Prediction of individual brain maturity using fMRI.
Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.
Dosenbach
Nico U F
NU
Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA. ndosenbach@wustl.edu
Nardos
Binyam
B
Cohen
Alexander L
AL
Fair
Damien A
DA
Power
Jonathan D
JD
Church
Jessica A
JA
Nelson
Steven M
SM
Wig
Gagan S
GS
Vogel
Alecia C
AC
Lessov-Schlaggar
Christina N
CN
Barnes
Kelly Anne
KA
Dubis
Joseph W
JW
Feczko
Eric
E
Coalson
Rebecca S
RS
Pruett
John R
JR
Barch
Deanna M
DM
Petersen
Steven E
SE
Schlaggar
Bradley L
BL
D000293:Adolescent; D000328:Adult; D000375:Aging; D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000254:growth & development* / Q000502:physiology*; D001931:Brain Mapping; D002531:Cerebellum / Q000254:growth & development / Q000502:physiology; D002648:Child; D005260:Female; D005625:Frontal Lobe / Q000254:growth & development / Q000502:physiology; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D015999:Multivariate Analysis; D009434:Neural Pathways; D009778:Occipital Lobe / Q000254:growth & development / Q000502:physiology; D055815:Young Adult