Intrinsic motivation (artificial intelligence) Quantum cognition Brain-reading Consciousness and the Brain Computational neuroscience Cutaneous rabbit illusion Kappa effect

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