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Cited by 1,293

The DOI matches its Crossref record; 126 of the 126 references it cites were found in a registry or an index.

A Baseline for the Multivariate Comparison of Resting-State Networks

Open access
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.·2011·Frontiers in Systems Neuroscience
DOI 10.3389/fnsys.2011.00002
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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.

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Metadata

Authors
Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., Havlicek, M., Rachakonda, S., Fries, J., Kalyanam, R., Michael, A. M., Caprihan, A., Turner, J. A., Eichele, T., Adelsheim, S., Bryan, A. D., Bustillo, J., Clark, V. P., Feldstein Ewing, S. W., Filbey, F., Ford, C. C., Hutchison, K., Jung, R. E., Kiehl, K. A., Kodituwakku, P., Komesu, Y. M., Mayer, A. R., Pearlson, G. D., Phillips, J. P., Sadek, J. R., Stevens, M., Teuscher, U., Thoma, R. J., & Calhoun, V. D.
Venue
Frontiers in Systems Neuroscience
Publisher
Frontiers Media SA
Published
2011
Volume
5
Pages
2-2
ISSN
1662-5137 (ISSN-L)
DOI
10.3389/fnsys.2011.00002
OpenAlex
W1973741448
Cited by
1,293
References
126
FWCI
28.04
Type
journal article
Language
en
Open access
gold

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