Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

John R. Pruett, Sridhar Kandala, Sarah Hoertel, Abraham Z. Snyder, Jed T. Elison, Tomoyuki Nishino, Eric Feczko, Nico U.F. Dosenbach, Binyam Nardos, Jonathan D. Power, Babatunde Adeyemo, Kelly N. Botteron, Robert C. McKinstry, Alan C. Evans, Heather C. Hazlett, Stephen R. Dager, Sarah Paterson, Robert T. Schultz, D. Louis Collins, Vladimir S. FonovMartin Styner, Guido Gerig, Samir Das, Penelope Kostopoulos, John N. Constantino, Annette M. Estes, Steven E. Petersen, Bradley L. Schlaggar, Joseph Piven

    Research output: Contribution to journalArticle

    Abstract

    Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI) data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs) classified 6 versus 12 month-old infants (128 datasets) above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.

    Original languageEnglish (US)
    Pages (from-to)123-133
    Number of pages11
    JournalDevelopmental Cognitive Neuroscience
    Volume12
    DOIs
    StatePublished - Apr 2015

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    Keywords

    • Development
    • Functional brain networks
    • Functional connectivity magnetic resonance imaging (fcMRI)
    • Infant
    • Multivariate pattern analysis (MVPA)
    • Support vector machine (SVM)

    ASJC Scopus subject areas

    • Cognitive Neuroscience

    Cite this

    Pruett, J. R., Kandala, S., Hoertel, S., Snyder, A. Z., Elison, J. T., Nishino, T., Feczko, E., Dosenbach, N. U. F., Nardos, B., Power, J. D., Adeyemo, B., Botteron, K. N., McKinstry, R. C., Evans, A. C., Hazlett, H. C., Dager, S. R., Paterson, S., Schultz, R. T., Collins, D. L., ... Piven, J. (2015). Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data. Developmental Cognitive Neuroscience, 12, 123-133. https://doi.org/10.1016/j.dcn.2015.01.003