AUTHOR=Allen Elena A., Erhardt Erik B., Damaraju Eswar , Gruner William , Segall Judith M., Silva Rogers F., Havlicek Martin , Rachakonda Srinivas , Fries Jill , Kalyanam Ravi , Michael Andrew M., Caprihan Arvind , Turner Jessica A., Eichele Tom , Adelsheim Steven , Bryan Angela D., Bustillo Juan , Clark Vincent P., Feldstein Ewing Sarah W., Filbey Francesca , Ford Corey C., Hutchison Kent , Jung Rex E., Kiehl Kent A., Kodituwakku Piyadasa , Komesu Yuko M., Mayer Andrew R., Pearlson Godfrey D., Phillips John P., Sadek Joseph R., Stevens Michael , Teuscher Ursina , Thoma Robert J., Calhoun Vince D. TITLE=A Baseline for the Multivariate Comparison of Resting-State Networks JOURNAL=Frontiers in Systems Neuroscience VOLUME=5 YEAR=2011 URL=https://www.frontiersin.org/journals/systems-neuroscience/articles/10.3389/fnsys.2011.00002 DOI=10.3389/fnsys.2011.00002 ISSN=1662-5137 ABSTRACT=

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.