Large-scale brain networks of the human left temporal pole: A functional connectivity MRI study

Belen Pascual, Joseph C. Masdeu, Mark Hollenbeck, Nikos Makris, Ricardo Insausti, Song Lin Ding, Bradford C. Dickerson

Research output: Contribution to journalArticle

108 Scopus citations

Abstract

The most rostral portion of the human temporal cortex, the temporal pole (TP), has been described as "enigmatic" because its functional neuroanatomy remains unclear. Comparative anatomy studies are only partially helpful, because the human TP is larger and cytoarchitectonically more complex than in nonhuman primates. Considered by Brodmann as a single area (BA 38), the human TP has been recently parceled into an array of cytoarchitectonic subfields. In order to clarify the functional connectivity of subregions of the TP, we undertook a study of 172 healthy adults using resting-state functional connectivity MRI. Remarkably, a hierarchical cluster analysis performed to group the seeds into distinct subsystems according to their large-scale functional connectivity grouped 87.5% of the seeds according to the recently described cytoarchitectonic subregions of the TP. Based on large-scale functional connectivity, there appear to be 4 major subregions of the TP: 1) dorsal, with predominant connectivity to auditory/somatosensory and language networks; 2) ventromedial, predominantly connected to visual networks; 3) medial, connected to paralimbic structures; and 4) anterolateral, connected to the default-semantic network. The functional connectivity of the human TP, far more complex than its known anatomic connectivity in monkey, is concordant with its hypothesized role as a cortical convergence zone.

Original languageEnglish (US)
Pages (from-to)680-702
Number of pages23
JournalCerebral Cortex
Volume25
Issue number3
DOIs
StatePublished - Mar 1 2015

Keywords

  • Anterior temporal lobe
  • brain anatomy
  • cytoarchitecture
  • language
  • resting-state fMRI

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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