Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (8): 28-33.doi: 10.6040/j.issn.1671-7554.0.2020.1012

• Special Topic on Brain Science and Brain Like Intelligence • Previous Articles     Next Articles

The construction, asymmetry and genetic correlation of 4D digital brain atlas

Shuwei LIU1,2,*(),Yunxia LOU1,2,Yuchun TANG1,2   

  1. 1. Research Center for Sectional and Imaging Anatomy, Cheeloo College of Medicine, Shandong University, School of Basic Medical Sciences, Shandong University, Digital Human Institute, Shandong University, Jinan 250012, Shandong, China
    2. Institute of Brain and Brain-Inspired Science, Shandong University, Jinan 250012, Shandong, China
  • Received:2020-06-24 Online:2020-08-07 Published:2020-08-07
  • Contact: Shuwei LIU E-mail:liusw@sdu.edu.cn

Abstract:

Human Brain Mapping is an important tool for exploring the structure and function of human brains, and is the basic platform for analyzing and processing brain structure and function information. The establishment of standardized 4D brain maps of different ages, genders and brain types, and the use of computer technology for visualization and dynamic analysis of brain structure can provide a detailed morphological basis for the embryogenesis and development of human brain structure and function. In this review, we present recent studies regarding the construction, asymmetry and genetic correlation of 4D digital brain atlas. Finally, discussions on the future research directions of brain atlas are given.

Key words: Digital, Brain atlas, Brain template, Asymmetry, Genetic correlation

CLC Number: 

  • R338.1
1 Amunts K , Knoll AC , Lippert T , et al. The Human Brain Project-Synergy between neuroscience, computing, informatics, and brain-inspired technologies[J]. PLoS Biol, 2019, 17 (7): e3000344.
doi: 10.1371/journal.pbio.3000344
2 Bjerke IE , Ovsthus M , Papp EA , et al. Data integration through brain atlasing: Human Brain Project tools and strategies[J]. Eur Psychiat, 2018, 50: 70- 76.
doi: 10.1016/j.eurpsy
3 Ewert S , Plettig P , Li NF , et al. Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity[J]. Neuroimage, 2018, 170: 271- 282.
doi: 10.1016/j.neuroimage.2017.05.015
4 Oishi K , Chang LD , Huang H . Baby brain atlases[J]. Neuroimage, 2019, 185: 865- 880.
doi: 10.1016/j.neuroimage.2018.04.003
5 Kawasaki T , Shin M , Kimura Y , et al. Topographic anatomy of the subthalamic nucleus localized by high-resolution human brain atlas superimposing digital images of cross-sectioned surfaces and histological images of microscopic sections from frozen cadaveric brains[J]. J Clin Neurosci, 2018, 53: 193- 202.
doi: 10.1016/j.jocn
6 Sivaswamy J , Thottupattu AJ , Mehta R , et al. Construction of Indian human brain atlas[J]. Neurol India, 2019, 67 (1): 229- 234.
7 Zhang YY , Wei HJ , Cronin MJ , et al. Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping[J]. Neuroimage, 2018, 171: 176- 189.
doi: 10.1016/j.neuroimage.2018.01.008
8 Mazziotta JC , Toga AW , Evans A , et al. A probabilistic atlas of the human brain: theory and rationale for its development. The International Consortium for Brain Mapping (ICBM)[J]. Neuroimage, 1995, 2 (2): 89- 101.
doi: 10.1006/nimg.1995.1012
9 Fujihara K , Takei Y . FreeSurfer as a platform for associating brain structure with function[J]. Brain Nerve, 2018, 70 (7): 841- 848.
10 Guo CJ , Ferreira D , Fink K , et al. Repeatability and reproducibility of FreeSurfer, FSL-SIENAX and SPM brain volumetric measurements and the effect of lesion filling in multiple sclerosis[J]. Eur Radiol, 2019, 29 (3): 1355- 1364.
doi: 10.1007/s00330-018-5710-x
11 Yokota H , Vijayasarathi A , Cekic M , et al. Diagnostic performance of glymphatic system evaluation using diffusion tensor imaging in idiopathic normal pressure hydrocephalus and mimickers[J]. Curr Gerontol Geriatr Res, 2019, 2019: 5675014.
doi: 10.1155/2019/5675014
12 Glasser MF , Coalson TS , Robinson EC , et al. A multi-modal parcellation of human cerebral cortex[J]. Nature, 2016, 536 (7615): 171- 178.
doi: 10.1038/nature18933
13 Vogel JW , La Joie R , Grothe MJ , et al. A molecular gradient along the longitudinal axis of the human hippocampus informs large-scale behavioral systems[J]. Nat Commun, 2020, 11 (1): 960.
14 Iglesias JE , Insausti R , Lerma-Usabiaga G , et al. A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology[J]. Neuroimage, 2018, 183: 314- 326.
doi: 10.1016/j.neuroimage.2018.08.012
15 Kunst M , Laurell E , Mokayes N , et al. A Cellular-Resolution Atlas of the Larval Zebrafish Brain[J]. Neuron, 2019, 103 (1): 21- 38.
doi: 10.1016/j.neuron.2019.04.034
16 Liu CR , Ye FQ , Yen CCC , et al. A digital 3D atlas of the marmoset brain based on multi-modal MRI[J]. Neuroimage, 2018, 169: 106- 116.
doi: 10.1016/j.neuroimage.2017.12.004
17 Murakami TC , Mano T , Saikawa S , et al. A three-dimensional single-cell-resolution whole-brain atlas using CUBIC-X expansion microscopy and tissue clearing[J]. Nat Neurosci, 2018, 21 (4): 625- 637.
doi: 10.1038/s41593-018-0109-1
18 Oishi K , Mori S , Troncoso JC , et al. Mapping tracts in the human subthalamic area by 11.7T ex vivo diffusion tensor imaging[J]. Brain Struct Funct, 2020, 225 (4): 1293- 1312.
19 Tang YC , Hojatkashani C , Dinov ID , et al. The construction of a Chinese MRI brain atlas: A morphometric comparison study between Chinese and Caucasian cohorts[J]. Neuroimage, 2010, 51 (1): 33- 41.
doi: 10.1016/j.neuroimage.2010.01.111
20 Zhan J , Dinov ID , Li J , et al. Spatial-temporal atlas of human fetal brain development during the early second trimester[J]. Neuroimage, 2013, 82: 115- 126.
doi: 10.1016/j.neuroimage.2013.05.063
21 Yu Q , Ouyang A , Chalak L , et al. Structural development of human fetal and preterm brain cortical plate based on population-averaged templates[J]. Cereb Cortex, 2016, 26 (11): 4381- 4391.
doi: 10.1093/cercor/bhv201
22 Liang PP , Shi L , Chen N , et al. Construction of brain atlases based on a multi-center MRI dataset of 2020 Chinese adults[J]. Sci Rep, 2015, 5: 18216.
doi: 10.1038/srep18216
23 Wang X , Chen N , Zuo Z , et al. Probabilistic MRI brain anatomical atlases based on 1, 000 Chinese subjects[J]. PLoS One, 2013, 8 (1): e50939.
doi: 10.1371/journal.pone.0050939
24 Fan L , Li H , Zhuo J , et al. The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture[J]. Cereb Cortex, 2016, 26 (8): 3508- 3526.
doi: 10.1093/cercor/bhw157
25 Hagen S , Jacques C , Maillard L , et al. Spatially dissociated intracerebral maps for face- and house-selective activity in the human ventral occipito-temporal cortex[J]. Cereb Cortex, 2020, 30 (7): 4026- 4043.
doi: 10.1093/cercor/bhaa022
26 No authors listed . Focus on human brain mapping[J]. Nat Neurosci, 2017, 20 (3): 297.
27 Sun B , Tang YC , Fan LZ , et al. The pineal region: thin sectional anatomy with MR correlation in the coronal plane[J]. Surg Radiol Anat, 2008, 30 (7): 575- 582.
doi: 10.1007/s00276-008-0375-9
28 Sun B , Wang D , Tang YC , et al. The pineal volume: a three-dimensional volumetric study in healthy young adults using 3.0 T MR data[J]. Int J Dev Neurosci, 2009, 27 (7): 655- 660.
doi: 10.1016/j.ijdevneu.2009.08.002
29 Tang YC , Sun W , Toga AW , et al. A probabilistic atlas of human brainstem pathways based on connectome imaging data[J]. Neuroimage, 2018, 169: 227- 239.
doi: 10.1016/j.neuroimage.2017.12.042
30 Novitskaya Y , Dumpelmann M , Vlachos A , et al. In vivo -assessment of the human temporal network: Evidence for asymmetrical effective connectivity[J]. Neuroimage, 2020, 214: 116769.
doi: 10.1016/j.neuroimage
31 Tang YC , Zhao L , Lou YX , et al. Brain structure differences between Chinese and Caucasian cohorts: A comprehensive morphometry study[J]. Hum Brain Mapp, 2018, 39 (5): 2147- 2155.
doi: 10.1002/hbm.23994
32 Lou Y , Zhao L , Yu S , et al. Brain asymmetry differences between Chinese and Caucasian populations: a surface-based morphometric comparison study[J]. Brain Imaging Behav, 2019.
doi: 10.1007/s11682-019-00184-7
33 Sun B , Ge H , Tang Y , et al. Asymmetries of the central sulcus in young adults: Effects of gender, age and sulcal pattern[J]. Int J Dev Neurosci, 2015, 44: 65- 74.
doi: 10.1016/j.ijdevneu
34 Fan L , Tang Y , Sun B , et al. Sexual dimorphism and asymmetry in human cerebellum: an MRI-based morphometric study[J]. Brain Res, 2010, 1353: 60- 73.
doi: 10.1016/j.brainres
35 Yin X , Han Y , Ge H , et al. Inferior frontal white matter asymmetry correlates with executive control of attention[J]. Hum Brain Mapp, 2013, 34 (4): 796- 813.
doi: 10.1002/hbm.21477
36 Xiao M , Ge HT , Khundrakpam BS , et al. Attention performance measured by attention metwork test is correlated with global and regional efficiency of structural brain networks[J]. Front Behav Neurosci, 2016, 10: 194.
doi: 10.3389/fnbeh.2016.00194
37 Xu J , Rees G , Yin X , et al. Spontaneous neuronal activity predicts intersubject variations in executive control of attention[J]. Neuroscience, 2014, 263: 181- 192.
doi: 10.1016/j.neuroscience
38 Xu JH , Yin XT , Ge HT , et al. Attentional performance is correlated with the local regional efficiency of intrinsic brain networks[J]. Front Behav Neurosci, 2015, 9: 200.
doi: 10.3389/fnbeh
39 Xu J , Yin X , Ge H , et al. Heritability of the effective connectivity in the resting-state default mode metwork[J]. Cereb Cortex, 2017, 27 (12): 5626- 5634.
doi: 10.1093/cercor/bhw332
40 Yin XT , Zhao L , Xu JH , et al. Anatomical substrates of the alerting, orienting and executive control components of attention: Focus on the posterior parietal lobe[J]. PLoS One, 2012, 7 (11): e50590.
doi: 10.1371/journal.pone.0050590
41 Leng Y , Shi YG , Yu QW , et al. Phenotypic and genetic correlations between the lobar segments of the inferior fronto-occipital fasciculus and attention[J]. Sci Rep, 2016, 6: 33015.
doi: 10.1038/srep33015
42 Ge HT , Yin XT , Xu JH , et al. Fiber pathways of attention subnetworks revealed with tract-based spatial statistics (TBSS) and probabilistic tractography[J]. PLoS One, 2013, 8 (11): e78831.
doi: 10.1371/journal.pone.0078831
43 Grasby KL , Jahanshad N , Painter JN , et al. The genetic architecture of the human cerebral cortex[J]. Science, 2020, 367 (6484): 6690.
doi: 10.1126/science.aay6690
44 Reineberg AE , Hatoum AS , Hewitt JK , et al. Genetic and environmental influence on the human functional connectome[J]. Cereb Cortex, 2020, 30 (4): 2099- 2113.
doi: 10.1093/cercor/bhz225
No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] SUO Dongyang, SHEN Fei, GUO Hao, LIU Lichang, YANG Huimin, YANG Xiangdong. Expression and mechanism of Tim-3 in animal model of drug-induced acute kidney injury[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 1 -6 .
[2] ZHANG Baowen, LEI Xiangli, LI Jinna, LUO Xiangjun, ZOU Rong. miR-21-5p targeted TIMP3 to inhibit proliferation and extracellular matrix accumulation of mesangial cells in Type II diabetic nephropathy mice[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 7 -14 .
[3] LONG Tingting, XIE Ming, ZHOU Lu, ZHU Junde. Effect of Noggin protein on learning and memory abilities and the dentate gyrus structure after cerebral ischemia reperfusion injury in mice[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 15 -23 .
[4] FU Jieqi, ZHANG Man, ZHANG Xiaolu, LI Hui, CHEN Hong. Molecular mechanism of Toll-like receptor 4 in the aggravation of blood lipid accumulation by inhibiting the peroxisome proliferator-activate receptor γ[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 24 -31 .
[5] MA Qingyuan, PU Peidong, HAN Fei, WANG Chao, ZHU Zhoujun, WANG Weishan, SHI Chenhui. Effect of miR-27b-3p regulating SMAD1 on osteosarcoma cell proliferation, migration and invasion[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 32 -37 .
[6] LI Ning, LI Juan, XIE Yan, LI Peilong, WANG Yunshan, DU Lutao, WANG Chuanxin. Expression of LncRNA AL109955.1 in 80 cases of colorectal cancer and its effect on cell proliferation, migration and invasion[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 38 -46 .
[7] SHI Shuang, LI Juan, MI Qi, WANG Yunshan, DU Lutao, WANG Chuanxin. Construction and application of a miRNAs prognostic risk assessment model of gastric cancer[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 47 -52 .
[8] XIAO Juan, XIAO Qiang, CONG Wei, LI Ting, DING Shouluan, ZHANG Yuan, SHAO Chunchun, WU Mei, LIU Jianing, JIA Hongying. Comparison of diagnostic efficacy of two kinds of thyroid imagine reporting and data systems[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 53 -59 .
[9] DING Xiangyun, YU Qingmei, ZHANG Wenfang, ZHUANG Yuan, HAO Jing. Correlation of the expression of insulin-like growth factor II in granulosa cells and ovulation induction outcomes of 84 patients with polycystic ovary syndrome[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 60 -66 .
[10] XU Yuxiang, LIU Yudong, ZHANG Peng, DUAN Ruisheng. A retrospective analysis of risk factors of cerebral microbleeds in 101 patients with cerebral small vessel disease[J]. Journal of Shandong University (Health Sciences), 2020, 58(7): 67 -71 .