This title appears in the Scientific Report :
2021
Please use the identifier:
http://hdl.handle.net/2128/28438 in citations.
Cortical oscillations implement a backbone for sampling-based computation in spiking neural networks
Cortical oscillations implement a backbone for sampling-based computation in spiking neural networks
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 giv...
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Personal Name(s): | Korcsak-Gorzo, Agnes (Corresponding author) |
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Müller, Michael G. / Baumbach, Andreas / Leng, Luziwei / Breitwieser, Oliver Julien / van Albada, Sacha J. / Senn, Walter / Meier, Karlheinz / Legenstein, Robert / Petrovici, Mihai A. | |
Contributing Institute: |
Computational and Systems Neuroscience; INM-6 Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 |
Published in: | 2021 |
Imprint: |
2021
|
Document Type: |
Preprint |
Research Program: |
JL SMHB - Joint Lab Supercomputing and Modeling for the Human Brain (JL SMHB-2021-2027) Human Brain Project Specific Grant Agreement 3 Human Brain Project Specific Grant Agreement 2 Computational Principles |
Link: |
Get full text OpenAccess |
Publikationsportal JuSER |
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. |