Altered resting-state whole-brain functional networks of neonates with intrauterine growth restriction. (April 2016)

• Record Type: Journal Article
• Authors: Batalle, Dafnis; Muñoz-Moreno, Emma; Tornador, Cristian; Bargallo, Nuria; Deco, Gustavo; Eixarch, Elisenda; Gratacos, Eduard
• Is Part Of: Cortex. Volume 77(2016)
• Page Start: 119
• Page End: 131
• Publication Date: 2016-04
• Subjects: Brain mapping -- fMRI -- Newborn -- Fetal growth retardation -- Connectomics; ADHD attention deficit hyperactive disorder -- ASD autism spectrum disorders -- BOLD blood oxygen level-dependent -- CSF cerebrospinal fluid -- DFC dynamic functional connectivity -- FA fractional anisotropy -- FDR false discovery rate -- GA gestational age -- GM grey matter -- ICA independent component analysis -- IUGR intrauterine growth restriction -- MRI magnetic resonance imaging -- NBAS Neonatal Behavioral Assessment Scale -- PMA post menstrual age -- ROI region of interest -- rs-fMRI resting-state functional MRI -- RSN resting state networks -- WM white matter; Neuropsychology -- Periodicals; Nervous system -- Periodicals; Neurology -- Periodicals; Psychophysiology -- Periodicals; Behavior -- Periodicals; Neurology -- Periodicals; 612.825
• DOI: 10.1016/j.cortex.2016.01.012
• Languages: English
• ISSNs: 0010-9452

Abstract

Abstract: The feasibility to use functional MRI (fMRI) during natural sleep to assess low-frequency basal brain activity fluctuations in human neonates has been demonstrated, although its potential to characterise pathologies of prenatal origin has not yet been exploited. In the present study, we used intrauterine growth restriction (IUGR) as a model of altered neurodevelopment due to prenatal condition to show the suitability of brain networks to characterise functional brain organisation at neonatal age. Particularly, we analysed resting-state fMRI signal of 20 neonates with IUGR and 13 controls, obtaining whole-brain functional networks based on correlations of blood oxygen level-dependent (BOLD) signal in 90 grey matter regions of an anatomical atlas (AAL). Characterisation of the networks obtained with graph theoretical features showed increased network infrastructure and raw efficiencies but reduced efficiency after normalisation, demonstrating hyper-connected but sub-optimally organised IUGR functional brain networks. Significant association of network features with neurobehavioral scores was also found. Further assessment of spatiotemporal dynamics displayed alterations into features associated to frontal, cingulate and lingual cortices. These findings show the capacity of functional brain networks to characterise brain reorganisation from an early age, and their potential to develop biomarkers of altered neurodevelopment.