.png){kind=icon}
.png){kind=icon}
Return
A sub plus cortical fMRI-based surface parcellation
.png){kind=icon}
OA
AI
DOI：10.1002/hbm.25675.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Both cortical and subcortical structures are organized into a large number of distinct areas reflecting functional and cytoarchitectonic differences. Mapping these areas is of fundamental importance to neuroscience. A central obstacle to this task is the inaccuracy associated with bringing results from individuals into a common space. The vast individual differences in morphology pose a serious problem for volumetric registration. Surface-based approaches fare substantially better, but have thus far been used only for cortical parcellation, leaving subcortical parcellation in volumetric space. We extend the surface-based approach to include also the subcortical deep gray-matter structures, thus achieving a uniform representation across both cortex and subcortex, suitable for use with surface-based metrics that span these structures, for example, white/gray contrast. Using data from the Enhanced Nathan Klein Institute-Rockland Sample, limited to individuals between 19 and 69 years of age, we generate a functional parcellation of both the cortical and subcortical surfaces. To assess this extended parcellation, we show that (a) our parcellation provides greater homogeneity of functional connectivity patterns than do arbitrary parcellations matching in the number and size of parcels; (b) our parcels align with known cortical and subcortical architecture; and (c) our extended functional parcellation provides an improved fit to the complexity of life-span (6-85 years) changes in white/gray contrast data compared to arbitrary parcellations matching in the number and size of parcels, supporting its use with surface-based measures. We provide our extended functional parcellation for the use of the neuroimaging community.
Keywords:
boundary mapping
cortical parcellation
functional connectivity
model fitting
subcortical parcellation
white
gray contrast
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.