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Journal of NeurophysiologyNeurosciencePeer-reviewed journal article

Parallel Distributed Networks Resolved at High Resolution Reveal Close Juxtaposition of Distinct Regions

Rodrigo M. BragaiD, Koene R. A. Van DijkiD, Jon̈athan R. PolimeniiD, Mark C. EldaiefiD, Randy L. BuckneriD

PDFDOIPreprint

Abstract

Examination of large-scale distributed networks within the individual reveals details of cortical network organization that are absent in group-averaged studies. One recent discovery is that a distributed transmodal network, often referred to as the default network, is comprised of two separate but closely interdigitated networks, only one of which is coupled to posterior parahippocampal cortex. Not all studies of individuals have identified the same networks and questions remain about the degree to which the two networks are separate, particularly within regions hypothesized to be interconnected hubs. Here we replicate the observation of network separation across analytical (seed-based connectivity and parcellation) and data projection (volume and surface) methods in 2 individuals each scanned 31 times. Additionally, 3 individuals were examined with high-resolution fMRI to gain further insight into the anatomical details. The two networks were identified with separate regions localized to adjacent portions of the cortical ribbon, sometimes inside the same sulcus. Midline regions previously implicated as hubs revealed near complete spatial separation of the two networks, displaying a complex spatial topography in the posterior cingulate and precuneus. The network coupled to parahippocampal cortex also revealed a separate region directly within the hippocampus at or near the subiculum. These collective results support that the default network is composed of at least two spatially juxtaposed networks. Fine spatial details and juxta-positions of the two networks can be identified within individuals at high resolution, providing insight into the network organization of association cortex and placing further constraints on interpretation of group-averaged neuroimaging data.

Citations
162
FWCI
10.60
Field percentile
top 1%

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