Literature DB >> 29990581

Resting-state functional MRI studies on infant brains: A decade of gap-filling efforts.

Han Zhang1, Dinggang Shen2, Weili Lin3.   

Abstract

Resting-state functional MRI (rs-fMRI) is one of the most prevalent brain functional imaging modalities. Previous rs-fMRI studies have mainly focused on adults and elderly subjects. Recently, infant rs-fMRI studies have become an area of active research. After a decade of gap filling studies, many facets of the brain functional development from early infancy to toddler has been uncovered. However, infant rs-fMRI is still in its infancy. The image analysis tools for neonates and young infants can be quite different from those for adults. From data analysis to result interpretation, more questions and issues have been raised, and new hypotheses have been formed. With the anticipated availability of unprecedented high-resolution rs-fMRI and dedicated analysis pipelines from the Baby Connectome Project (BCP), it is important now to revisit previous findings and hypotheses, discuss and comment existing issues and problems, and make a "to-do-list" for the future studies. This review article aims to comprehensively review a decade of the findings, unveiling hidden jewels of the fields of developmental neuroscience and neuroimage computing. Emphases will be given to early infancy, particularly the first few years of life. In this review, an end-to-end summary, from infant rs-fMRI experimental design to data processing, and from the development of individual functional systems to large-scale brain functional networks, is provided. A comprehensive summary of the rs-fMRI findings in developmental patterns is highlighted. Furthermore, an extensive summary of the neurodevelopmental disorders and the effects of other hazardous factors is provided. Finally, future research trends focusing on emerging dynamic functional connectivity and state-of-the-art functional connectome analysis are summarized. In next decade, early infant rs-fMRI and developmental connectome study could be one of the shining research topics.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Autism; Baby connectome project; Brain network; Children; Connectome; Development; Dynamic functional connectivity; Functional MRI; Functional connectivity; Graph-theoretical analysis; Infant; Neonate; Resting state; Toddler

Mesh:

Year:  2018        PMID: 29990581      PMCID: PMC6289773          DOI: 10.1016/j.neuroimage.2018.07.004

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  194 in total

1.  Community structure in time-dependent, multiscale, and multiplex networks.

Authors:  Peter J Mucha; Thomas Richardson; Kevin Macon; Mason A Porter; Jukka-Pekka Onnela
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Review 2.  Sensitive periods in the development of the brain and behavior.

Authors:  Eric I Knudsen
Journal:  J Cogn Neurosci       Date:  2004-10       Impact factor: 3.225

Review 3.  Unrest at rest: default activity and spontaneous network correlations.

Authors:  Randy L Buckner; Justin L Vincent
Journal:  Neuroimage       Date:  2007-01-25       Impact factor: 6.556

4.  Consistent reconstruction of cortical surfaces from longitudinal brain MR images.

Authors:  Gang Li; Jingxin Nie; Guorong Wu; Yaping Wang; Dinggang Shen
Journal:  Neuroimage       Date:  2011-11-15       Impact factor: 6.556

Review 5.  Short-range connections in the developmental connectome during typical and atypical brain maturation.

Authors:  Minhui Ouyang; Huiying Kang; John A Detre; Timothy P L Roberts; Hao Huang
Journal:  Neurosci Biobehav Rev       Date:  2017-10-09       Impact factor: 8.989

6.  A dynamic 4D probabilistic atlas of the developing brain.

Authors:  Maria Kuklisova-Murgasova; Paul Aljabar; Latha Srinivasan; Serena J Counsell; Valentina Doria; Ahmed Serag; Ioannis S Gousias; James P Boardman; Mary A Rutherford; A David Edwards; Joseph V Hajnal; Daniel Rueckert
Journal:  Neuroimage       Date:  2010-10-20       Impact factor: 6.556

7.  Fetal functional imaging portrays heterogeneous development of emerging human brain networks.

Authors:  András Jakab; Ernst Schwartz; Gregor Kasprian; Gerlinde M Gruber; Daniela Prayer; Veronika Schöpf; Georg Langs
Journal:  Front Hum Neurosci       Date:  2014-10-22       Impact factor: 3.169

8.  Thalamocortical Connectivity Predicts Cognition in Children Born Preterm.

Authors:  Gareth Ball; Libuse Pazderova; Andrew Chew; Nora Tusor; Nazakat Merchant; Tomoki Arichi; Joanna M Allsop; Frances M Cowan; A David Edwards; Serena J Counsell
Journal:  Cereb Cortex       Date:  2015-01-16       Impact factor: 5.357

9.  Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity.

Authors:  William Hedley Thompson; Peter Fransson
Journal:  Sci Rep       Date:  2016-12-19       Impact factor: 4.379

10.  Exploring Dynamic Brain Functional Networks Using Continuous "State-Related" Functional MRI.

Authors:  Xun Li; Yu-Feng Zang; Han Zhang
Journal:  Biomed Res Int       Date:  2015-08-27       Impact factor: 3.411

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  35 in total

1.  A Computational Framework for Dissociating Development-Related from Individually Variable Flexibility in Regional Modularity Assignment in Early Infancy.

Authors:  Mayssa Soussia; Xuyun Wen; Zhen Zhou; Bing Jin; Tae-Eui Kam; Li-Ming Hsu; Zhengwang Wu; Gang Li; Li Wang; Islem Rekik; Weili Lin; Dinggang Shen; Han Zhang
Journal:  Med Image Comput Comput Assist Interv       Date:  2020-09-29

2.  Disentangled Intensive Triplet Autoencoder for Infant Functional Connectome Fingerprinting.

Authors:  Dan Hu; Fan Wang; Han Zhang; Zhengwang Wu; Li Wang; Weili Lin; Gang Li; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2020-09-29

3.  Disentangled-Multimodal Adversarial Autoencoder: Application to Infant Age Prediction With Incomplete Multimodal Neuroimages.

Authors:  Dan Hu; Han Zhang; Zhengwang Wu; Fan Wang; Li Wang; J Keith Smith; Weili Lin; Gang Li; Dinggang Shen
Journal:  IEEE Trans Med Imaging       Date:  2020-11-30       Impact factor: 10.048

4.  First-year development of modules and hubs in infant brain functional networks.

Authors:  Xuyun Wen; Han Zhang; Gang Li; Mingxia Liu; Weiyan Yin; Weili Lin; Jun Zhang; Dinggang Shen
Journal:  Neuroimage       Date:  2018-10-10       Impact factor: 6.556

5.  Functional individual variability development of the neonatal brain.

Authors:  Wenjian Gao; Ziyi Huang; Wenfei Ou; Xiaoqian Tang; Wanying Lv; Jingxin Nie
Journal:  Brain Struct Funct       Date:  2022-06-06       Impact factor: 3.270

6.  Reference-Relation Guided Autoencoder with Deep CCA Restriction for Awake-to-Sleep Brain Functional Connectome Prediction.

Authors:  Dan Hu; Weiyan Yin; Zhengwang Wu; Liangjun Chen; Li Wang; Weili Lin; Gang Li
Journal:  Med Image Comput Comput Assist Interv       Date:  2021-09-21

Review 7.  Understanding Vulnerability and Adaptation in Early Brain Development using Network Neuroscience.

Authors:  Alice M Graham; Mollie Marr; Claudia Buss; Elinor L Sullivan; Damien A Fair
Journal:  Trends Neurosci       Date:  2021-03-01       Impact factor: 13.837

8.  Variability in Infants' Functional Brain Network Connectivity Is Associated With Differences in Affect and Behavior.

Authors:  Caroline M Kelsey; Katrina Farris; Tobias Grossmann
Journal:  Front Psychiatry       Date:  2021-06-09       Impact factor: 4.157

9.  Distinct effects of prematurity on MRI metrics of brain functional connectivity, activity, and structure: Univariate and multivariate analyses.

Authors:  Antonio M Chiarelli; Carlo Sestieri; Riccardo Navarra; Richard G Wise; Massimo Caulo
Journal:  Hum Brain Mapp       Date:  2021-05-06       Impact factor: 5.038

10.  Development of Dynamic Functional Architecture during Early Infancy.

Authors:  Xuyun Wen; Rifeng Wang; Weiyan Yin; Weili Lin; Han Zhang; Dinggang Shen
Journal:  Cereb Cortex       Date:  2020-10-01       Impact factor: 5.357

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