bioRxivNeuroscience
Intrinsic functional architecture of the macaque dorsal and ventral lateral frontal cortex
Alexandros GoulasiD, Peter Stiers, R. Matthew HutchisoniD, Stefan EverlingiD, Michael Petrides, Daniel S MarguliesiD
Abstract
Investigations of the cellular and connectional organization of the lateral frontal cortex (LFC) of the macaque monkey provide indispensable knowledge for generating hypotheses about the human LFC. However, despite numerous investigations, there are still debates on the organization of this brain region. In vivo neuroimaging techniques such as resting-state fMRI can be used to define the functional circuitry of brain areas producing results largely consistent with gold-standard invasive tract-tracing techniques and offering the opportunity for cross-species comparison within the same modality. Our results using resting-state fMRI from macaque monkeys to uncover the intrinsic functional architecture of the LFC corroborate previous findings and inform current debates. Specifically, we show that i) the region in the midline and anterior to the superior arcuate sulcus is divided in two areas separated by the posterior supraprincipal dimple; ii) the cytoarchitectonically defined area 6DC/F2 contains two connectional divisions; and, iii) a distinct area occupies the cortex around the spur of the arcuate, updating what was previously proposed to be the border between dorsal and ventral motor/premotor areas. Within the ventral LFC specifically, the derived parcellation clearly suggests the presence of distinct areas i) with a somatomotor/orofacial connectional signature (putative area 44), ii) with an occulomotor connectional signature (putative frontal eye fields), and iii) premotor areas possibly hosting laryngeal and arm representations. Our results illustrate in detail the intrinsic functional architecture of the macaque LFC, thus providing valuable evidence for debates on its organization.
- organism: non-human primate
- assay: imaging
- research focus: spatial domain detection
- approach: statistical model
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