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Original Articles
Research on the connectivity method of human and macaque brain regions based on DTI
LI Binqiang  WANG Qianshan  YAO Rong  CHAI Jingwen  WANG Yue  LI Haifang 

Cite this article as: Li BQ, Wang QS, Yao R, et al. Research on the connectivity method of human and macaque brain regions based on DTI[J]. Chin J Magn Reson Imaging, 2022, 13(3): 43-48. DOI:10.12015/issn.1674-8034.2022.03.009.


[Abstract] Objective At present, the most important cross-species research method is to construct a homologous brain area control map based on the existing homologous sites. However, with the development of the individual, the cerebral cortex will expand irregularly, which affects the existing homologous sites on the individual. Based on this, a method of tracing white matter fiber bundles as a reference frame at the individual level was proposed to construct the connectivity fingerprints of human and macaque brain regions.Materials and Methods A total of 10 human subjects and 10 rhesus monkey subjects were selected from open brain imaging data set. White matter fiber tracts were extracted from preprocessed data at individual level, the connection strength between brain regions and white matter fiber tracts was calculated, and the connectivity finger pattern was constructed. The kronbach α coefficient was used to calculate the consistency between individuals within species. The cosine-similarity was used to analyze the connectivity patterns of homologous brain regions of two species, and the results were verified by permutation test.Results Within species, Broca's area (Broca44), Primary sensory area (S1), and Hippocampus (Hippoc)'s consistency coefficients were 0.636, 0.780, 0.977 in macaques, and in humans, the consistency coefficients were 0.781, 0.726, and 0.607. Among species, the cosine similarity calculation results of Broca44 area, S1 area, and Hippoc area were 0.979, 0.994, and 0.995.Conclusions Tracing white matter fiber tracts at the individual level and constructing connectivity fingerprints for cross-species research between humans and macaques is effective, and this result supports the construction of a cross-species comparison framework between humans and macaques.
[Keywords] cross-species research;diffusion tensor imaging;probabilistic tractography;connectivity relationship;similarity analysis

LI Binqiang   WANG Qianshan   YAO Rong   CHAI Jingwen   WANG Yue   LI Haifang*  

College of Information and Computer Science, Taiyuan University of Technology, Taiyuan 030000, China

Li HF, E-mail: lihaifang@tyut.edu.cn

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 61976150); Natural Science Foundation of Shanxi Province (No. 201801D121135).
Received  2021-11-23
Accepted  2022-03-01
DOI: 10.12015/issn.1674-8034.2022.03.009
Cite this article as: Li BQ, Wang QS, Yao R, et al. Research on the connectivity method of human and macaque brain regions based on DTI[J]. Chin J Magn Reson Imaging, 2022, 13(3): 43-48. DOI:10.12015/issn.1674-8034.2022.03.009.

[1]
Liu Z, Cai YJ, Wang Y, et al. Cloning of macaque monkeys by somatic cell nuclear transfer[J]. Cell, 2018, 172(4): 881-887.e7. DOI: 10.1016/j.cell.2018.01.020.
[2]
Passingham R. How good is the macaque monkey model of the human brain?[J]. Curr Opin Neurobiol, 2009, 19(1): 6-11. DOI: 10.1016/j.conb.2009.01.002.
[3]
Striedter GF, Belgard TG, Chen CC, et al. NSF workshop report: discovering general principles of nervous system organization by comparing brain maps across species[J]. J Comp Neurol, 2014, 522(7): 1445-1453. DOI: 10.1002/cne.23568.
[4]
Mars RB, Verhagen L, Gladwin TE, et al. Comparing brains by matching connectivity profiles[J]. Neurosci Biobehav Rev, 2016, 60: 90-97. DOI: 10.1016/j.neubiorev.2015.10.008.
[5]
van Essen DC. Cortical cartography and caret software[J]. NeuroImage, 2012, 62(2): 757-764. DOI: 10.1016/j.neuroimage.2011.10.077.
[6]
Rushworth MF, Noonan MP, Boorman ED, et al. Frontal cortex and reward-guided learning and decision-making[J]. Neuron, 2011, 70(6): 1054-1069. DOI: 10.1016/j.neuron.2011.05.014.
[7]
Fornito A, Zalesky A, Bullmore ET. Network scaling effects in graph analytic studies of human resting-state FMRI data[J]. Front Syst Neurosci, 2010, 4: 22. DOI: 10.3389/fnsys.2010.00022.
[8]
Mars RB, Sotiropoulos SN, Passingham RE, et al. Whole brain comparative anatomy using connectivity blueprints[J]. Elife, 2018, 7: e35237. DOI: 10.7554/eLife.35237.
[9]
Warrington S, Bryant KL, Khrapitchev AA, et al. XTRACT-Standardised protocols for automated tractography in the human and macaque brain[J]. Neuroimage, 2020, 217: 116923. DOI: 10.1016/j.neuroimage.2020.116923.
[10]
Bryant KL, Li LC, Eichert N, et al. A comprehensive atlas of white matter tracts in the chimpanzee[J]. PLoS Biol, 2020, 18(12): e3000971. DOI: 10.1371/journal.pbio.3000971.
[11]
Thiebaut de Schotten M, Dell'Acqua F, Valabregue R, et al. Monkey to human comparative anatomy of the frontal lobe association tracts[J]. Cortex, 2012, 48(1): 82-96. DOI: 10.1016/j.cortex.2011.10.001.
[12]
Hecht EE, Gutman DA, Preuss TM, et al. Process versus product in social learning: comparative diffusion tensor imaging of neural systems for action execution-observation matching in macaques, chimpanzees, and humans[J]. Cereb Cortex, 2013, 23(5): 1014-1024. DOI: 10.1093/cercor/bhs097.
[13]
van Essen DC, Smith SM, Barch DM, et al. The WU-minn human connectome project: an overview[J]. Neuroimage, 2013, 80: 62-79. DOI: 10.1016/j.neuroimage.2013.05.041.
[14]
Milham MP, Ai L, Koo B, et al. An open resource for non-human primate imaging[J]. Neuron, 2018, 100(1): 61-74.e2. DOI: 10.1016/j.neuron.2018.08.039.
[15]
Glasser MF, Sotiropoulos SN, Wilson JA, et al. The minimal preprocessing pipelines for the human connectome project[J]. NeuroImage, 2013, 80: 105-124. DOI: 10.1016/j.neuroimage.2013.04.127.
[16]
Xia XL, Fan LZ, Cheng C, et al. Multimodal connectivity-based parcellation reveals a shell-core dichotomy of the human nucleus accumbens[J]. Hum Brain Mapp, 2017, 38(8): 3878-3898. DOI: 10.1002/hbm.23636.
[17]
Hernandez-Fernandez M, Reguly I, Jbabdi S, et al. Using GPUs to accelerate computational diffusion MRI: from microstructure estimation to tractography and connectomes[J]. Neuroimage, 2019, 188: 598-615. DOI: 10.1016/j.neuroimage.2018.12.015.
[18]
Fan LZ, Li H, Zhuo JJ, 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.
[19]
Reveley C, Gruslys A, Ye FQ, et al. Three-dimensional digital template atlas of the macaque brain[J]. Cereb Cortex, 2017, 27(9): 4463-4477. DOI: 10.1093/cercor/bhw248.
[20]
Sporns O, Tononi G, Kötter R. The human connectome: a structural description of the human brain[J]. PLoS Comput Biol, 2005, 1(4): e42. DOI: 10.1371/journal.pcbi.0010042.
[21]
Petrides M, Pandya DN. Comparative cytoarchitectonic analysis of the human and the macaque ventrolateral prefrontal cortex and corticocortical connection patterns in the monkey[J]. Eur J Neurosci, 2002, 16(2): 291-310. DOI: 10.1046/j.1460-9568.2001.02090.x.
[22]
Mars RB, Jbabdi S, Rushworth MFS. A common space approach to comparative neuroscience[J]. Annu Rev Neurosci, 2021, 44: 69-86. DOI: 10.1146/annurev-neuro-100220-025942.
[23]
Ren KX, Wang QS, Xia XL, et al. Analysis of cross-species anatomical connection differences between human and macaque broca region[J]. J Taiyuan Univ Technol, 2021, 52(5): 728-739. DOI: 10.16355/j.cnki.issn1007-9432tyut.2021.05.006.
[24]
Xia XL, Gao F, Yuan Z. Species and individual differences and connectional asymmetry of Broca's area in humans and macaques[J]. Neuro Image, 2021, 244: 118583. DOI: 10.1016/j.neuroimage.2021.118583.
[25]
Xu T, Nenning KH, Schwartz E, et al. Cross-species functional alignment reveals evolutionary hierarchy within the connectome[J]. Neuroimage, 2020, 223: 117346. DOI: 10.1016/j.neuroimage.2020.117346.

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