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Prediction-error neurons in circuits with multiple neuron types: formation, refinement, and functional implications.
File(s)
Hertag.pdf (1.54 MB)
Published version
Author(s)
Hertäg, Loreen
Clopath, Claudia
Type
Journal Article
Abstract
SignificanceAn influential idea in neuroscience is that neural circuits do not only passively process sensory information but rather actively compare them with predictions thereof. A core element of this comparison is prediction-error neurons, the activity of which only changes upon mismatches between actual and predicted sensory stimuli. While it has been shown that these prediction-error neurons come in different variants, it is largely unresolved how they are simultaneously formed and shaped by highly interconnected neural networks. By using a computational model, we study the circuit-level mechanisms that give rise to different variants of prediction-error neurons. Our results shed light on the formation, refinement, and robustness of prediction-error circuits, an important step toward a better understanding of predictive processing.
Date Issued
2022-03-29
Date Acceptance
2022-02-13
Citation
Proceedings of the National Academy of Sciences of USA, 2022, 119 (13), pp.e2115699119-e2115699119
URI
URL
DOI
ISSN
0027-8424
Publisher
National Academy of Sciences
Start Page
e2115699119
End Page
e2115699119
Journal / Book Title
Proceedings of the National Academy of Sciences of USA
Volume
119
Issue
13
Copyright Statement
© 2022 the Author(s). Published by PNAS.
This article is distributed under Creative Commons
Attribution-NonCommercial-NoDerivatives License 4.0
(CC BY-NC-ND).
License URL
Sponsor
Wellcome Trust
Biotechnology and Biological Sciences Research Council (BBSRC)
Biotechnology and Biological Sciences Research Cou
Simons Foundation
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/35320037
Grant Number
200790/Z/16/Z
BB/P018785/1
ORCA 64155 (BB/N013956/1)
Award ID:564408
Subjects
homeostatic plasticity
inhibitory interneurons
prediction-error neurons
predictive processing
sensory coding
Neural Networks, Computer
Neurons
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2022-03-23