Parcellating cortical functional networks in individuals

TY - JOUR

T1 - Parcellating cortical functional networks in individuals

AU - Wang, Danhong

AU - Buckner, Randy L.

AU - Fox, Michael D.

AU - Holt, Daphne J.

AU - Holmes, Avram J.

AU - Stoecklein, Sophia

AU - Langs, Georg

AU - Pan, Ruiqi

AU - Qian, Tianyi

AU - Li, Kuncheng

AU - Baker, Justin T.

AU - Stufflebeam, Steven M.

AU - Wang, Kai

AU - Wang, Xiaomin

AU - Hong, Bo

AU - Liu, Hesheng

N1 - Publisher Copyright: © 2015 Nature America, Inc.

PY - 2015/11/25

Y1 - 2015/11/25

N2 - The capacity to identify the unique functional architecture of an individual's brain is a crucial step toward personalized medicine and understanding the neural basis of variation in human cognition and behavior. Here we developed a cortical parcellation approach to accurately map functional organization at the individual level using resting-state functional magnetic resonance imaging (fMRI). A population-based functional atlas and a map of inter-individual variability were employed to guide the iterative search for functional networks in individual subjects. Functional networks mapped by this approach were highly reproducible within subjects and effectively captured the variability across subjects, including individual differences in brain lateralization. The algorithm performed well across different subject populations and data types, including task fMRI data. The approach was then validated by invasive cortical stimulation mapping in surgical patients, suggesting potential for use in clinical applications.

AB - The capacity to identify the unique functional architecture of an individual's brain is a crucial step toward personalized medicine and understanding the neural basis of variation in human cognition and behavior. Here we developed a cortical parcellation approach to accurately map functional organization at the individual level using resting-state functional magnetic resonance imaging (fMRI). A population-based functional atlas and a map of inter-individual variability were employed to guide the iterative search for functional networks in individual subjects. Functional networks mapped by this approach were highly reproducible within subjects and effectively captured the variability across subjects, including individual differences in brain lateralization. The algorithm performed well across different subject populations and data types, including task fMRI data. The approach was then validated by invasive cortical stimulation mapping in surgical patients, suggesting potential for use in clinical applications.

UR - https://www.scopus.com/pages/publications/84949101858

UR - https://www.scopus.com/pages/publications/84949101858#tab=citedBy

U2 - 10.1038/nn.4164

DO - 10.1038/nn.4164

M3 - Article

C2 - 26551545

SN - 1097-6256

VL - 18

SP - 1853

EP - 1860

JO - Nature neuroscience

JF - Nature neuroscience

IS - 12

ER -