Bin He^1,2,3？, Zhengyi Yang^2？, Lingzhong Fan^2,4, Bin Gao², Hai Li², Chuyang Ye², Bo You^1* and Tianzi Jiang^{2,3,4,5,6,7,8*} 

¹School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, China

²Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China

³National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

⁴University of Chinese Academy of Sciences, Beijing, China

⁵Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China

⁶CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China

⁷Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia

⁸Chinese Institute for Brain Research, Beijing, China

Abstract  

Non-human primate models are widely used in studying the brain mechanism underlying brain development, cognitive functions, and psychiatric disorders. Neuroimaging techniques, such as magnetic resonance imaging, play an important role in the examinations of brain structure and functions. As an indispensable tool for brain imaging data analysis, brain atlases have been extensively investigated, and a variety of versions constructed. These atlases diverge in the criteria based on which they are plotted. The criteria range from cytoarchitectonic features, neurotransmitter receptor distributions, myelination fingerprints, and transcriptomic patterns to structural and functional connectomic profiles. Among them, brainnetome atlas is tightly related to brain connectome information and built by parcellating the brain on the basis of the anatomical connectivity profiles derived from structural neuroimaging data. The pipeline for building the brainnetome atlas has been published as a toolbox named ATPP (A Pipeline for Automatic Tractography-Based Brain Parcellation). In this paper, we present a variation of ATPP, which is dedicated to monkey brain parcellation, to address the significant differences in the process between the two species. The new toolbox, MonkeyCBP, has major alterations in three aspects: brain extraction, image registration, and validity indices. By parcellating two different brain regions (posterior cingulate cortex) and (frontal pole) of the rhesus monkey, we demonstrate the efficacy of these alterations. The toolbox has been made public (https://github.com/bheAI/MonkeyCBP_CLI, https://github.com/bheAI/MonkeyCBP_GUI). It is expected that the toolbox can benefit the non-human primate neuroimaging community with high-throughput computation and low labor involvement. 

Figure 1. Framework of the MonkeyCBP toolbox. The processing steps of the pipeline mainly including brain extraction, registration, probabilistic tractography, and clustering. First, the technique of brain extraction for monkey MRI data was performed; then based on T1w and diffusion tensor images of the same subjects, two defined regions of interest (ROIs), including the right posterior cingulate cortex and the bilateral frontal pole, are parcellated simultaneously. After pipeline processing, the parcellation results at both individual level and group level with a maximum probability map and probabilistic maps of each subarea of the right posterior cingulate cortex and the bilateral frontal pole are generated.