Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations
Формирование и оценка парцелляции корковых областей на основе корреляций в состоянии покоя
2014-10-14
SCID: 54.1/pt2hmc4c
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RSFC-boundary mappingarchitectonic mappingcortical area parcellationcortical surface mappingresting-state functional connectivity
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Abstract (AI)
The cortical surface is organized into a large number of cortical areas; however, these areas have not been comprehensively mapped in the human. Abrupt transitions in resting-state functional connectivity (RSFC) patterns can noninvasively identify locations of putative borders between cortical areas (RSFC-boundary mapping; Cohen et al. 2008). Here we describe a technique for using RSFC-boundary maps to define parcels that represent putative cortical areas. These parcels had highly homogenous RSFC patterns, indicating that they contained one unique RSFC signal; furthermore, the parcels were much more homogenous than a null model matched for parcel size when tested in two separate datasets. Several alternative parcellation schemes were tested this way, and no other parcellation was as homogenous as or had as large a difference compared with its null model. The boundary map-derived parcellation contained parcels that overlapped with architectonic mapping of areas 17, 2, 3, and 4. These parcels had a network structure similar to the known network structure of the brain, and their connectivity patterns were reliable across individual subjects. These observations suggest that RSFC-boundary map-derived parcels provide information about the location and extent of human cortical areas. A parcellation generated using this method is available at http://www.nil.wustl.edu/labs/petersen/Resources.html.
Key Findings
1
Compared with alternative parcellation schemes, the boundary-derived parcellation was the most homogeneous and showed the largest improvement over its null model.
2
RSFC-boundary maps were used to generate cortical parcels representing putative human cortical areas.
3
Several derived parcels overlapped architectonically mapped areas 17, 2, 3, and 4, supporting their anatomical validity.
4
The parcels exhibited brain-like network organization and connectivity patterns that were reliable across individual subjects; the resulting parcellation was made publicly available.
5
The resulting parcels showed highly homogeneous resting-state functional connectivity patterns, significantly exceeding size-matched null models in two datasets.
Research Object
human cortical areas represented by parcels derived from resting-state functional connectivity boundary maps
Research Subject
the homogeneity, anatomical correspondence, network organization, and cross-subject reliability of the parcels as indicators of putative cortical area locations and extents
Publication Details
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2014-10-14
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