基本介紹
- 中文名：代政嘉
- 國籍：中國
- 民族：漢
- 出生地：湖南南縣
- 畢業院校：北京師範大學
- 學位/學歷：博士
- 專業方向：認知神經科學
- 任職院校：中山大學
研究領域,人物經歷,教育背景,職業經歷,科研項目,科研論著,教授課程,
研究領域
人腦連線組學、情緒的個體差異、情緒相關精神疾病（抑鬱症、焦慮症、精神分裂症、阿爾茨海默病）、神經影像計算、人工智慧
主要研究方向：
（1）使用多模態神經影像技術（結構磁共振影像、功能磁共振影像）探究活體人腦網路的連線模式，包括結構網路的形成機制、功能網路的描述以及結構和功能網路的關聯；
（2）人腦網路個體差異的研究，探索其原因以及是否可以作為指紋圖，識別個體情緒相關的指標；
（3）採用多模態影像技術研究精神疾病患者客觀的生物標記物，並為疾病的治療提供神經基礎。
人物經歷
教育背景
· 2005年-2009年：北京理工大學大學理學院學院 數學專業 理學學士
· 2009年-2015年：北京師範大學認知神經科學與學習國家重點實驗室 認知神經科學專業 理學博士
職業經歷
· 2015年6月-2017年1月：中山大學大學心理學系 講師
· 2017年1月-2022年4月：中山大學大學心理學系 副教授
· 2022年4月-至今：中山大學大學心理學系 教授
科研項目
• 廣東省自然科學基金面上項目，人腦網路通訊策略及其在阿爾茨海默病中的套用，2022-2024，主持
• 北京師範大學認知神經科學與學習國家重點實驗室開放課題，基於多模態人腦連線組的認知老化神經機制研究，2021.01-2022.12
• 廣東省自然科學基金面上項目，幸福感個體差異的腦連線組學研究，2019.10-2022.09，主持
• 中山大學青年教師重點培育項目，幸福感的神經機制及其與情緒調節的關聯研究，2019.01-2020.12，主持
• 國家自然科學基金青年項目，基於多模態磁共振影像的阿爾茨海默病疾病進程腦連線組學研究，2017.01-2019.12，主持
• 廣東省自然科學基金-博士啟動項目，基於靜息態功能磁共振成像的人腦功能網路動態特性及其套用研究，2016.06-2019.06，主持
• 中山大學百人計畫二期——緊缺優秀青年人才，2015.06-2018.06，主持
科研論著
近年來在本領域國際期刊發表SCI/SSCI論文42篇（ESI Top 1%高被引論文3篇），其中以第一/共同第一作者和通訊作者在Schizophrenia Bulletin、Radiology、NeuroImage、Cerebral Cortex、Social cognitive and affective neuroscience等領域著名期刊發表研究論文26篇（ESI Top 1%高被引論文1篇）。論文被Nature Reviews系列期刊(包括Nature Reviews Neuroscience和Nature Reviews Neurology)、Trends in Cognitive Sciences、The American Journal of Psychiatry, PNAS、BRAIN等國際頂尖期刊多次正面引用，論文的累計影響因子約為200，SCI引用1900餘次。(*為通訊作者，為共同第一作者)
1.Gu, Y., Li, L., Zhang, Y., Ma, J., Yang, C., Xiao, Y., Shu, N., Can C, Lin, Y. *, Dai, Z. *, 2022. The overlapping modular organization of human brain functional networks across the adult lifespan. Neuroimage, In press. (SCI, Q1)
2.Fan, L., Yu, M., Zhu, Y., Tang, X., Wang, X., Zhang, X., Ma, J., Zhang, J., Zhang, X.*, Dai, Z. *, 2022. Aberrant Large-scale Brain Modules in Deficit and Non-deficit Schizophrenia. Progress in Neuropsychopharmacology & Biological Psychiatry, 113, 110461. (SCI, Q1)
3.Sun, Y., Ma, J., Huang, M., Yi, Y., Wang, Y., Gu, Y., Lin, Y., Li, M., Dai, Z. *, 2022. Functional connectivity Dynamics as a Function of the Fluctuation of Tension during Film Watching. Brain Imaging and Behavior, In press. (SCI, Q2)
4.Li, L., Wei, Y., Zhang, J., Ma, J., Yi, Y., Gu, Y., Li, L., Lin, Y., Dai, Z. *, 2021. Gene Expression Associated with Individual Variability in Intrinsic Functional Connectivity. NeuroImage, 245, 118743. (SCI, Q1)
5.Lin, Y., Ma, J., Huang, B., Zhang, J., Zhang, Y., Dai, Z*, 2021. Predicting Human Intrinsic Functional Connectivity from Structural Connectivity: An Artificial Neural Network Approach. IEEE Transactions on Network Science and Engineering, 8, 2625-2638. (SCI, Q1)
6.Ma, J., Zhang, J., Lin, Y. *, Dai, Z*, 2021. Cost-efficiency trade-offs of the human brain network revealed by a multiobjective evolutionary algorithm. NeuroImage, 236, 118040. (SCI, Q1)
7.Guo, X., Yang, F., Fan, L., Gu, Y., Ma, J., Zhang, J., Liao, M.*, Zhai, T., Zhang, Y., Li, L., Su, L., Dai, Z.*, 2021. Disruption of Functional and Structural Networks in First-Episode, Drug-naïve Adolescents with Generalized Anxiety Disorder. Journal of Affective Disorders 284, 229-237. (SSCI, Q1)
8.Xiao, Y. , Lin, Y., Ma, J., Qian, J., Ke, Z., Li, L., Yi, Y., Zhang, J., Cam-CAN, Dai, Z. *, 2021. Predicting Visual Working Memory with Multimodal MRI, Hum Brain Mapp 42, 1446-1462. (SCI, Q1)
9.Ma, J., Lin, Y., Hu, C., Zhang, J., Yi, Y., Dai, Z.,2021.Integrated and Segregated Frequency Architecture of Human Brain Network, Brain structure and function 226, 335-350. (SCI, Q1)
10. Yang, F., Zhang, J., Fan, L., Liao, M., Wang, Y., Chen, Chang., Zhai, T., Zhang, Y., Li, L., Su, L., Dai, Z. *, 2020. White Matter Structural Network Disturbances in First-Episode, Drug-naïve Adolescents with Generalized Anxiety Disorder, Journal of Psychiatric Research 130, 394-404. (SSCI, Q1)
11. Gu, Y., Lin, Y., Huang, L., Ma, J., Zhang, J., Xiao, Y., Dai, Z.*, Alzheimer's Disease Neuroimaging Initiative, 2020. Abnormal Dynamic Functional Connectivity in Alzheimer’s Disease. CNS Neuroscience & Therapeutics 26, 962-971. (SCI, Q1)
12. Yang, F., Fan, L., Zhai, T., Lin, Y., Wang, Y., Ma, J., Liao, M., Zhang, Y., Li, L., Su, L., Dai, Z.*, 2019. Decreased Intrinsic Functional Connectivity in Default Mode and Fronto-Parietal Networks in First-Episode, Drug-Naive Adolescents with Generalized Anxiety Disorder. Frontiers in Human Neuroscience 12, 539. (SCI, Q2)
13. Dai, Z., Lin, Q., Li, T., Wang, X., Yuan, H., Yu, X., He, Y., Wang, H., 2019. Disrupted structural and fucntional brain networks in Alzheimer's disease. Neurobiology of aging 75, 71-82. (SCI, Q1)
14. Lin, Y., Ma, J., Gu, Y., Yang, S., Li, LMW., Dai, Z. *, 2018. Intrinsic Overlapping Modular Organization of Human Brain Functional Networks Intrinsic Revealed by A Multiobjective Evolutionary Algorithm. Neuroimage 181, 430-445. (SCI, Q1)
15. Yi, Y., Li, L M W., Xiao, Y., Ma, J., Fan, L., Dai, Z. *, 2018. Brain Activity Mediates the Relation between Emotional But Not Instrumental Support and Trait Loneliness. Social cognitive and affective neuroscience 13, 995-1002. (SCI, Q2)
16. Li, L M W., Luo, S., Ma, J., Lin, Y., Fan, L., Zhong, S., Yang, J., Huang, Y., Gu, Y., Fan, L., Dai, Z. *, Wu,X., 2018. Functional connectivity pattern underlies individual differences in independent self-construal. Social cognitive and affective neuroscience 13, 269-280. (SCI, Q2)
17. Yu, M., Dai, Z., Tang, X., Wang, X., Zhang, X., Sha, W., Yao, S., Shu, N., Wang, X., Yang, J., Zhang, X., Zhang, X., He, Y., Zhang, Z., 2017. Convergence and divergence of brain network dysfunction in deficit and non-deficit schizophrenia. Schizophr Bull 43, 1315-1328. (SCI, Q1)
18. Wang, Z. , Dai, Z. , Shu, H., Liao, X., Yue, C., Liu, D., Guo, Q., He, Y., Zhang, Z., 2017 APOE Genotype Effects on Intrinsic Brain Network Connectivity in Patients with Amnestic Mild Cognitive Impairment. Sci.Rep 7, 397. (SCI, Q1)
19. Sun, Y., Dai, Z., Li, Y., Sheng, C., Li, H., Wang, X., Chen, X., He, Y., Han, Y., 2016. Subjective cognitive decline: mapping functional and structural brain changes—a combined resting-state functional and structural MR imaging study. Radiology 281, 185-92. (SCI, Q1)
20. Wang, Z., Dai, Z., Shu, H., Liu, D., Guo, Q., He, Y., Zhang, Z., 2016 Cortical Thickness and Microstructural White Matter Changes Detect Amnestic Mild Cognitive Impairment. J Alzheimers Dis 56(1), 415-428. (SCI, Q2)
21. Dai Z., Yan C., Li K., Wang Z., Wang J., Cao M., Lin Q., Shu N., Xia M., Bi Y., He Y., 2015. Identifying and mapping connectivity patterns of brain network hubs in Alzheimer’s disease. Cereb Cortex, 25(10), 3723-3742. (SCI, Q1)
22. Dai, Z., Bi, Y., He, Y., 2015. With great brain hub connectivity comes great vulnerability. CNS Neuroscience & Therapeutics 21(7), 541-542. (Commentary, SCI, Q1)
23. Liu, Y., Dai, Z., Duan, Y., Huang, J., Ren, Z., Liu, Z., Dong, H., Shu, N., Vrenken, H., Wattjes, M., Barkhof, F., He, Y., Li, K., 2015. Whole brain functional connectivity in clinically isolated syndrome without conventional brain MRI lesions. Eur Radiol 26(9), 2982-91. (SCI, Q1)
24. Liu, C., Dai, Z., Zhang, R., Zhang, M., Hou, Y., Qi, Z., Huang, Z., Lin, Y., Zhan, S., He, Y., Wang, Y., 2015. Mapping intrinsic functional brain changes and repetitive transcranial magnetic stimulation neuromodulation in idiopathic restless legs syndrome: a resting-state functional magnetic resonance imaging study. Sleep Med 16(6), 785-791. (SCI, Q2)
25. Dai, Z., He, Y., 2014. Disrupted structural and functional brain connectomes in mild cognitive impairment and Alzheimer’s disease. Neurosci Bull 30(2), 217-232. (SCI, Q2)
26. Dai, Z., Yan, C., Wang, Z., Wang, J., Xia, M., Li, K., He, Y., 2012. Discriminative analysis of early Alzheimer's disease using multi-modal imaging and multi-level characterization with multi-classifier (M3). Neuroimage 59(3), 2187-2195. (SCI, Q1)
教授課程
·本科生:《腦科學初探》，《神經影像技術與心理健康》，《Matlab程式設計基礎》，《每周心理學研究論壇》
•碩士生: 《磁共振成像數據分析專題》
•博士生: 《磁共振成像數據分析專題》
