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Mapping the Scene and Object Processing Networks by Intracranial EEG

Human perception and cognition are based predominantly on visual information processing. Much of the information regarding neuronal correlates of visual processing has been derived from functional imaging studies, which have identified a variety of brain areas contributing to visual analysis, recogn...

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Autores principales: Vlcek, Kamil, Fajnerova, Iveta, Nekovarova, Tereza, Hejtmanek, Lukas, Janca, Radek, Jezdik, Petr, Kalina, Adam, Tomasek, Martin, Krsek, Pavel, Hammer, Jiri, Marusic, Petr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581859/
https://www.ncbi.nlm.nih.gov/pubmed/33192393
http://dx.doi.org/10.3389/fnhum.2020.561399
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author Vlcek, Kamil
Fajnerova, Iveta
Nekovarova, Tereza
Hejtmanek, Lukas
Janca, Radek
Jezdik, Petr
Kalina, Adam
Tomasek, Martin
Krsek, Pavel
Hammer, Jiri
Marusic, Petr
author_facet Vlcek, Kamil
Fajnerova, Iveta
Nekovarova, Tereza
Hejtmanek, Lukas
Janca, Radek
Jezdik, Petr
Kalina, Adam
Tomasek, Martin
Krsek, Pavel
Hammer, Jiri
Marusic, Petr
author_sort Vlcek, Kamil
collection PubMed
description Human perception and cognition are based predominantly on visual information processing. Much of the information regarding neuronal correlates of visual processing has been derived from functional imaging studies, which have identified a variety of brain areas contributing to visual analysis, recognition, and processing of objects and scenes. However, only two of these areas, namely the parahippocampal place area (PPA) and the lateral occipital complex (LOC), were verified and further characterized by intracranial electroencephalogram (iEEG). iEEG is a unique measurement technique that samples a local neuronal population with high temporal and anatomical resolution. In the present study, we aimed to expand on previous reports and examine brain activity for selectivity of scenes and objects in the broadband high-gamma frequency range (50–150 Hz). We collected iEEG data from 27 epileptic patients while they watched a series of images, containing objects and scenes, and we identified 375 bipolar channels responding to at least one of these two categories. Using K-means clustering, we delineated their brain localization. In addition to the two areas described previously, we detected significant responses in two other scene-selective areas, not yet reported by any electrophysiological studies; namely the occipital place area (OPA) and the retrosplenial complex. Moreover, using iEEG we revealed a much broader network underlying visual processing than that described to date, using specialized functional imaging experimental designs. Here, we report the selective brain areas for scene processing include the posterior collateral sulcus and the anterior temporal region, which were already shown to be related to scene novelty and landmark naming. The object-selective responses appeared in the parietal, frontal, and temporal regions connected with tool use and object recognition. The temporal analyses specified the time course of the category selectivity through the dorsal and ventral visual streams. The receiver operating characteristic analyses identified the PPA and the fusiform portion of the LOC as being the most selective for scenes and objects, respectively. Our findings represent a valuable overview of visual processing selectivity for scenes and objects based on iEEG analyses and thus, contribute to a better understanding of visual processing in the human brain.
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spelling pubmed-75818592020-11-13 Mapping the Scene and Object Processing Networks by Intracranial EEG Vlcek, Kamil Fajnerova, Iveta Nekovarova, Tereza Hejtmanek, Lukas Janca, Radek Jezdik, Petr Kalina, Adam Tomasek, Martin Krsek, Pavel Hammer, Jiri Marusic, Petr Front Hum Neurosci Human Neuroscience Human perception and cognition are based predominantly on visual information processing. Much of the information regarding neuronal correlates of visual processing has been derived from functional imaging studies, which have identified a variety of brain areas contributing to visual analysis, recognition, and processing of objects and scenes. However, only two of these areas, namely the parahippocampal place area (PPA) and the lateral occipital complex (LOC), were verified and further characterized by intracranial electroencephalogram (iEEG). iEEG is a unique measurement technique that samples a local neuronal population with high temporal and anatomical resolution. In the present study, we aimed to expand on previous reports and examine brain activity for selectivity of scenes and objects in the broadband high-gamma frequency range (50–150 Hz). We collected iEEG data from 27 epileptic patients while they watched a series of images, containing objects and scenes, and we identified 375 bipolar channels responding to at least one of these two categories. Using K-means clustering, we delineated their brain localization. In addition to the two areas described previously, we detected significant responses in two other scene-selective areas, not yet reported by any electrophysiological studies; namely the occipital place area (OPA) and the retrosplenial complex. Moreover, using iEEG we revealed a much broader network underlying visual processing than that described to date, using specialized functional imaging experimental designs. Here, we report the selective brain areas for scene processing include the posterior collateral sulcus and the anterior temporal region, which were already shown to be related to scene novelty and landmark naming. The object-selective responses appeared in the parietal, frontal, and temporal regions connected with tool use and object recognition. The temporal analyses specified the time course of the category selectivity through the dorsal and ventral visual streams. The receiver operating characteristic analyses identified the PPA and the fusiform portion of the LOC as being the most selective for scenes and objects, respectively. Our findings represent a valuable overview of visual processing selectivity for scenes and objects based on iEEG analyses and thus, contribute to a better understanding of visual processing in the human brain. Frontiers Media S.A. 2020-10-09 /pmc/articles/PMC7581859/ /pubmed/33192393 http://dx.doi.org/10.3389/fnhum.2020.561399 Text en Copyright © 2020 Vlcek, Fajnerova, Nekovarova, Hejtmanek, Janca, Jezdik, Kalina, Tomasek, Krsek, Hammer and Marusic. http://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 Human Neuroscience
Vlcek, Kamil
Fajnerova, Iveta
Nekovarova, Tereza
Hejtmanek, Lukas
Janca, Radek
Jezdik, Petr
Kalina, Adam
Tomasek, Martin
Krsek, Pavel
Hammer, Jiri
Marusic, Petr
Mapping the Scene and Object Processing Networks by Intracranial EEG
title Mapping the Scene and Object Processing Networks by Intracranial EEG
title_full Mapping the Scene and Object Processing Networks by Intracranial EEG
title_fullStr Mapping the Scene and Object Processing Networks by Intracranial EEG
title_full_unstemmed Mapping the Scene and Object Processing Networks by Intracranial EEG
title_short Mapping the Scene and Object Processing Networks by Intracranial EEG
title_sort mapping the scene and object processing networks by intracranial eeg
topic Human Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581859/
https://www.ncbi.nlm.nih.gov/pubmed/33192393
http://dx.doi.org/10.3389/fnhum.2020.561399
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