Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Jul;222(5):2173-2182.
doi: 10.1007/s00429-016-1333-7. Epub 2016 Nov 2.

Gradients of connectivity distance are anchored in primary cortex

Sabine Oligschläger  1   2 , Julia M Huntenburg  1   3 , Johannes Golchert  1 , Mark E Lauckner  1 , Tyler Bonnen  4 , Daniel S Margulies  5
Affiliations

Gradients of connectivity distance are anchored in primary cortex

Sabine Oligschläger et al. Brain Struct Funct. 2017 Jul.

Abstract

Connectivity between distant cortical areas is a valuable, yet costly feature of cortical organization and is predominantly found between regions of heteromodal association cortex. The recently proposed 'tethering hypothesis' describes the emergence of long-distance connections in association cortex as a function of their spatial separation from primary cortical regions. Here, we investigate this possibility by characterizing the distance between functionally connected areas along the cortical surface. We found a systematic relationship between an area's characteristic connectivity distance and its distance from primary cortical areas. Specifically, the further a region is located from primary sensorimotor regions, the more distant are its functional connections with other areas of the cortex. The measure of connectivity distance also captured major functional subdivisions of the cerebral cortex: unimodal, attention, and higher-order association regions. Our findings provide evidence for the anchoring role of primary cortical regions in establishing the spatial distribution of cortical properties that are related to functional specialization and differentiation.

Keywords: Connectivity; Cortical organization; Spatial organization; Topography.

PubMed Disclaimer

Conflict of interest statement

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Figures

Fig. 1
Fig. 1
Calculation of distance-to-connected-areas. a Geodesic distance. To capture spatial relationships of areas across the cortical surface, we measured the geodesic distance between nodes. In contrast to Euclidean distance (i.e., a straight line between two points; black), geodesic distance refers to the shortest path along the surface (purple). b Maps of distance-to-connected-areas describe each node’s average distance to functionally connected areas along the cortical surface. Computation for one example node: the ipsilateral functional connectivity for this node was thresholded to select nodes of highest connectivity only. The seed node’s geodesic distance to all selected nodes was averaged resulting in its characteristic distance-to-connected-areas
Fig. 2
Fig. 2
Group-level distance-to-connected-areas. a Group-level maps of distance-to-connected-areas (at 2% connectivity threshold) formed a consistent topographical pattern: distance-to-connected-areas was shortest in primary cortex and longest in association cortex. Specifically, the measure precisely delineated primary cortical regions: shortest distances lined the temporal transverse sulcus (primary auditory cortex, left box), the central sulcus (primary motor and somatosensory cortex, left box), and the calcarine sulcus (primary visual cortex, right box). With further distance from these regions, distance-to-connected-areas increased progressively, reaching peak values in higher-order association areas (lateral temporal, inferior parietal lobule, superior and middle frontal gyri). b Histogram of group-level distance-to-connected-areas
Fig. 3
Fig. 3
The spatial progression of distance-to-connected-areas across the cortical surface was investigated with relation to locations of primary cortex. a Distance from primary cortex. The map shows the geodesic distance from the closest node of a primary cortical region (green outline: depth of the calcarine sulcus, temporal transverse sulcus, and central sulcus). Prefrontal areas anterior to the intermediate frontal sulcus were excluded from the correlation as they deviated from the overall pattern of increasing connectivity distance with distance from primary cortex. b Distance-to-connected-areas showed a systematic relationship with distance from primary cortex as shown by the spatial correlation between the map of distance-to-connected-areas (shown in Fig. 2) and the map of distance from primary cortex (Spearman’s r = 0.7, p ≤ 0.01, slope = 0.6). These findings show that the spatial distribution of distance-to-connected-areas is anchored in locations of primary cortex
Fig. 4
Fig. 4
Broad domains of cortical functions are marked by distance-to-connected-areas. a Intrinsic networks (17-network template by Yeo et al. 2011). b Network-specific distributions of distance-to-connected-areas. c This matrix shows pairwise comparisons between the network distributions using the Jenson–Shannon divergence measure. k-means clustering of this matrix revealed three network groups that are broadly similar in functionality: sensorimotor (purple), attention (orange), and higher-order cognitive functions (yellow). d Class membership projected to the fsaverage5 surface. SMb somatomotor, Vc visual, SMa somatomotor, Vp visual, DAb dorsal attention, L limbic, Dc default, Dd default, DAa dorsal attention, Cc frontoparietal control, VA ventral attention, S salience, Da default, Ca frontoparietal control, Db default, Cb frontoparietal control
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Achard S, Bullmore E. Efficiency and cost of economical brain functional networks. PLoS Comput Biol. 2007;3:e17. doi: 10.1371/journal.pcbi.0030017. - DOI - PMC - PubMed
    1. Barrett LF, Simmons WK. Interoceptive predictions in the brain. Nat Rev Neurosci. 2015;16:419–429. doi: 10.1038/nrn3950. - DOI - PMC - PubMed
    1. Bassett DS, Bullmore E. Small-world brain networks. Neuroscientist. 2006;12:512–523. doi: 10.1177/1073858406293182. - DOI - PubMed
    1. Bazin P-L, Weiss M, Dinse J, et al. A computational framework for ultra-high resolution cortical segmentation at 7Tesla. Neuroimage. 2014;93(Pt 2):201–209. doi: 10.1016/j.neuroimage.2013.03.077. - DOI - PubMed
    1. Behzadi Y, Restom K, Liau J, Liu TT. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage. 2007;37:90–101. doi: 10.1016/j.neuroimage.2007.04.042. - DOI - PMC - PubMed

LinkOut - more resources