Functional connectivity based parcellation of early visual cortices

Abstract

Human brain can be divided into multiple brain regions based on anatomical and functional properties. Recent studies showed that resting-state connectivity can be utilized for parcellating brain regions and identifying their distinctive roles. In this study, we aimed to parcellate the primary and secondary visual cortices (V1 and V2) into several subregions based on functional connectivity and to examine the functional characteristics of each subregion. We used resting-state data from a research database and also acquired resting-state data with retinotopy results from a local site. The long-range connectivity profile and three different algorithms (i.e., K-means, Gaussian mixture model distribution, and Ward's clustering algorithms) were adopted for the parcellation. We compared the parcellation results within V1 and V2 with the eccentric map in retinotopy. We found that the boundaries between subregions within V1 and V2 were located in the parafovea, indicating that the anterior and posterior subregions within V1 and V2 corresponded to peripheral and central visual field representations, respectively. Next, we computed correlations between each subregion within V1 and V2 and intermediate and high-order regions in ventral and dorsal visual pathways. We found that the anterior subregions of V1 and V2 were strongly associated with regions in the dorsal stream (V3A and inferior parietal gyrus), whereas the posterior subregions of V1 and V2 were highly related to regions in the ventral stream (V4v and inferior temporal gyrus). Our findings suggest that the anterior and posterior subregions of V1 and V2, parcellated based on functional connectivity, may have distinct functional properties.

Keywords: dorsal and ventral streams; functional connectivity; parcellation; peripheral and foveal visual field representations; resting-state fMRI; visual cortex.

Figure 1

(a) Dice coefficients and (b) silhouette coefficients as a function of the number of clusters k (k = 2 … 10). Red, green, and blue lines indicate K‐means, GMM distribution, and Ward's clustering algorithm, respectively [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 2

The parcellation results using long‐range connectivity profile matrix. Probability maps of the group mean parcellation results in V1 and V2 using (a) K‐means, (b) GMM distribution, and (c) Ward's clustering algorithms. The first and fourth columns are the anterior subregions, the second and fifth columns are the posterior subregions, and the third and sixth columns are 3D versions of V1 and V2, respectively. The color indicates the relative frequency of parcellated voxel assignments, showing that a large number of subjects exhibited similar parcellation results [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

Comparison between the parcellated subregions within V1 and V2 and retinotopic maps in a representative subject. (a) Parcellation results of V1 (left) and V2 (right). (b) Euclidian distances between the boundaries of the subregions within V1 (left) and V2 (right) and each eccentricity. (c) The mean eccentricity of the boundary between the subregions within V1 and V2 is plotted (each black dot indicates individual subject's data, and error bars indicate ±1 standard errors of the mean [SEM]). (d) The boundaries of the subregions within V1 and V2 (white dotted lines) on the eccentricity map in each hemisphere. The white solid lines indicate the boundaries between V1/V2 and V2/V3 (Ant, anterior; Post, posterior) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 4

Mean correlation values between the ROIs and anterior or posterior subregions of V1 and V2, using (a) K‐means, (b) GMM distribution, and (c) Ward's clustering algorithms (error bars indicate 1 SEM, and the asterisk denotes p < .001). (d) ROIs in dorsal and ventral streams: bilateral V3A, V4v, inferior parietal gyrus (IPG), and inferior temporal gyrus (ITG). We defined V3A and V4v using JuBrain atlas and IPG and ITG using the automated anatomical labeling atlas [Color figure can be viewed at http://wileyonlinelibrary.com]