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  Canonical microcircuits for predictive coding

Bastos, A., Usrey, W., Adams, R., Mangun, G., Fries, P., & Friston, K. (2012). Canonical microcircuits for predictive coding. Neuron, 76(4), 695-711. doi:10.1016/j.neuron.2012.10.038.

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Bastos_2012_CanonicalMicrocircuits.pdf (Publisher version), 2MB
 
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2012
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Open Archive/Elsevier User Licence. Copyright © 2012 Elsevier Inc.
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 Creators:
Bastos, Andre M.1, 2, Author
Usrey, W. Martin, Author
Adams, Rick A., Author
Mangun, George R., Author
Fries, Pascal1, 2, Author                 
Friston, Karl J., Author
Affiliations:
1Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, ou_2074314              
2Fries Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, DE, ou_3381216              

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Free keywords: Animals Cerebral Cortex/*anatomy & histology Computer Simulation Feedback, Physiological Functional Laterality Humans Models, Neurological Nerve Net/anatomy & histology/*physiology Neural Pathways/*physiology
 Abstract: This Perspective considers the influential notion of a canonical (cortical) microcircuit in light of recent theories about neuronal processing. Specifically, we conciliate quantitative studies of microcircuitry and the functional logic of neuronal computations. We revisit the established idea that message passing among hierarchical cortical areas implements a form of Bayesian inference-paying careful attention to the implications for intrinsic connections among neuronal populations. By deriving canonical forms for these computations, one can associate specific neuronal populations with specific computational roles. This analysis discloses a remarkable correspondence between the microcircuitry of the cortical column and the connectivity implied by predictive coding. Furthermore, it provides some intuitive insights into the functional asymmetries between feedforward and feedback connections and the characteristic frequencies over which they operate.

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 Dates: 2012-11-212012
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuron.2012.10.038
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Title: Neuron
Source Genre: Journal
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Pages: - Volume / Issue: 76 (4) Sequence Number: - Start / End Page: 695 - 711 Identifier: ISSN: 0896-6273