In imaging data based brain network analysis, a necessary precursor for constructing meaningful brain networks is to identify functionally homogeneous regions of interest (ROIs) for defining network nodes. For parcellating the brain based on resting state fMRI data, normalized cut is one widely used clustering algorithm which groups voxels according to the similarity of functional signals. Due ...

The human connectome is an intricate system of interconnected elements, providing the basis for integrative brain function. An essential step in the macroscopic mapping and examination of this network of structural and functional interactions is the subdivision of the brain into large-scale regions. Parcellation approaches used for the formation of macroscopic brain networks include application...

The parcellation of the cortex via its anatomical properties has been an important research endeavor for over a century. To date, however, a universally accepted parcellation scheme for the human brain still remains elusive. In the current review, we explore the use of in vivo diffusion imaging and white matter tractography as a non-invasive method for the structural and functional parcellation...

An alternative parcellation of the orbitofrontal cortex is described for the automated anatomical labeling atlas of Tzourio-Mazoyer et al. (2002) (Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage 15:273-289). The new parcellation of the orbitofrontal cortex follows the description provided by Chiavara...

We compare two strategies for modeling the connections of the brain's white matter: fiber clustering and the parcellation-based connectome. Both methods analyze diffusion magnetic resonance imaging fiber tractography to produce a quantitative description of the brain's connections. Fiber clustering is designed to reconstruct anatomically-defined white matter tracts, while the parcellation-based...

Deriving a meaningful functional brain parcellation is a very challenging issue in task-related fMRI analysis. The joint parcellation detection estimation model addresses this issue by inferring the parcels from fMRI data. However, it requires a priori fixing the number of parcels through an initial mask for parcellation. Hence, this difficult task generally depends on the subject. The proposed...

Recent work with functional connectivity data has led to significant progress in understanding the functional organization of the brain. While the majority of the literature has focused on group-level parcellation approaches, there is ample evidence that the brain varies in both structure and function across individuals. In this work, we introduce a parcellation technique that incorporates deli...

There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas th...

Volumetric measurements obtained from image parcellation have been instrumental in uncovering structure-function relationships. However, anatomical study of the cerebellum is a challenging task. Because of its complex structure, expert human raters have been necessary for reliable and accurate segmentation and parcellation. Such delineations are time-consuming and prohibitively expensive for la...