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Cortical oscillations support sampling-based computations in spiking neural networks
by
Korcsak-Gorzo, Agnes
, Baumbach, Andreas
, Leng, Luziwei
, Breitwieser, Oliver J.
, Müller, Michael G.
, Senn, Walter
, Legenstein, Robert
, van Albada, Sacha J.
, Petrovici, Mihai A.
, Meier, Karlheinz
in
Action Potentials
/ Biology and Life Sciences
/ Brain
/ Computational neuroscience
/ Computer and Information Sciences
/ Computer Simulation
/ Firing pattern
/ Mathematical models
/ Medicine and Health Sciences
/ Models, Neurological
/ Neural networks
/ Neural Networks, Computer
/ Neural oscillations
/ Neurons
/ Oscillations
/ Physical Sciences
/ Physiological aspects
/ Probabilistic inference
/ Psychological aspects
/ Rhythms
/ Sampling
/ Simulation
/ Social Sciences
/ Spiking
2022
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Cortical oscillations support sampling-based computations in spiking neural networks
by
Korcsak-Gorzo, Agnes
, Baumbach, Andreas
, Leng, Luziwei
, Breitwieser, Oliver J.
, Müller, Michael G.
, Senn, Walter
, Legenstein, Robert
, van Albada, Sacha J.
, Petrovici, Mihai A.
, Meier, Karlheinz
in
Action Potentials
/ Biology and Life Sciences
/ Brain
/ Computational neuroscience
/ Computer and Information Sciences
/ Computer Simulation
/ Firing pattern
/ Mathematical models
/ Medicine and Health Sciences
/ Models, Neurological
/ Neural networks
/ Neural Networks, Computer
/ Neural oscillations
/ Neurons
/ Oscillations
/ Physical Sciences
/ Physiological aspects
/ Probabilistic inference
/ Psychological aspects
/ Rhythms
/ Sampling
/ Simulation
/ Social Sciences
/ Spiking
2022
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Cortical oscillations support sampling-based computations in spiking neural networks
by
Korcsak-Gorzo, Agnes
, Baumbach, Andreas
, Leng, Luziwei
, Breitwieser, Oliver J.
, Müller, Michael G.
, Senn, Walter
, Legenstein, Robert
, van Albada, Sacha J.
, Petrovici, Mihai A.
, Meier, Karlheinz
in
Action Potentials
/ Biology and Life Sciences
/ Brain
/ Computational neuroscience
/ Computer and Information Sciences
/ Computer Simulation
/ Firing pattern
/ Mathematical models
/ Medicine and Health Sciences
/ Models, Neurological
/ Neural networks
/ Neural Networks, Computer
/ Neural oscillations
/ Neurons
/ Oscillations
/ Physical Sciences
/ Physiological aspects
/ Probabilistic inference
/ Psychological aspects
/ Rhythms
/ Sampling
/ Simulation
/ Social Sciences
/ Spiking
2022
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Cortical oscillations support sampling-based computations in spiking neural networks
Journal Article
Cortical oscillations support sampling-based computations in spiking neural networks
2022
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Overview
Being permanently confronted with an uncertain world, brains have faced evolutionary pressure to represent this uncertainty in order to respond appropriately. Often, this requires visiting multiple interpretations of the available information or multiple solutions to an encountered problem. This gives rise to the so-called mixing problem: since all of these “valid” states represent powerful attractors, but between themselves can be very dissimilar, switching between such states can be difficult. We propose that cortical oscillations can be effectively used to overcome this challenge. By acting as an effective temperature, background spiking activity modulates exploration. Rhythmic changes induced by cortical oscillations can then be interpreted as a form of simulated tempering. We provide a rigorous mathematical discussion of this link and study some of its phenomenological implications in computer simulations. This identifies a new computational role of cortical oscillations and connects them to various phenomena in the brain, such as sampling-based probabilistic inference, memory replay, multisensory cue combination, and place cell flickering.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
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