Dataset Information

Using Functional Connectivity Magnetic Resonance Imaging to Measure Brain Connectivity in Preterm Infants.

ABSTRACT: BACKGROUND:The use of functional connectivity magnetic resonance imaging (fcMRI) in research involving preterm infants is relatively new, and its feasibility in this population is not fully established. However, fcMRI images reveal functional neural connections that may be useful in establishing the mechanisms of neuroprotective interventions in preterm infants. OBJECTIVE:The aim of this study was to determine the feasibility of using fcMRI to measure differences in functional neural connections in nursing intervention studies. METHODS:A pilot study was conducted as part of a longitudinal, randomized controlled trial (RCT) testing the effect of a feeding intervention on neurodevelopmental and clinical outcomes of preterm infants randomly assigned to one of two groups: a patterned feeding experience (PFE) group and a usual feeding care (UFC) group. The fcMRIs were done at term-equivalent age. Visual, motor, and default mode networks were analyzed. RESULTS:Seven infants were studied (four were in the PFE group, and three were in the UFC group). Participants were selected sequentially from the parent RCT. Clear images were obtained from all participants. Differences were noted among PFE and UFC infants: Infants receiving PFE were hyperconnective in the default mode (caudate, anterior cingulate cortex, and precuneus) and motor networks (middle temporal and middle occipital areas) and hypoconnective in others areas of the default mode (hippocampal and lingual regions) and motor networks (precentral and superior frontal cortices) relative to UFC infants. No differences were noted in visual networks. DISCUSSION:The feasibility of using fcMRI at term-equivalent age in preterm infants who participated in an RCT on the effect of a nursing intervention was shown. Differences in connectivity among infants by group were detected. Further research is needed to show the benefit of fcMRI in studies of preterm infants given the costs of the procedure as well as the uncertain relationship of this early outcome measure to long-term neurodevelopment.

SUBMITTER: Pickler R

PROVIDER: S-EPMC5776701 | biostudies-literature | 2017 Nov/Dec

REPOSITORIES: biostudies-literature

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Using Functional Connectivity Magnetic Resonance Imaging to Measure Brain Connectivity in Preterm Infants.

Pickler Rita R Sealschott Stephanie S Moore Margo M Merhar Stephanie S Tkach Jean J Salzwedel Andrew P AP Lin Weili W Gao Wai W

Nursing research 20171101 6

<h4>Background</h4>The use of functional connectivity magnetic resonance imaging (fcMRI) in research involving preterm infants is relatively new, and its feasibility in this population is not fully established. However, fcMRI images reveal functional neural connections that may be useful in establishing the mechanisms of neuroprotective interventions in preterm infants.<h4>Objective</h4>The aim of this study was to determine the feasibility of using fcMRI to measure differences in functional neu ...[more]

PMID: 29095379

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Project description:Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep conditions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory" of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circuit and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, nodes and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB-131115-H0075 on November 15, 2013.

Project description:Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 × 10(-7)). In subjects <20 years of age, the classifier performed at 89% accuracy (P = 5.4 × 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects <20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance >10 cm). Brain regions showing greatest differences included regions of the default mode network, superior parietal lobule, fusiform gyrus and anterior insula. Overall, classification accuracy was better for younger subjects, with differences between autism and control subjects diminishing after 19 years of age. Classification scores of unaffected siblings of individuals with autism were more similar to those of the control subjects than to those of the subjects with autism. These findings indicate feasibility of a functional connectivity magnetic resonance imaging diagnostic assay for autism.

Dataset Information

Using Functional Connectivity Magnetic Resonance Imaging to Measure Brain Connectivity in Preterm Infants.

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Using Functional Connectivity Magnetic Resonance Imaging to Measure Brain Connectivity in Preterm Infants.

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