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Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications
Predictable sensory stimuli do not evoke significant responses in a subset of cortical excitatory neurons. Some of those neurons, however, change their activity upon mismatches between actual and predicted stimuli. Different variants of these prediction-error neurons exist, and they differ in their...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060484/ https://www.ncbi.nlm.nih.gov/pubmed/35320037 http://dx.doi.org/10.1073/pnas.2115699119 |
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author | Hertäg, Loreen Clopath, Claudia |
author_facet | Hertäg, Loreen Clopath, Claudia |
author_sort | Hertäg, Loreen |
collection | PubMed |
description | Predictable sensory stimuli do not evoke significant responses in a subset of cortical excitatory neurons. Some of those neurons, however, change their activity upon mismatches between actual and predicted stimuli. Different variants of these prediction-error neurons exist, and they differ in their responses to unexpected sensory stimuli. However, it is unclear how these variants can develop and coexist in the same recurrent network and how they are simultaneously shaped by the astonishing diversity of inhibitory interneurons. Here, we study these questions in a computational network model with three types of inhibitory interneurons. We find that balancing excitation and inhibition in multiple pathways gives rise to heterogeneous prediction-error circuits. Dependent on the network’s initial connectivity and distribution of actual and predicted sensory inputs, these circuits can form different variants of prediction-error neurons that are robust to network perturbations and generalize to stimuli not seen during learning. These variants can be learned simultaneously via homeostatic inhibitory plasticity with low baseline firing rates. Finally, we demonstrate that prediction-error neurons can support biased perception, we illustrate a number of functional implications, and we discuss testable predictions. |
format | Online Article Text |
id | pubmed-9060484 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-90604842022-09-23 Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications Hertäg, Loreen Clopath, Claudia Proc Natl Acad Sci U S A Biological Sciences Predictable sensory stimuli do not evoke significant responses in a subset of cortical excitatory neurons. Some of those neurons, however, change their activity upon mismatches between actual and predicted stimuli. Different variants of these prediction-error neurons exist, and they differ in their responses to unexpected sensory stimuli. However, it is unclear how these variants can develop and coexist in the same recurrent network and how they are simultaneously shaped by the astonishing diversity of inhibitory interneurons. Here, we study these questions in a computational network model with three types of inhibitory interneurons. We find that balancing excitation and inhibition in multiple pathways gives rise to heterogeneous prediction-error circuits. Dependent on the network’s initial connectivity and distribution of actual and predicted sensory inputs, these circuits can form different variants of prediction-error neurons that are robust to network perturbations and generalize to stimuli not seen during learning. These variants can be learned simultaneously via homeostatic inhibitory plasticity with low baseline firing rates. Finally, we demonstrate that prediction-error neurons can support biased perception, we illustrate a number of functional implications, and we discuss testable predictions. National Academy of Sciences 2022-03-23 2022-03-29 /pmc/articles/PMC9060484/ /pubmed/35320037 http://dx.doi.org/10.1073/pnas.2115699119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Biological Sciences Hertäg, Loreen Clopath, Claudia Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications |
title | Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications |
title_full | Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications |
title_fullStr | Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications |
title_full_unstemmed | Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications |
title_short | Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications |
title_sort | prediction-error neurons in circuits with multiple neuron types: formation, refinement, and functional implications |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060484/ https://www.ncbi.nlm.nih.gov/pubmed/35320037 http://dx.doi.org/10.1073/pnas.2115699119 |
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