Connectivity_based Parcellation Of The Human Brodmann Area 32

The human brain which was regarded as the commander of the human central nervous system is one of the most complex system in nature. Efforts made to map its structure to study its functions could greatly enhance our understanding of the human brain. The present study of brain atlas provides the opportunity to investigate the individual differences and to explore how these individual differences affect the cognitive functions. Recent studies have shown that the function of the human brain is determined by its external connectivity patterns. Therefore, the parcellation of human brain based on different connectivity patterns could better portrayed the functional segregation and integration. In our study, we aimed to build the atlas of human Brodmann area 32(BA32) on the basis of different connectivity patterns.The human BA32 of which is the transition cortex,was mainly located between anterior cingulated sulcus and paracingulate sulcus. The previous studies to parcellate BA32 were primarily based on the post-mortem techniques, such as cytoarchitecture and receptor distribution patters. However, these studies did not consider the effects of size and location of paracingulate sulcus(PCS) on parcellation results for BA32. In addition, these studies cannot be performed in vivo and cannot provide the structural and functional connectivity information. In our study, we first divided the subjects into two groups: one group with PCS, and the other with no PCS. Then we parcellated the BA32 into six different subregions on the basis of different anatomical connectivity patterns using edge-weight spectral clustering method. Although BA32 is a very complex area and participates in different cognitive functions,our parcellation results for BA32 were consistent with the cytoarchitectonic findings. In order to validate the reliability of parcellation results for BA32, we mapped the whole anatomical connectivity patterns for each subregion and found different connectivity patterns of BA32 subregions. We also found the different connectivity patterns of the BA32 subregion between the two groups. Our finding provided important references for future studies on this area.