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701 results on '"Zuo, Xi-Nian"'

3. Initiating PeriCBD to probe perinatal influences on neurodevelopment during 3–10 years in China

Author

Wang, Yin-Shan, Su, Xue-Ting, Ke, Li, He, Qing-Hua, Chang, Da, Nie, JingJing, Luo, XinLi, Chen, Fumei, Xu, Jihong, Zhang, Cai, Zhang, Shudong, Zhang, Shuyue, An, Huiping, Guo, Rui, Yue, Suping, Duan, Wen, Jia, Shichao, Yang, Sijia, Yu, Yankun, Zhao, Yang, Zhou, Yang, Chen, Li-Zhen, Fan, Xue-Ru, Gao, Peng, Lv, Chenyu, Wu, Ziyun, Zhao, Yunyan, Quan, Xi, Zhao, Feng, Mu, Yanchao, Yan, Yu, Xu, Wenchao, Liu, Jie, Xing, Lixia, Chen, Xiaoqin, Wu, Xiang, Zhao, Lanfeng, Huang, Zhijuan, Ren, Yanzhou, Hao, Hongyan, Li, Hui, Wang, Jing, Dong, Qing, Chen, Liyan, Huang, Ruiwang, Liu, Siman, Wang, Yun, Dong, Qi, and Zuo, Xi-Nian

Published
2024
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5. Cross-ancestry genome-wide association studies of brain imaging phenotypes

Author

Fu, Jilian, Zhang, Quan, Wang, Jianhua, Wang, Meiyun, Zhang, Bing, Zhu, Wenzhen, Qiu, Shijun, Geng, Zuojun, Cui, Guangbin, Yu, Yongqiang, Liao, Weihua, Zhang, Hui, Gao, Bo, Xu, Xiaojun, Han, Tong, Yao, Zhenwei, Qin, Wen, Liu, Feng, Liang, Meng, Wang, Sijia, Xu, Qiang, Xu, Jiayuan, Zhang, Peng, Li, Wei, Shi, Dapeng, Wang, Caihong, Lui, Su, Yan, Zhihan, Chen, Feng, Zhang, Jing, Li, Jiance, Shen, Wen, Miao, Yanwei, Wang, Dawei, Xian, Junfang, Gao, Jia-Hong, Zhang, Xiaochu, Xu, Kai, Zuo, Xi-Nian, Zhang, Longjiang, Ye, Zhaoxiang, Cheng, Jingliang, Li, Mulin Jun, and Yu, Chunshui

Published
2024
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6. A Paradigm Shift in Neuroscience Driven by Big Data: State of art, Challenges, and Proof of Concept

Author

Zhou, Zi-Xuan and Zuo, Xi-Nian

Subjects
Quantitative Biology - Neurons and Cognition, Quantitative Biology - Quantitative Methods, Statistics - Methodology
Abstract

A recent editorial in Nature noted that cognitive neuroscience is at a crossroads where it is a thorny issue to reliably reveal brain-behavior associations. This commentary sketches a big data science way out for cognitive neuroscience, namely population neuroscience. In terms of design, analysis, and interpretations, population neuroscience research takes the design control to an unprecedented level, greatly expands the dimensions of the data analysis space, and paves a paradigm shift for exploring mechanisms on brain-behavior associations., Comment: 6 pages, 1 figure

Published
2022

8. Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits

Author

Xue, Kaizhong, Gao, Bo, Chen, Feng, Wang, Meiyun, Cheng, Jingliang, Zhang, Bing, Zhu, Wenzhen, Qiu, Shijun, Geng, Zuojun, Zhang, Xiaochu, Cui, Guangbin, Yu, Yongqiang, Zhang, Quan, Liao, Weihua, Zhang, Hui, Xu, Xiaojun, Han, Tong, Qin, Wen, Liu, Feng, Liang, Meng, Guo, Lining, Xu, Qiang, Xu, Jiayuan, Fu, Jilian, Zhang, Peng, Li, Wei, Shi, Dapeng, Wang, Caihong, Lui, Su, Yan, Zhihan, Zhang, Jing, Li, Jiance, Wang, Dawei, Xian, Junfang, Xu, Kai, Zuo, Xi-Nian, Zhang, Longjiang, Ye, Zhaoxiang, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L. W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Lemaitre, Herve, Poustka, Luise, Hohmann, Sarah, Holz, Nathalie, Fröhner, Juliane H., Smolka, Michael N., Vaidya, Nilakshi, Walter, Henrik, Whelan, Robert, Shen, Wen, Miao, Yanwei, and Yu, Chunshui

Published
2023
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9. Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder

Author

Adamson, Chris, Adler, Sophie, Alexander-Bloch, Aaron F., Anagnostou, Evdokia, Anderson, Kevin M., Areces-Gonzalez, Ariosky, Astle, Duncan E., Auyeung, Bonnie, Ayub, Muhammad, Bae, Jong Bin, Ball, Gareth, Baron-Cohen, Simon, Beare, Richard, Bedford, Saashi A., Benegal, Vivek, Bethlehem, Richard A.I., Beyer, Frauke, Blangero, John, Cábez, Manuel Blesa, Boardman, James P., Borzage, Matthew, Bosch-Bayard, Jorge F., Bourke, Niall, Bullmore, Edward T., Calhoun, Vince D., Chakravarty, Mallar M., Chen, Christina, Chertavian, Casey, Chetelat, Gaël, Chong, Yap S., Corvin, Aiden, Costantino, Manuela, Courchesne, Eric, Crivello, Fabrice, Cropley, Vanessa L., Crosbie, Jennifer, Crossley, Nicolas, Delarue, Marion, Delorme, Richard, Desrivieres, Sylvane, Devenyi, Gabriel, Di Biase, Maria A., Dolan, Ray, Donald, Kirsten A., Donohoe, Gary, Dorfschmidt, Lena, Dunlop, Katharine, Edwards, Anthony D., Elison, Jed T., Ellis, Cameron T., Elman, Jeremy A., Eyler, Lisa, Fair, Damien A., Fletcher, Paul C., Fonagy, Peter, Franz, Carol E., Galan-Garcia, Lidice, Gholipour, Ali, Giedd, Jay, Gilmore, John H., Glahn, David C., Goodyer, Ian M., Grant, P.E., Groenewold, Nynke A., Gudapati, Shreya, Gunning, Faith M., Gur, Raquel E., Gur, Ruben C., Hammill, Christopher F., Hansson, Oskar, Hedden, Trey, Heinz, Andreas, Henson, Richard N., Heuer, Katja, Hoare, Jacqueline, Holla, Bharath, Holmes, Avram J., Huang, Hao, Ipser, Jonathan, Jack, Clifford R., Jr., Jackowski, Andrea P., Jia, Tianye, Jones, David T., Jones, Peter B., Kahn, Rene S., Karlsson, Hasse, Karlsson, Linnea, Kawashima, Ryuta, Kelley, Elizabeth A., Kern, Silke, Kim, Ki-Woong, Kitzbichler, Manfred G., Kremen, William S., Lalonde, François, Landeau, Brigitte, Lerch, Jason, Lewis, John D., Li, Jiao, Liao, Wei, Liston, Conor, Lombardo, Michael V., Lv, Jinglei, Mallard, Travis T., Marcelis, Machteld, Mathias, Samuel R., Mazoyer, Bernard, McGuire, Philip, Meaney, Michael J., Mechelli, Andrea, Misic, Bratislav, Morgan, Sarah E., Mothersill, David, Ortinau, Cynthia, Ossenkoppele, Rik, Ouyang, Minhui, Palaniyappan, Lena, Paly, Leo, Pan, Pedro M., Pantelis, Christos, Park, Min Tae M., Paus, Tomas, Pausova, Zdenka, Paz-Linares, Deirel, Binette, Alexa Pichet, Pierce, Karen, Qian, Xing, Qiu, Anqi, Raznahan, Armin, Rittman, Timothy, Rodrigue, Amanda, Rollins, Caitlin K., Romero-Garcia, Rafael, Ronan, Lisa, Rosenberg, Monica D., Rowitch, David H., Salum, Giovanni A., Satterthwaite, Theodore D., Schaare, H. Lina, Schabdach, Jenna, Schachar, Russell J., Schöll, Michael, Schultz, Aaron P., Seidlitz, Jakob, Sharp, David, Shinohara, Russell T., Skoog, Ingmar, Smyser, Christopher D., Sperling, Reisa A., Stein, Dan J., Stolicyn, Aleks, Suckling, John, Sullivan, Gemma, Thyreau, Benjamin, Toro, Roberto, Traut, Nicolas, Tsvetanov, Kamen A., Turk-Browne, Nicholas B., Tuulari, Jetro J., Tzourio, Christophe, Vachon-Presseau, Étienne, Valdes-Sosa, Mitchell J., Valdes-Sosa, Pedro A., Valk, Sofie L., van Amelsvoort, Therese, Vandekar, Simon N., Vasung, Lana, Vértes, Petra E., Victoria, Lindsay W., Villeneuve, Sylvia, Villringer, Arno, Vogel, Jacob W., Wagstyl, Konrad, Wang, Yin-Shan S., Warfield, Simon K., Warrier, Varun, Westman, Eric, Westwater, Margaret L., Whalley, Heather C., White, Simon R., Witte, A. Veronica, Yang, Ning, Yeo, B.T. Thomas, Yun, Hyuk Jin, Zalesky, Andrew, Zar, Heather J., Zettergren, Anna, Zhou, Juan H., Ziauddeen, Hisham, Zimmerman, Dabriel, Zugman, Andre, Zuo, Xi-Nian N., Ho, Natalie C.W., Nogovitsyn, Nikita, Metzak, Paul, Ballester, Pedro L., Hassel, Stefanie, Rotzinger, Susan, Poppenk, Jordan, Lam, Raymond W., Taylor, Valerie H., Milev, Roumen, Frey, Benicio N., Harkness, Kate L., Addington, Jean, and Kennedy, Sidney H.

Published
2024
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10. Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes

Author

Liu, Nana, Zhang, Longjiang, Tian, Tian, Cheng, Jingliang, Zhang, Bing, Qiu, Shijun, Geng, Zuojun, Cui, Guangbin, Zhang, Quan, Liao, Weihua, Yu, Yongqiang, Zhang, Hui, Gao, Bo, Xu, Xiaojun, Han, Tong, Yao, Zhenwei, Qin, Wen, Liu, Feng, Liang, Meng, Xu, Qiang, Fu, Jilian, Xu, Jiayuan, Zhu, Wenzhen, Zhang, Peng, Li, Wei, Shi, Dapeng, Wang, Caihong, Lui, Su, Yan, Zhihan, Chen, Feng, Li, Jiance, Zhang, Jing, Wang, Dawei, Shen, Wen, Miao, Yanwei, Xian, Junfang, Gao, Jia-Hong, Zhang, Xiaochu, Li, Mulin Jun, Xu, Kai, Zuo, Xi-Nian, Wang, Meiyun, Ye, Zhaoxiang, and Yu, Chunshui

Published
2023
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14. A longitudinal resource for population neuroscience of school-age children and adolescents in China

Author

Fan, Xue-Ru, Wang, Yin-Shan, Chang, Da, Yang, Ning, Rong, Meng-Jie, Zhang, Zhe, He, Ye, Hou, Xiaohui, Zhou, Quan, Gong, Zhu-Qing, Cao, Li-Zhi, Dong, Hao-Ming, Nie, Jing-Jing, Chen, Li-Zhen, Zhang, Qing, Zhang, Jia-Xin, Zhang, Lei, Li, Hui-Jie, Bao, Min, Chen, Antao, Chen, Jing, Chen, Xu, Ding, Jinfeng, Dong, Xue, Du, Yi, Feng, Chen, Feng, Tingyong, Fu, Xiaolan, Ge, Li-Kun, Hong, Bao, Hu, Xiaomeng, Huang, Wenjun, Jiang, Chao, Li, Li, Li, Qi, Li, Su, Liu, Xun, Mo, Fan, Qiu, Jiang, Su, Xue-Quan, Wei, Gao-Xia, Wu, Yiyang, Xia, Haishuo, Yan, Chao-Gan, Yan, Zhi-Xiong, Yang, Xiaohong, Zhang, Wenfang, Zhao, Ke, Zhu, Liqi, and Zuo, Xi-Nian

Published
2023
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15. Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics.

Author

Bridgeford, Eric W, Wang, Shangsi, Wang, Zeyi, Xu, Ting, Craddock, Cameron, Dey, Jayanta, Kiar, Gregory, Gray-Roncal, William, Colantuoni, Carlo, Douville, Christopher, Noble, Stephanie, Priebe, Carey E, Caffo, Brian, Milham, Michael, Zuo, Xi-Nian, Consortium for Reliability and Reproducibility, and Vogelstein, Joshua T

Subjects
Consortium for Reliability and Reproducibility, Humans, Artifacts, Brain Mapping, Reproducibility of Results, Genome, Connectome, Datasets as Topic, Clinical Research, Mathematical Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

Replicability, the ability to replicate scientific findings, is a prerequisite for scientific discovery and clinical utility. Troublingly, we are in the midst of a replicability crisis. A key to replicability is that multiple measurements of the same item (e.g., experimental sample or clinical participant) under fixed experimental constraints are relatively similar to one another. Thus, statistics that quantify the relative contributions of accidental deviations-such as measurement error-as compared to systematic deviations-such as individual differences-are critical. We demonstrate that existing replicability statistics, such as intra-class correlation coefficient and fingerprinting, fail to adequately differentiate between accidental and systematic deviations in very simple settings. We therefore propose a novel statistic, discriminability, which quantifies the degree to which an individual's samples are relatively similar to one another, without restricting the data to be univariate, Gaussian, or even Euclidean. Using this statistic, we introduce the possibility of optimizing experimental design via increasing discriminability and prove that optimizing discriminability improves performance bounds in subsequent inference tasks. In extensive simulated and real datasets (focusing on brain imaging and demonstrating on genomics), only optimizing data discriminability improves performance on all subsequent inference tasks for each dataset. We therefore suggest that designing experiments and analyses to optimize discriminability may be a crucial step in solving the replicability crisis, and more generally, mitigating accidental measurement error.

Published
2021

16. Genome-wide association study of hippocampal blood-oxygen-level-dependent-cerebral blood flow correlation in Chinese Han population

Author

Xue, Hui, Xu, Xiaojun, Yan, Zhihan, Cheng, Jingliang, Zhang, Longjiang, Zhu, Wenzhen, Cui, Guangbin, Zhang, Quan, Qiu, Shijun, Yao, Zhenwei, Qin, Wen, Liu, Feng, Liang, Meng, Fu, Jilian, Xu, Qiang, Xu, Jiayuan, Xie, Yingying, Zhang, Peng, Li, Wei, Wang, Caihong, Shen, Wen, Zhang, Xiaochu, Xu, Kai, Zuo, Xi-Nian, Ye, Zhaoxiang, Yu, Yongqiang, Xian, Junfang, and Yu, Chunshui

Published
2023
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21. The impact of pre-adulthood urbanicity on hippocampal subfield volumes and neurocognitive abilities in young adults

Author

Liu, Mengge, Han, Tong, Wu, Yue, Cheng, Jingliang, Zhang, Longjiang, Zhang, Bing, Zuo, Xi-Nian, Zhu, Wenzhen, Qiu, Shijun, Geng, Zuojun, Zhang, Xiaochu, Cui, Guangbin, Zhang, Quan, Yu, Yongqiang, Zhang, Hui, Gao, Bo, Xu, Xiaojun, Yao, Zhenwei, Qin, Wen, Liang, Meng, Liu, Feng, Guo, Lining, Xu, Qiang, Fu, Jilian, Xu, Jiayuan, Tang, Jie, Liu, Nana, Xue, Kaizhong, Zhang, Peng, Li, Wei, Shi, Dapeng, Wang, Caihong, Gao, Jia-Hong, Lui, Su, Yan, Zhihan, Chen, Feng, Li, Jiance, Zhang, Jing, Shen, Wen, Miao, Yanwei, Xian, Junfang, Yu, Le, Xu, Kai, Wang, Meiyun, Ye, Zhaoxiang, Liao, Wei-Hua, Wang, Dawei, and Yu, Chunshui

Published
2023
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23. Global urbanicity is associated with brain and behaviour in young people

Author

Xu, Jiayuan, Liu, Xiaoxuan, Li, Qiaojun, Goldblatt, Ran, Qin, Wen, Liu, Feng, Chu, Congying, Luo, Qiang, Ing, Alex, Guo, Lining, Liu, Nana, Liu, Huaigui, Huang, Conghong, Cheng, Jingliang, Wang, Meiyun, Geng, Zuojun, Zhu, Wenzhen, Zhang, Bing, Liao, Weihua, Qiu, Shijun, Zhang, Hui, Xu, Xiaojun, Yu, Yongqiang, Gao, Bo, Han, Tong, Cui, Guangbin, Chen, Feng, Xian, Junfang, Li, Jiance, Zhang, Jing, Zuo, Xi-Nian, Wang, Dawei, Shen, Wen, Miao, Yanwei, Yuan, Fei, Lui, Su, Zhang, Xiaochu, Xu, Kai, Zhang, Longjiang, Ye, Zhaoxiang, Banaschewski, Tobias, Barker, Gareth J., Bokde, Arun L. W., Flor, Herta, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Lemaitre, Herve, Paus, Tomáš, Poustka, Luise, Robinson, Lauren, Hohmann, Sarah, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Winterer, Jeanne, Patrick, Kevin, Calhoun, Vince, Li, Mulin Jun, Liang, Meng, Gong, Peng, Barker, Edward D., Clinton, Nicholas, Marquand, Andre, Yu, Le, Yu, Chunshui, and Schumann, Gunter

Published
2022
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24. Reduced nucleus accumbens functional connectivity in reward network and default mode network in patients with recurrent major depressive disorder

Author

Ding, Yu-Dan, Chen, Xiao, Chen, Zuo-Bing, Li, Le, Li, Xue-Ying, Castellanos, Francisco Xavier, Bai, Tong-Jian, Bo, Qi-Jing, Cao, Jun, Chang, Zhi-Kai, Chen, Guan-Mao, Chen, Ning-Xuan, Chen, Wei, Cheng, Chang, Cheng, Yu-Qi, Cui, Xi-Long, Duan, Jia, Fang, Yi-Ru, Gong, Qi-Yong, Hou, Zheng-Hua, Hu, Lan, Kuang, Li, Li, Feng, Li, Hui-Xian, Li, Kai-Ming, Li, Tao, Liu, Yan-Song, Liu, Zhe-Ning, Long, Yi-Cheng, Lu, Bin, Luo, Qing-Hua, Meng, Hua-Qing, Peng, Dai-Hui, Qiu, Hai-Tang, Qiu, Jiang, Shen, Yue-Di, Shi, Yu-Shu, Si, Tian-Mei, Tang, Yan-Qing, Wang, Chuan-Yue, Wang, Fei, Wang, Kai, Wang, Li, Wang, Xiang, Wang, Ying, Wang, Yu-Wei, Wu, Xiao-Ping, Wu, Xin-Ran, Xie, Chun-Ming, Xie, Guang-Rong, Xie, Hai-Yan, Xie, Peng, Xu, Xiu-Feng, Yang, Hong, Yang, Jian, Yao, Jia-Shu, Yao, Shu-Qiao, Yin, Ying-Ying, Yuan, Yong-Gui, Zang, Yu-Feng, Zhang, Ai-Xia, Zhang, Hong, Zhang, Ke-Rang, Zhang, Lei, Zhang, Zhi-Jun, Zhao, Jing-Ping, Zhou, Ru-Bai, Zhou, Yi-Ting, Zhu, Jun-Juan, Zhu, Zhi-Chen, Zou, Chao-Jie, Zuo, Xi-Nian, Yan, Chao-Gan, and Guo, Wen-Bin

Published
2022
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27. Atypical brain aging and its association with working memory performance in major depressive disorder

Author

Ho, Natalie C.W., primary, Bethlehem, Richard AI., additional, Seidlitz, Jakob, additional, Nogovitsyn, Nikita, additional, Metzak, Paul, additional, Ballester, Pedro L., additional, Hassel, Stefanie, additional, Rotzinger, Susan, additional, Poppenk, Jordan, additional, Lam, Raymond W., additional, Taylor, Valerie H., additional, Milev, Roumen, additional, Adamson, Chris, additional, Adler, Sophie, additional, Alexander-Bloch, Aaron F., additional, Anagnostou, Evdokia, additional, Anderson, Kevin M., additional, Areces-Gonzalez, Ariosky, additional, Astle, Duncan E., additional, Auyeung, Bonnie, additional, Ayub, Muhammad, additional, Bae, Jong Bin, additional, Ball, Gareth, additional, Baron-Cohen, Simon, additional, Beare, Richard, additional, Bedford, Saashi A., additional, Benegal, Vivek, additional, Bethlehem, Richard A.I., additional, Beyer, Frauke, additional, Blangero, John, additional, Blesa Cábez, Manuel, additional, Boardman, James P., additional, Borzage, Matthew, additional, Bosch-Bayard, Jorge F., additional, Bourke, Niall, additional, Bullmore, Edward T., additional, Calhoun, Vince D., additional, Chakravarty, Mallar M., additional, Chen, Christina, additional, Chertavian, Casey, additional, Chetelat, Gaël, additional, Chong, Yap S., additional, Corvin, Aiden, additional, Costantino, Manuela, additional, Courchesne, Eric, additional, Crivello, Fabrice, additional, Cropley, Vanessa L., additional, Crosbie, Jennifer, additional, Crossley, Nicolas, additional, Delarue, Marion, additional, Delorme, Richard, additional, Desrivieres, Sylvane, additional, Devenyi, Gabriel, additional, Di Biase, Maria A., additional, Dolan, Ray, additional, Donald, Kirsten A., additional, Donohoe, Gary, additional, Dorfschmidt, Lena, additional, Dunlop, Katharine, additional, Edwards, Anthony D., additional, Elison, Jed T., additional, Ellis, Cameron T., additional, Elman, Jeremy A., additional, Eyler, Lisa, additional, Fair, Damien A., additional, Fletcher, Paul C., additional, Fonagy, Peter, additional, Franz, Carol E., additional, Galan-Garcia, Lidice, additional, Gholipour, Ali, additional, Giedd, Jay, additional, Gilmore, John H., additional, Glahn, David C., additional, Goodyer, Ian M., additional, Grant, P.E., additional, Groenewold, Nynke A., additional, Gudapati, Shreya, additional, Gunning, Faith M., additional, Gur, Raquel E., additional, Gur, Ruben C., additional, Hammill, Christopher F., additional, Hansson, Oskar, additional, Hedden, Trey, additional, Heinz, Andreas, additional, Henson, Richard N., additional, Heuer, Katja, additional, Hoare, Jacqueline, additional, Holla, Bharath, additional, Holmes, Avram J., additional, Huang, Hao, additional, Ipser, Jonathan, additional, Jack, Clifford R., additional, Jackowski, Andrea P., additional, Jia, Tianye, additional, Jones, David T., additional, Jones, Peter B., additional, Kahn, Rene S., additional, Karlsson, Hasse, additional, Karlsson, Linnea, additional, Kawashima, Ryuta, additional, Kelley, Elizabeth A., additional, Kern, Silke, additional, Kim, Ki-Woong, additional, Kitzbichler, Manfred G., additional, Kremen, William S., additional, Lalonde, François, additional, Landeau, Brigitte, additional, Lerch, Jason, additional, Lewis, John D., additional, Li, Jiao, additional, Liao, Wei, additional, Liston, Conor, additional, Lombardo, Michael V., additional, Lv, Jinglei, additional, Mallard, Travis T., additional, Marcelis, Machteld, additional, Mathias, Samuel R., additional, Mazoyer, Bernard, additional, McGuire, Philip, additional, Meaney, Michael J., additional, Mechelli, Andrea, additional, Misic, Bratislav, additional, Morgan, Sarah E., additional, Mothersill, David, additional, Ortinau, Cynthia, additional, Ossenkoppele, Rik, additional, Ouyang, Minhui, additional, Palaniyappan, Lena, additional, Paly, Leo, additional, Pan, Pedro M., additional, Pantelis, Christos, additional, Park, Min Tae M., additional, Paus, Tomas, additional, Pausova, Zdenka, additional, Paz-Linares, Deirel, additional, Pichet Binette, Alexa, additional, Pierce, Karen, additional, Qian, Xing, additional, Qiu, Anqi, additional, Raznahan, Armin, additional, Rittman, Timothy, additional, Rodrigue, Amanda, additional, Rollins, Caitlin K., additional, Romero-Garcia, Rafael, additional, Ronan, Lisa, additional, Rosenberg, Monica D., additional, Rowitch, David H., additional, Salum, Giovanni A., additional, Satterthwaite, Theodore D., additional, Schaare, H. Lina, additional, Schabdach, Jenna, additional, Schachar, Russell J., additional, Schöll, Michael, additional, Schultz, Aaron P., additional, Sharp, David, additional, Shinohara, Russell T., additional, Skoog, Ingmar, additional, Smyser, Christopher D., additional, Sperling, Reisa A., additional, Stein, Dan J., additional, Stolicyn, Aleks, additional, Suckling, John, additional, Sullivan, Gemma, additional, Thyreau, Benjamin, additional, Toro, Roberto, additional, Traut, Nicolas, additional, Tsvetanov, Kamen A., additional, Turk-Browne, Nicholas B., additional, Tuulari, Jetro J., additional, Tzourio, Christophe, additional, Vachon-Presseau, Étienne, additional, Valdes-Sosa, Mitchell J., additional, Valdes-Sosa, Pedro A., additional, Valk, Sofie L., additional, van Amelsvoort, Therese, additional, Vandekar, Simon N., additional, Vasung, Lana, additional, Vértes, Petra E., additional, Victoria, Lindsay W., additional, Villeneuve, Sylvia, additional, Villringer, Arno, additional, Vogel, Jacob W., additional, Wagstyl, Konrad, additional, Wang, Yin-Shan S., additional, Warfield, Simon K., additional, Warrier, Varun, additional, Westman, Eric, additional, Westwater, Margaret L., additional, Whalley, Heather C., additional, White, Simon R., additional, Witte, A. Veronica, additional, Yang, Ning, additional, Yeo, B.T. Thomas, additional, Yun, Hyuk Jin, additional, Zalesky, Andrew, additional, Zar, Heather J., additional, Zettergren, Anna, additional, Zhou, Juan H., additional, Ziauddeen, Hisham, additional, Zimmerman, Dabriel, additional, Zugman, Andre, additional, Zuo, Xi-Nian N., additional, Frey, Benicio N., additional, Harkness, Kate L., additional, Addington, Jean, additional, and Kennedy, Sidney H., additional

Published
2024
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28. Brain structural alterations in MDD patients with gastrointestinal symptoms: Evidence from the REST-meta-MDD project

Author

Liu, Peng-hong, Li, Yan, Zhang, Ai-Xia, Sun, Ning, Li, Gai-Zhi, Chen, Xiao, Bai, Tong-Jian, Bo, Qi-Jing, Chen, Guan-Mao, Chen, Ning-Xuan, Chen, Tao-Lin, Chen, Wei, Cheng, Chang, Cheng, Yu-Qi, Cui, Xi-Long, Duan, Jia, Fang, Yi-Ru, Gong, Qi-Yong, Guo, Wen-Bin, Hou, Zheng-Hua, Hu, Lan, Kuang, Li, Li, Feng, Li, Kai-Ming, Li, Tao, Liu, Yan-Song, Liu, Zhe-Ning, Long, Yi-Cheng, Luo, Qing-Hua, Meng, Hua-Qing, Peng, Dai-Hui, Qiu, Hai-Tang, Qiu, Jiang, Shen, Yue-Di, Shi, Yu-Shu, Wang, Fei, Wang, Kai, Wang, Li, Wang, Xiang, Wang, Ying, Wu, Xiao-Ping, Wu, Xin-Ran, Xie, Chun-Ming, Xie, Guang-Rong, Xie, Hai-Yan, Xie, Peng, Xu, Xiu-Feng, Yang, Hong, Yang, Jian, Yao, Jia-Shu, Yao, Shu-Qiao, Yin, Ying-Ying, Yuan, Yong-Gui, Zhang, Hong, Zhang, Lei, Zhang, Zhi-Jun, Zhou, Ru-Bai, Zhou, Yi-Ting, Zhu, Jun-Juan, Zou, Chao-Jie, Si, Tian-Mei, Zuo, Xi-Nian, Yan, Chao-Gan, and Zhang, Ke-Rang

Published
2021
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29. Disrupted intrinsic functional brain topology in patients with major depressive disorder

Author

Yang, Hong, Chen, Xiao, Chen, Zuo-Bing, Li, Le, Li, Xue-Ying, Castellanos, Francisco Xavier, Bai, Tong-Jian, Bo, Qi-Jing, Cao, Jun, Chang, Zhi-Kai, Chen, Guan-Mao, Chen, Ning-Xuan, Chen, Wei, Cheng, Chang, Cheng, Yu-Qi, Cui, Xi-Long, Duan, Jia, Fang, Yiru, Gong, Qi-Yong, Guo, Wen-Bin, Hou, Zheng-Hua, Hu, Lan, Kuang, Li, Li, Feng, Li, Hui-Xian, Li, Kai-Ming, Li, Tao, Liu, Yan-Song, Liu, Zhe-Ning, Long, Yi-Cheng, Lu, Bin, Luo, Qing-Hua, Meng, Hua-Qing, Peng, Daihui, Qiu, Hai-Tang, Qiu, Jiang, Shen, Yue-Di, Shi, Yu-Shu, Si, Tian-Mei, Tang, Yan-Qing, Wang, Chuan-Yue, Wang, Fei, Wang, Kai, Wang, Li, Wang, Xiang, Wang, Ying, Wang, Yu-Wei, Wu, Xiao-Ping, Wu, Xin-Ran, Xie, Chun-Ming, Xie, Guang-Rong, Xie, Hai-Yan, Xie, Peng, Xu, Xiu-Feng, Yang, Jian, Yao, Jia-Shu, Yao, Shu-Qiao, Yin, Ying-Ying, Yuan, Yong-Gui, Zang, Yu-Feng, Zhang, Ai-Xia, Zhang, Hong, Zhang, Ke-Rang, Zhang, Lei, Zhang, Zhi-Jun, Zhao, Jing-Ping, Zhou, Rubai, Zhou, Yi-Ting, Zhu, Jun-Juan, Zhu, Zhi-Chen, Zou, Chao-Jie, Zuo, Xi-Nian, and Yan, Chao-Gan

Published
2021
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32. Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks

Author

Betzel, Richard F., Fukushima, Makoto, He, Ye, Zuo, Xi-Nian, and Sporns, Olaf

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

We investigate the relationship of resting-state fMRI functional connectivity estimated over long periods of time with time-varying functional connectivity estimated over shorter time intervals. We show that using Pearson's correlation to estimate functional connectivity implies that the range of fluctuations of functional connections over short time scales is subject to statistical constraints imposed by their connectivity strength over longer scales. We present a method for estimating time-varying functional connectivity that is designed to mitigate this issue and allows us to identify episodes where functional connections are unexpectedly strong or weak. We apply this method to data recorded from $N=80$ participants, and show that the number of unexpectedly strong/weak connections fluctuates over time, and that these variations coincide with intermittent periods of high and low modularity in time-varying functional connectivity. We also find that during periods of relative quiescence regions associated with default mode network tend to join communities with attentional, control, and primary sensory systems. In contrast, during periods where many connections are unexpectedly strong/weak, default mode regions dissociate and form distinct modules. Finally, we go on to show that, while all functional connections can at times manifest stronger (more positively correlated) or weaker (more negatively correlated) than expected, a small number of connections, mostly within the visual and somatomotor networks, do so a disproportional number of times. Our statistical approach allows the detection of functional connections that fluctuate more or less than expected based on their long-time averages and may be of use in future studies characterizing the spatio-temporal patterns of time-varying functional connectivity, Comment: 47 Pages, 8 Figures, 4 Supplementary Figures

Published
2015
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33. Fluctuations between high- and low-modularity topology in time-resolved functional connectivity

Author

Fukushima, Makoto, Betzel, Richard F., He, Ye, de Reus, Marcel A., Heuvel, Martijn P. van den, Zuo, Xi-Nian, and Sporns, Olaf

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Modularity is an important topological attribute for functional brain networks. Recent studies have reported that modularity of functional networks varies not only across individuals being related to demographics and cognitive performance, but also within individuals co-occurring with fluctuations in network properties of functional connectivity, estimated over short time intervals. However, characteristics of these time-resolved functional networks during periods of high and low modularity have remained largely unexplored. In this study we investigate spatiotemporal properties of time-resolved networks in the high and low modularity periods during rest, with a particular focus on their spatial connectivity patterns, temporal homogeneity and test-retest reliability. We show that spatial connectivity patterns of time-resolved networks in the high and low modularity periods are represented by increased and decreased dissociation of the default mode network module from task-positive network modules, respectively. We also find that the instances of time-resolved functional connectivity sampled from within the high (low) modularity period are relatively homogeneous (heterogeneous) over time, indicating that during the low modularity period the default mode network interacts with other networks in a variable manner. We confirmed that the occurrence of the high and low modularity periods varies across individuals with moderate inter-session test-retest reliability and that it is correlated with previously-reported individual differences in the modularity of functional connectivity estimated over longer timescales. Our findings illustrate how time-resolved functional networks are spatiotemporally organized during periods of high and low modularity, allowing one to trace individual differences in long-timescale modularity to the variable occurrence of network configurations at shorter timescales., Comment: Reorganized the paper; to appear in NeuroImage; arXiv abstract shortened to fit within character limits

Published
2015
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34. Functional brain modules reconfigure at multiple scales across the human lifespan

Author

Betzel, Richard F., Mišić, Bratislav, He, Ye, Rumschlag, Jeffrey, Zuo, Xi-Nian, and Sporns, Olaf

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

The human brain is a complex network of interconnected brain regions organized into functional modules with distinct roles in cognition and behavior. An important question concerns the persistence and stability of these modules over the human lifespan. Here we use graph-theoretic analysis to algorithmically uncover the brain's intrinsic modular organization across multiple spatial scales ranging from small communities comprised of only a few brain regions to large communities made up of many regions. We find that at coarse scales modules become progressively more segregated, while at finer scales segregation decreases. Module composition also exhibits scale-specific and age-dependent changes. At coarse scales, the module assignments of regions normally associated with control, default mode, attention, and visual networks are highly flexible. At fine scales the most flexible regions are associated with the default mode network. Finally, we show that, with age, some regions in the default mode network, specifically retrosplenial cortex, maintain a greater proportion of functional connections to their own module, while regions associated with somatomotor and saliency/ventral attention networks distribute their links more evenly across modules., Comment: 56 pages, 7 figures, 6 supplemental figures

Published
2015

35. Generative models of the human connectome

Author

Betzel, Richard F., Avena-Koenigsberger, Andrea, Goñi, Joaquín, He, Ye, de Reus, Marcel A., Griffa, Alessandra, Vértes, Petra E., Mišić, Bratislav, Thiran, Jean-Philippe, Hagmann, Patric, Heuvel, Martijn van den, Zuo, Xi-Nian, Bullmore, Edward T., and Sporns, Olaf

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan., Comment: 38 pages, 5 figures + 19 supplemental figures, 1 table

Published
2015
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37. Charting brain growth in tandem with brain templates at school age

Author

Dong, Hao-Ming, Castellanos, F. Xavier, Yang, Ning, Zhang, Zhe, Zhou, Quan, He, Ye, Zhang, Lei, Xu, Ting, Holmes, Avram J., Thomas Yeo, B.T., Chen, Feiyan, Wang, Bin, Beckmann, Christian, White, Tonya, Sporns, Olaf, Qiu, Jiang, Feng, Tingyong, Chen, Antao, Liu, Xun, Chen, Xu, Weng, Xuchu, Milham, Michael P., and Zuo, Xi-Nian

Published
2020
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40. How growth without siblings affects adult brain and behavior

Author

Yu, Chunshui, primary, Tang, Jie, additional, Zhang, Jing, additional, Li, Wei, additional, Wang, Meiyun, additional, Cheng, Jingliang, additional, Zhang, Bing, additional, Zhu, Wenzhen, additional, Qiu, Shijun, additional, Cui, Guangbin, additional, Yu, Yongqiang, additional, Liao, Weihua, additional, Zhang, Hui, additional, Gao, Bo, additional, Xu, Xiaojun, additional, Yang, Yunjun, additional, Han, Tong, additional, Yao, Zhenwei, additional, Zhang, Quan, additional, Qin, Wen, additional, Liu, Feng, additional, Liang, Meng, additional, Wang, Sijia, additional, Xu, Qiang, additional, Xu, Jiayuan, additional, Fu, Jilian, additional, Ji, Yuan, additional, Liu, Nana, additional, Zhang, Peng, additional, Shi, Dapeng, additional, Wang, Caihong, additional, Lui, Su, additional, Yan, Zhihan, additional, Chen, Feng, additional, Shen, Wen, additional, Miao, Yanwei, additional, Wang, Dawei, additional, Xian, Junfang, additional, Zhang, Xiaochu, additional, Xu, Kai, additional, Zuo, Xi-Nian, additional, Zhang, Long Jiang, additional, Ye, Zhaoxiang, additional, Geng, Zuojun, additional, Gao, Jia-Hong, additional, and Consortium, The CHIMGEN, additional

Published
2024
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42. Reduced default mode network functional connectivity in patients with recurrent major depressive disorder

Author

Yan, Chao-Gan, Chen, Xiao, Li, Le, Castellanos, Francisco Xavier, Bai, Tong-Jian, Bo, Qi-Jing, Cao, Jun, Chen, Guan-Mao, Chen, Ning-Xuan, Chen, Wei, Cheng, Chang, Cheng, Yu-Qi, Cui, Xi-Long, Duan, Jia, Fang, Yi-Ru, Gong, Qi-Yong, Guo, Wen-Bin, Hou, Zheng-Hua, Hu, Lan, Kuang, Li, Li, Feng, Li, Kai-Ming, Li, Tao, Liu, Yan-Song, Liu, Zhe-Ning, Long, Yi-Cheng, Luo, Qing-Hua, Meng, Hua-Qing, Peng, Dai-Hui, Qiu, Hai-Tang, Qiu, Jiang, Shen, Yue-Di, Shi, Yu-Shu, Wang, Chuan-Yue, Wang, Fei, Wang, Kai, Wang, Li, Wang, Xiang, Wang, Ying, Wu, Xiao-Ping, Wu, Xin-Ran, Xie, Chun-Ming, Xie, Guang-Rong, Xie, Hai-Yan, Xie, Peng, Xu, Xiu-Feng, Yang, Hong, Yang, Jian, Yao, Jia-Shu, Yao, Shu-Qiao, Yin, Ying-Ying, Yuan, Yong-Gui, Zhang, Ai-Xia, Zhang, Hong, Zhang, Ke-Rang, Zhang, Lei, Zhang, Zhi-Jun, Zhou, Ru-Bai, Zhou, Yi-Ting, Zhu, Jun-Juan, Zou, Chao-Jie, Si, Tian-Mei, Zuo, Xi-Nian, Zhao, Jing-Ping, and Zang, Yu-Feng

Published
2019

49. Spontaneous low-frequency fluctuations in the neural system for emotional perception in major psychiatric disorders: amplitude similarities and differences across frequency bands

Author

Chang, Miao, Edmiston, Elliot K., Womer, Fay Y., Zhou, Qian, Wei, Shengnan, Jiang, Xiaowei, Zhou, Yifang, Ye, Yuting, Huang, Haiyan, Zuo, Xi-Nian, Xu, Ke, Tang, Yanqing, and Wang, Fei

Subjects
Bipolar disorder -- Comparative analysis -- Physiological aspects, Schizophrenia -- Comparative analysis -- Physiological aspects, Emotions -- Comparative analysis, Major depressive disorder -- Physiological aspects, Neurons -- Physiological aspects, Mental disorders, Brain, Health, Psychology and mental health
Abstract

Background: Growing evidence indicates both shared and distinct features of emotional perception in schizophrenia, bipolar disorder and major depressive disorder. In these disorders, alterations in spontaneous low-frequency fluctuations have been reported in the neural system for emotional perception, but the similarities and differences in the amplitude of low-frequency fluctuation (ALFF) across the 3 disorders are unknown. Methods: We compared ALFF and its signal balance in the neural system for emotional perception at 2 frequency bands (slow-5 and slow-4) in 119 participants with schizophrenia, 100 with bipolar disorder, 123 with major depressive disorder and 183 healthy controls. We performed exploratory Pearson partial correlation analyses to determine the relationship between ALFF signal balance and clinical variables. Results: We observed commonalities in ALFF change patterns across the 3 disorders for emotional perception neural substrates, such as increased ALFF in the anterior cerebrum (including subcortical, limbic, paralimbic and heteromodal cortical regions) and decreased ALFF in the posterior visual cortices. Schizophrenia, bipolar disorder and major depressive disorder showed significantly decreased ALFF signal balance in the neural system for emotional perception at both slow-5 and slow-4 frequency bands, with the greatest alterations for schizophrenia, followed by bipolar disorder and major depressive disorder. We found a negative correlation between ALFF signal balance and negative/disorganized symptoms in slow-4 across the 3 disorders. Limitations: The relatively broad age range in our sample and the cross-sectional study design may not account for our findings. Conclusion: The extent of the commonalities we observed further support the concept of core neurobiological disruptions shared among the 3 disorders; ALFF signal balance could be an important neuroimaging marker for the diagnosis and treatment of schizophrenia, bipolar disorder and major depressive disorder., Introduction Psychiatric nosology arose in central Europe toward the end of the 19th century. In particular, Kraepelin made the foundational distinction between dementia praecox (schizophrenia) and manic depression. (1) The [...]

Published
2019
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