RT Journal Article
SR Electronic
T1 Large-scale meta-analysis suggests low regional modularity in lateral frontal cortex
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 083352
DO 10.1101/083352
A1 Alejandro de la Vega
A1 Tal Yarkoni
A1 Tor D. Wager
A1 Marie T. Banich
YR 2016
UL http://biorxiv.org/content/early/2016/10/25/083352.abstract
AB Extensive fMRI study of human lateral frontal cortex (LFC) has yet to yield a consensus mapping between discrete anatomy and psychological states, partly due to the difficulty of inferring mental states in individual studies. Here, we used a data-driven approach to generate a comprehensive functional-anatomical mapping of LFC from 11,406 neuroimaging studies. We identified putatively separable LFC regions on the basis of whole-brain co-activation, revealing 14 clusters organized into three whole-brain networks. Next, we used multivariate classification to identify the psychological states that best predicted activity in each sub-region, resulting in preferential psychological profiles. We observed large functional differences between networks, suggesting brain networks support distinct modes of processing. Within each network, however, we observed low functional specificity, suggesting discrete psychological states are not modularly organized. Our results are consistent with the view that individual LFC regions work as part of highly parallel, distributed networks to give rise to flexible, adaptive behavior.