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. 2013 Dec;83:288-93.
doi: 10.1016/j.neuroimage.2013.05.020. Epub 2013 May 29.

Intrinsic Connectivity Network Mapping in Young Children During Natural Sleep

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Free PMC article

Intrinsic Connectivity Network Mapping in Young Children During Natural Sleep

Janessa H Manning et al. Neuroimage. .
Free PMC article

Abstract

Structural and functional neuroimaging have substantively informed the pathophysiology of numerous adult neurological and psychiatric disorders. While structural neuroimaging is readily acquired in sedated young children, pediatric application of functional neuroimaging has been limited by the behavioral demands of in-scanner task performance. Here, we investigated whether functional magnetic resonance imaging (fMRI) acquired during natural sleep and without experimental stimulation offers a viable strategy for studying young children. We targeted the lengthy epoch of non-rapid eye movement, stage 3 (NREM3) sleep typically observed at sleep onset in sleep-deprived children. Seven healthy, preschool-aged children (24-58 months) were studied, acquiring fMRI measurements of cerebral blood flow (CBF) and of intrinsic connectivity networks (ICNs), with concurrent sleep-stage monitoring. ICN data (T2* fMRI) were reliably obtained during NREM3 sleep; CBF data (arterial spin labeled fMRI) were not reliably obtained, as scanner noises disrupted sleep. Applying independent component analysis (ICA) to T2* data, distinct ICNs were observed which corresponded closely with those reported in the adult literature. Notably, a network associated with orthography in adults was not observed, suggesting that ICNs exhibit a developmental trajectory. We conclude that resting-state fMRI obtained in sleep is a promising paradigm for neurophysiological investigations of young children.

Keywords: ASL; BOLD; Biomarker; CBF; EEG; EOG; ICA; Intrinsic connectivity network; Magnetic resonance imaging; NREM; POD; Pediatric; Sleep; arterial spin labeling; blood oxygen level dependent; cerebral blood flow; electro-oculogram; electroencephalogram; fMRI; functional magnetic resonance imaging; independent component analysis; non-rapid eye movement; pediatric-onset neurological disorder.

Conflict of interest statement

CONFLICTS OF INTEREST.

The authors have no conflicts of interest to report.

Figures

Figure 1
Figure 1. Image-Data Acquisition Time line
Prep = subject preparation, including placement of sound-attenuating ear plugs, adhesive electrodes, and foam head restraints. Localizer = anatomical localization scan to position the imaging volume. T1 = T1-weighted anatomical scan. T2* = 15 min BOLD image-volume acquisition for ICN analysis. ASL = 2.5 min arterial spin labeled acquisition. The number of epochs of T2* (1-3) and ASL data (3-5) varied across subjects, depending on sleep duration. SS = sleep-stage determination, which was performed between all imaging epochs.
Figure 2
Figure 2. Intrinsic Connectivity Networks (ICNs)
The ten ICNs accounting for the greatest variance in seven, soundly sleeping (NREM3), preschool-aged children (24-58 months) are illustrated (p≤ 0.05). The ICNs observed here in sleeping children corresponded closely both to those reported in 35 awake, resting-state in health adults and to those observed by applying ICA analysis the BrainMap database (Fox and Lancaster, 2002), a large (~ 33,000 subjects) task-state data set (Smith, Fox et al., 2009). Table 2 lists the observed pediatric ICNs ranked by variance accounted for and the closest analog (by spatial pattern) from adult networks.

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