TY - JOUR
T1 - Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data
AU - Pruett, John R.
AU - Kandala, Sridhar
AU - Hoertel, Sarah
AU - Snyder, Abraham Z.
AU - Elison, Jed T.
AU - Nishino, Tomoyuki
AU - Feczko, Eric
AU - Dosenbach, Nico U.F.
AU - Nardos, Binyam
AU - Power, Jonathan D.
AU - Adeyemo, Babatunde
AU - Botteron, Kelly N.
AU - McKinstry, Robert C.
AU - Evans, Alan C.
AU - Hazlett, Heather C.
AU - Dager, Stephen R.
AU - Paterson, Sarah
AU - Schultz, Robert T.
AU - Collins, D. Louis
AU - Fonov, Vladimir S.
AU - Styner, Martin
AU - Gerig, Guido
AU - Das, Samir
AU - Kostopoulos, Penelope
AU - Constantino, John N.
AU - Estes, Annette M.
AU - Petersen, Steven E.
AU - Schlaggar, Bradley L.
AU - Piven, Joseph
N1 - Publisher Copyright:
© 2015 The Authors. Published by Elsevier Ltd.
PY - 2015/4
Y1 - 2015/4
N2 - 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.
AB - 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.
KW - Development
KW - Functional brain networks
KW - Functional connectivity magnetic resonance imaging (fcMRI)
KW - Infant
KW - Multivariate pattern analysis (MVPA)
KW - Support vector machine (SVM)
UR - http://www.scopus.com/inward/record.url?scp=84923321389&partnerID=8YFLogxK
U2 - 10.1016/j.dcn.2015.01.003
DO - 10.1016/j.dcn.2015.01.003
M3 - Article
C2 - 25704288
AN - SCOPUS:84923321389
SN - 1878-9293
VL - 12
SP - 123
EP - 133
JO - Developmental Cognitive Neuroscience
JF - Developmental Cognitive Neuroscience
ER -