Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves

At rest, healthy human brain activity is characterized by large electroencephalography (EEG) fluctuations in the 8-13 Hz range, commonly referred to as the alpha band. Although it is well known that EEG alpha activity varies across individuals, few studies have investigated how this may be related t...

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Main Authors:	Renauld, Emmanuelle, Descoteaux, Maxime, Bernier, Michaël, Garyfallidis, Eleftherios, Whittingstall, Kevin
Format:	Online
Language:	English
Published:	Public Library of Science 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934857/

id	pubmed-4934857
recordtype	oai_dc
spelling	pubmed-49348572016-07-18 Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves Renauld, Emmanuelle Descoteaux, Maxime Bernier, Michaël Garyfallidis, Eleftherios Whittingstall, Kevin Research Article At rest, healthy human brain activity is characterized by large electroencephalography (EEG) fluctuations in the 8-13 Hz range, commonly referred to as the alpha band. Although it is well known that EEG alpha activity varies across individuals, few studies have investigated how this may be related to underlying morphological variations in brain structure. Specifically, it is generally believed that the lateral geniculate nucleus (LGN) and its efferent fibres (optic radiation, OR) play a key role in alpha activity, yet it is unclear whether their shape or size variations contribute to its inter-subject variability. Given the widespread use of EEG alpha in basic and clinical research, addressing this is important, though difficult given the problems associated with reliably segmenting the LGN and OR. For this, we employed a multi-modal approach and combined diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI) and EEG in 20 healthy subjects to measure structure and function, respectively. For the former, we developed a new, semi-automated approach for segmenting the OR and LGN, from which we extracted several structural metrics such as volume, position and diffusivity. Although these measures corresponded well with known morphology based on previous post-mortem studies, we nonetheless found that their inter-subject variability was not significantly correlated to alpha power or peak frequency (p >0.05). Our results therefore suggest that alpha variability may be mediated by an alternative structural source and our proposed methodology may in general help in better understanding the influence of anatomy on function such as measured by EEG or fMRI. Public Library of Science 2016-07-06 /pmc/articles/PMC4934857/ /pubmed/27383146 http://dx.doi.org/10.1371/journal.pone.0156436 Text en © 2016 Renauld et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Renauld, Emmanuelle Descoteaux, Maxime Bernier, Michaël Garyfallidis, Eleftherios Whittingstall, Kevin
spellingShingle	Renauld, Emmanuelle Descoteaux, Maxime Bernier, Michaël Garyfallidis, Eleftherios Whittingstall, Kevin Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves
author_facet	Renauld, Emmanuelle Descoteaux, Maxime Bernier, Michaël Garyfallidis, Eleftherios Whittingstall, Kevin
author_sort	Renauld, Emmanuelle
title	Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves
title_short	Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves
title_full	Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves
title_fullStr	Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves
title_full_unstemmed	Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves
title_sort	semi-automatic segmentation of optic radiations and lgn, and their relationship to eeg alpha waves
description	At rest, healthy human brain activity is characterized by large electroencephalography (EEG) fluctuations in the 8-13 Hz range, commonly referred to as the alpha band. Although it is well known that EEG alpha activity varies across individuals, few studies have investigated how this may be related to underlying morphological variations in brain structure. Specifically, it is generally believed that the lateral geniculate nucleus (LGN) and its efferent fibres (optic radiation, OR) play a key role in alpha activity, yet it is unclear whether their shape or size variations contribute to its inter-subject variability. Given the widespread use of EEG alpha in basic and clinical research, addressing this is important, though difficult given the problems associated with reliably segmenting the LGN and OR. For this, we employed a multi-modal approach and combined diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI) and EEG in 20 healthy subjects to measure structure and function, respectively. For the former, we developed a new, semi-automated approach for segmenting the OR and LGN, from which we extracted several structural metrics such as volume, position and diffusivity. Although these measures corresponded well with known morphology based on previous post-mortem studies, we nonetheless found that their inter-subject variability was not significantly correlated to alpha power or peak frequency (p >0.05). Our results therefore suggest that alpha variability may be mediated by an alternative structural source and our proposed methodology may in general help in better understanding the influence of anatomy on function such as measured by EEG or fMRI.
publisher	Public Library of Science
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934857/
_version_	1613605087298453504

Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves

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