Adapting parcellation schemes to study fetal brain connectivity in serial imaging studies

Xi Cheng, Jakob Wilm, Sharmishtaa Seshamani, Mads Fogtmann, Christopher Kroenke, Colin Studholme

Research output: Contribution to journalArticle

Abstract

A crucial step in studying brain connectivity is the definition of the Regions Of Interest (ROI's) which are considered as nodes of a network graph. These ROI's identified in structural imaging reflect consistent functional regions in the anatomies being compared. However in serial studies of the developing fetal brain such functional and associated structural markers are not consistently present over time. In this study we adapt two non-atlas based parcellation schemes to study the development of connectivity networks of a fetal monkey brain using Diffusion Weighted Imaging techniques. Results demonstrate that the fetal brain network exhibits small-world characteristics and a pattern of increased cluster coefficients and decreased global efficiency. These findings may provide a route to creating a new biomarker for healthy fetal brain development.

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Brain
Imaging techniques
Small-world networks
Biomarkers
Fetal Development
Haplorhini
Anatomy

ASJC Scopus subject areas

  • Medicine(all)

Cite this

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title = "Adapting parcellation schemes to study fetal brain connectivity in serial imaging studies",
abstract = "A crucial step in studying brain connectivity is the definition of the Regions Of Interest (ROI's) which are considered as nodes of a network graph. These ROI's identified in structural imaging reflect consistent functional regions in the anatomies being compared. However in serial studies of the developing fetal brain such functional and associated structural markers are not consistently present over time. In this study we adapt two non-atlas based parcellation schemes to study the development of connectivity networks of a fetal monkey brain using Diffusion Weighted Imaging techniques. Results demonstrate that the fetal brain network exhibits small-world characteristics and a pattern of increased cluster coefficients and decreased global efficiency. These findings may provide a route to creating a new biomarker for healthy fetal brain development.",
author = "Xi Cheng and Jakob Wilm and Sharmishtaa Seshamani and Mads Fogtmann and Christopher Kroenke and Colin Studholme",
year = "2013",
doi = "10.1109/EMBC.2013.6609440",
language = "English (US)",
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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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AU - Wilm, Jakob

AU - Seshamani, Sharmishtaa

AU - Fogtmann, Mads

AU - Kroenke, Christopher

AU - Studholme, Colin

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AB - A crucial step in studying brain connectivity is the definition of the Regions Of Interest (ROI's) which are considered as nodes of a network graph. These ROI's identified in structural imaging reflect consistent functional regions in the anatomies being compared. However in serial studies of the developing fetal brain such functional and associated structural markers are not consistently present over time. In this study we adapt two non-atlas based parcellation schemes to study the development of connectivity networks of a fetal monkey brain using Diffusion Weighted Imaging techniques. Results demonstrate that the fetal brain network exhibits small-world characteristics and a pattern of increased cluster coefficients and decreased global efficiency. These findings may provide a route to creating a new biomarker for healthy fetal brain development.

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