UCLA Brain Mapping Center

Publications

Resting-state fMRI can reliably map neural networks in children.

Thomason ME; Dennis EL; Joshi AA; Joshi SH; Dinov ID; Chang C; Henry ML; Johnson RF; Thompson PM; Toga AW; Glover GH; Van Horn JD; Gotlib IH;
NeuroImage. 2011-Mar-1; 55(165-75):1
 
Resting-state MRI (rs-fMRI) is a powerful procedure for studying whole-brain neural connectivity. In this study we provide the first empirical evidence of the longitudinal reliability of rs-fMRI in children. We compared rest-retest measurements across spatial, temporal and frequency domains for each of six cognitive and sensorimotor intrinsic connectivity networks (ICNs) both within and between scan sessions. Using Kendall'sW, concordance of spatial maps ranged from .60 to .86 across networks, for various derived measures. The Pearson correlation coefficient for temporal coherence between networks across all Time 1-Time 2 (T1/T2) z-converted measures was .66 (p<.001). There were no differences between T1/T2 measurements in low-frequency power of the ICNs. For the visual network, within-session T1 correlated with the T2 low-frequency power, across participants. These measures from resting-state data in children were consistent across multiple domains (spatial, temporal, and frequency). Resting-state connectivity is therefore a reliable method for assessing large-scale brain networks in children.
 
PMID: 21134471    doi: 10.1016/j.neuroimage.2010.11.080
 

BMAP Author