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Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice
INTRODUCTION: The visual cortex is a key region in the mouse brain, responsible for processing visual information. Comprised of six distinct layers, each with unique neuronal types and connections, the visual cortex exhibits diverse decoding properties across its layers. This study aimed to investig...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560757/ https://www.ncbi.nlm.nih.gov/pubmed/37817884 http://dx.doi.org/10.3389/fncel.2023.1238777 |
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author | Kong, Chui Wang, Yangzhen Xiao, Guihua |
author_facet | Kong, Chui Wang, Yangzhen Xiao, Guihua |
author_sort | Kong, Chui |
collection | PubMed |
description | INTRODUCTION: The visual cortex is a key region in the mouse brain, responsible for processing visual information. Comprised of six distinct layers, each with unique neuronal types and connections, the visual cortex exhibits diverse decoding properties across its layers. This study aimed to investigate the relationship between visual stimulus decoding properties and the cortical layers of the visual cortex while considering how this relationship varies across different decoders and brain regions. METHODS: This study reached the above conclusions by analyzing two publicly available datasets obtained through two-photon microscopy of visual cortex neuronal responses. Various types of decoders were tested for visual cortex decoding. RESULTS: Our findings indicate that the decoding accuracy of neuronal populations with consistent sizes varies among visual cortical layers for visual stimuli such as drift gratings and natural images. In particular, layer 4 neurons in VISp exhibited significantly higher decoding accuracy for visual stimulus identity compared to other layers. However, in VISm, the decoding accuracy of neuronal populations with the same size in layer 2/3 was higher than that in layer 4, despite the overall accuracy being lower than that in VISp and VISl. Furthermore, SVM surpassed other decoders in terms of accuracy, with the variation in decoding performance across layers being consistent among decoders. Additionally, we found that the difference in decoding accuracy across different imaging depths was not associated with the mean orientation selectivity index (OSI) and the mean direction selectivity index (DSI) neurons, but showed a significant positive correlation with the mean reliability and mean signal-to-noise ratio (SNR) of each layer's neuron population. DISCUSSION: These findings lend new insights into the decoding properties of the visual cortex, highlighting the role of different cortical layers and decoders in determining decoding accuracy. The correlations identified between decoding accuracy and factors such as reliability and SNR pave the way for more nuanced understandings of visual cortex functioning. |
format | Online Article Text |
id | pubmed-10560757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105607572023-10-10 Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice Kong, Chui Wang, Yangzhen Xiao, Guihua Front Cell Neurosci Cellular Neuroscience INTRODUCTION: The visual cortex is a key region in the mouse brain, responsible for processing visual information. Comprised of six distinct layers, each with unique neuronal types and connections, the visual cortex exhibits diverse decoding properties across its layers. This study aimed to investigate the relationship between visual stimulus decoding properties and the cortical layers of the visual cortex while considering how this relationship varies across different decoders and brain regions. METHODS: This study reached the above conclusions by analyzing two publicly available datasets obtained through two-photon microscopy of visual cortex neuronal responses. Various types of decoders were tested for visual cortex decoding. RESULTS: Our findings indicate that the decoding accuracy of neuronal populations with consistent sizes varies among visual cortical layers for visual stimuli such as drift gratings and natural images. In particular, layer 4 neurons in VISp exhibited significantly higher decoding accuracy for visual stimulus identity compared to other layers. However, in VISm, the decoding accuracy of neuronal populations with the same size in layer 2/3 was higher than that in layer 4, despite the overall accuracy being lower than that in VISp and VISl. Furthermore, SVM surpassed other decoders in terms of accuracy, with the variation in decoding performance across layers being consistent among decoders. Additionally, we found that the difference in decoding accuracy across different imaging depths was not associated with the mean orientation selectivity index (OSI) and the mean direction selectivity index (DSI) neurons, but showed a significant positive correlation with the mean reliability and mean signal-to-noise ratio (SNR) of each layer's neuron population. DISCUSSION: These findings lend new insights into the decoding properties of the visual cortex, highlighting the role of different cortical layers and decoders in determining decoding accuracy. The correlations identified between decoding accuracy and factors such as reliability and SNR pave the way for more nuanced understandings of visual cortex functioning. Frontiers Media S.A. 2023-09-25 /pmc/articles/PMC10560757/ /pubmed/37817884 http://dx.doi.org/10.3389/fncel.2023.1238777 Text en Copyright © 2023 Kong, Wang and Xiao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cellular Neuroscience Kong, Chui Wang, Yangzhen Xiao, Guihua Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice |
title | Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice |
title_full | Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice |
title_fullStr | Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice |
title_full_unstemmed | Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice |
title_short | Neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice |
title_sort | neuron populations across layer 2-6 in the mouse visual cortex exhibit different coding abilities in the awake mice |
topic | Cellular Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560757/ https://www.ncbi.nlm.nih.gov/pubmed/37817884 http://dx.doi.org/10.3389/fncel.2023.1238777 |
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