Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Kong, Chui, Wang, Yangzhen, Xiao, Guihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
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
_version_ 1785117790690082816
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
work_keys_str_mv AT kongchui neuronpopulationsacrosslayer26inthemousevisualcortexexhibitdifferentcodingabilitiesintheawakemice
AT wangyangzhen neuronpopulationsacrosslayer26inthemousevisualcortexexhibitdifferentcodingabilitiesintheawakemice
AT xiaoguihua neuronpopulationsacrosslayer26inthemousevisualcortexexhibitdifferentcodingabilitiesintheawakemice