Unravelling the intrinsic functional organization of the human lateral frontal cortex: a parcellation scheme based on resting-state fMRI

A. Goulas*, H.B.M. Uylings, P. Stiers

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Human and nonhuman primates exhibit flexible behavior. Functional, anatomical, and lesion studies indicate that the lateral fronta cortex (LFC) plays a pivotal role in such behavior. LFC consists of distinct subregions exhibiting distinct connectivity patterns that possibly relate to functional specializations. Inference about the border of each subregion in the human brain is performed with the aid of macroscopic landmarks and/or cytoarchitectonic parcellations extrapolated in a stereotaxic system. However, the high interindividual variability, the limited availability of cytoarchitectonic probabilistic maps, and the absence of robust functional localizers render the in vivo delineation and examination of the LFC subregions challenging. In this study, we use resting state fMRI for the in vivo parcellation of the human LFC on a subjectwise and data-driven manner. This approach succeeds in uncovering neuroanatomically realistic subregions, with potential anatomical substrates including BA46, 44, 45, 9 and related (sub)divisions. Ventral LFC subregions exhibit different functional connectivity (FC), which can account for different contributions in the language domain, while more dorsal adjacent subregions mark a transition to visuospatial/sensorimotor networks. Dorsal LFC subregions participate in known large-scale networks obeying an external/internal information processing dichotomy. Furthermore, we raced "families" of LFC subregions organized along the dorsal-ventral and anterior-posterior axis with distinct functional networks also encompassing specialized cingulate divisions. Similarities with the connectivity of macaque candidate homologs were observed, such as the premotor affiliation of presumed BA 46. The
current findings partially support dominant LFC models.
Original languageEnglish
Pages (from-to)10238-10252
JournalJournal of Neuroscience
Issue number30
Publication statusPublished - 1 Jan 2012

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