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Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants

The infant brain is unlike the adult brain, with considerable differences in morphological, neurodynamic, and haemodynamic features. As the majority of current MRI analysis tools were designed for use in adults, a primary objective of the Developing Human Connectome Project (dHCP) is to develop opti...

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Autores principales: Baxter, Luke, Fitzgibbon, Sean, Moultrie, Fiona, Goksan, Sezgi, Jenkinson, Mark, Smith, Stephen, Andersson, Jesper, Duff, Eugene, Slater, Rebeccah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347570/
https://www.ncbi.nlm.nih.gov/pubmed/30414984
http://dx.doi.org/10.1016/j.neuroimage.2018.11.006
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author Baxter, Luke
Fitzgibbon, Sean
Moultrie, Fiona
Goksan, Sezgi
Jenkinson, Mark
Smith, Stephen
Andersson, Jesper
Duff, Eugene
Slater, Rebeccah
author_facet Baxter, Luke
Fitzgibbon, Sean
Moultrie, Fiona
Goksan, Sezgi
Jenkinson, Mark
Smith, Stephen
Andersson, Jesper
Duff, Eugene
Slater, Rebeccah
author_sort Baxter, Luke
collection PubMed
description The infant brain is unlike the adult brain, with considerable differences in morphological, neurodynamic, and haemodynamic features. As the majority of current MRI analysis tools were designed for use in adults, a primary objective of the Developing Human Connectome Project (dHCP) is to develop optimised methodological pipelines for the analysis of neonatal structural, resting state, and diffusion MRI data. Here, in an independent neonatal dataset we have extended and optimised the dHCP fMRI preprocessing pipeline for the analysis of stimulus-response fMRI data. We describe and validate this extended dHCP fMRI preprocessing pipeline to analyse changes in brain activity evoked following an acute noxious stimulus applied to the infant's foot. We compare the results obtained from this extended dHCP pipeline to results obtained from a typical FSL FEAT-based analysis pipeline, evaluating the pipelines' outputs using a wide range of tests. We demonstrate that a substantial increase in spatial specificity and sensitivity to signal can be attained with a bespoke neonatal preprocessing pipeline through optimised motion and distortion correction, ICA-based denoising, and haemodynamic modelling. The improved sensitivity and specificity, made possible with this extended dHCP pipeline, will be paramount in making further progress in our understanding of the development of sensory processing in the infant brain.
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spelling pubmed-63475702019-02-01 Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants Baxter, Luke Fitzgibbon, Sean Moultrie, Fiona Goksan, Sezgi Jenkinson, Mark Smith, Stephen Andersson, Jesper Duff, Eugene Slater, Rebeccah Neuroimage Article The infant brain is unlike the adult brain, with considerable differences in morphological, neurodynamic, and haemodynamic features. As the majority of current MRI analysis tools were designed for use in adults, a primary objective of the Developing Human Connectome Project (dHCP) is to develop optimised methodological pipelines for the analysis of neonatal structural, resting state, and diffusion MRI data. Here, in an independent neonatal dataset we have extended and optimised the dHCP fMRI preprocessing pipeline for the analysis of stimulus-response fMRI data. We describe and validate this extended dHCP fMRI preprocessing pipeline to analyse changes in brain activity evoked following an acute noxious stimulus applied to the infant's foot. We compare the results obtained from this extended dHCP pipeline to results obtained from a typical FSL FEAT-based analysis pipeline, evaluating the pipelines' outputs using a wide range of tests. We demonstrate that a substantial increase in spatial specificity and sensitivity to signal can be attained with a bespoke neonatal preprocessing pipeline through optimised motion and distortion correction, ICA-based denoising, and haemodynamic modelling. The improved sensitivity and specificity, made possible with this extended dHCP pipeline, will be paramount in making further progress in our understanding of the development of sensory processing in the infant brain. Academic Press 2019-02-01 /pmc/articles/PMC6347570/ /pubmed/30414984 http://dx.doi.org/10.1016/j.neuroimage.2018.11.006 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Baxter, Luke
Fitzgibbon, Sean
Moultrie, Fiona
Goksan, Sezgi
Jenkinson, Mark
Smith, Stephen
Andersson, Jesper
Duff, Eugene
Slater, Rebeccah
Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants
title Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants
title_full Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants
title_fullStr Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants
title_full_unstemmed Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants
title_short Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants
title_sort optimising neonatal fmri data analysis: design and validation of an extended dhcp preprocessing pipeline to characterise noxious-evoked brain activity in infants
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347570/
https://www.ncbi.nlm.nih.gov/pubmed/30414984
http://dx.doi.org/10.1016/j.neuroimage.2018.11.006
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