| Title |
Parcellation of Macaque Cortex with Anatomical Connectivity Profiles
|
|---|---|
| Published in |
Brain Topography, July 2017
|
| DOI | 10.1007/s10548-017-0576-9 |
| Pubmed ID | |
| Authors |
Jiaojian Wang, Zhentao Zuo, Sangma Xie, Yifan Miao, Yuanye Ma, Xudong Zhao, Tianzi Jiang |
| Abstract |
The macaque model has been widely used to investigate the brain mechanisms of specific cognitive functions and psychiatric disorders. However, a detailed functional architecture map of the macaque cortex in vivo is still lacking. Here, we aimed to construct a new macaque cortex atlas based on its anatomical connectivity profiles using in vivo diffusion MRI. First, we defined the macaque cortical seed areas using the NeuroMaps atlas. Then, we applied the anatomical connectivity patterns-based parcellation approach to parcellate the macaque cortex into 80 subareas in each hemisphere, which were approximately symmetric between the two hemispheres. In each hemisphere, we identified 14 subareas in the frontal cortex, 9 subareas in the somatosensory cortex, 13 subareas in the parietal cortex, 16 subareas in the temporal cortex, 16 subareas in the occipital cortex, and 12 subareas in the limbic system. Finally, the graph-based network analyses of the anatomical network based on newly constructed macaque cortex atlas identified seven hub areas including bilateral ventral premotor cortex, bilateral superior parietal lobule, right medial precentral gyrus, and right precuneus. This newly constructed macaque cortex atlas may facilitate studies of the structure and functions of the macaque brain in the future. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 30% |
| Researcher | 6 | 26% |
| Student > Master | 3 | 13% |
| Professor | 1 | 4% |
| Student > Doctoral Student | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 4 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 9 | 39% |
| Computer Science | 2 | 9% |
| Psychology | 2 | 9% |
| Medicine and Dentistry | 1 | 4% |
| Agricultural and Biological Sciences | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 8 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 July 2017.
All research outputs
#14,072,753
of 22,988,380 outputs
Outputs from Brain Topography
#259
of 485 outputs
Outputs of similar age
#167,897
of 312,390 outputs
Outputs of similar age from Brain Topography
#2
of 6 outputs
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