基本信息


詹阳男博导中国科学院深圳先进技术研究院
电子邮件： yang.zhan@siat.ac.cn
通信地址： 深圳市南山区西丽深圳大学城学苑大道1068号
邮政编码： 518055
实验室：http://zhanlab.siat.ac.cn



部门/实验室：脑所
研究领域系统神经科学；神经环路与行为；神经信号处理

招生信息
招生专业071006-神经生物学
081002-信号与信息处理

招生方向神经环路与行为，神经信号处理
神经信号处理


教育背景2006-01--2010-06英国剑桥大学博士
2003-10--2005-10英国约克大学硕士（研究式）
1999-10--2003-07大连理工大学本科


工作经历
工作简历2010-06~2014-06,欧洲分子生物实验室,博士后


科研活动1. Zhong T, Zhang M, Fu Y, Han Y, Guan H, He H, Zhao T, Xing L, Xue X*, Zhang Y*, Zhan Y*, An artificial triboelectricity-brain-behavior closed loop for intelligent olfactory substitution. Nano Energy. 2019, 63, 103884.
2. Zeng H, He H, Fu Y, Zhao T, Han W, Xing L, Zhang Y*, Zhan Y*, Xue X*, A self-powered brain-linked biosensing electronic-skin for actively tasting beverage and its potential application in artificial gustation. Nanoscale. 2018. DOI: 10.1039/c8nr06178e.
3. Dai XJ, Jiang J, Zhang Z, Nie X, Liu BX, Pei L, Gong H, Hu J, Lu G*, Zhan Y*. Plasticity and Susceptibility of Brain Morphometry Alterations to Insufficient Sleep. Front Psychiatry. 2018, 9:266.
4. Dai Y, Fu Y, Zeng H, Xing L, Zhang Y*, Zhan Y*, Xue X*. A Self-Powered Brain-Linked Vision Electronic-Skin Based on Triboelectric-Photodetecing Pixel-Addressable Matrix for Visual Image Recognition and Behavior Intervention. Advanced Functional Materials. 2018, 28, **.
5. Fu Y, Zhang M, Dai Y, Zeng H, Sun C, Han Y, Xing L, Wang S, Xue X*, Zhan Y*, Zhang Y*, A self-powered brain multi-perception receptor for sensory-substitution application. Nano Energy. 2018, 44: 43–52.
6. Zhou TT, Zhu H, Fan ZX, Wang F, Chen Y, Liang HX, Yang ZF, Zhang L, Lin LN, Zhan Y, Wang Z, Hu H*. History of winning remodels thalamo-PFC circuit to reinforce social dominance. Science. 2017, 357: 162-168.
7. Franklin TB, Silva BA, Perova Z, Marrone L, Masferrer ME, Zhan Y, Kaplan A, Greetham L, Verrechia V, Halman A, Pagella S, Vyssotski AL, Illarionova A, Grinevich V, Branco T, Gross CT*. Prefrontal cortical control of a brainstem social behavior circuit. Nature Neurosci. 2017, 20(2):260-270.
8. Zhan Y*. Harnessing GABAergic Transmission for Slow Oscillations. Neurosci Bull. 2016, 32(5): 501-502.
9. Song W, Xu Q, Zhang Y, Zhan Y, Zheng W*, Song L*. Fully integrated reflection-mode photoacoustic, two-photon, and second harmonic generation microscopy in vivo, Sci Rep. 2016, 6: 32240.
10. Lu Y, Zhong C, Wang L, Wei P, He W, Huang K, Zhang Y, Zhan Y, Feng G, Wang L*. Optogenetic dissection of ictal propagation in the hippocampal-entorhinal cortex structures. Nature Commun. 2016, 7:10962.
11. Dai XJ, Nie X, Liu X, Pei L, Jiang J, Peng DC, Gong HH*, Zeng XJ*, Wáng YJ, Zhan Y, Gender Differences in Regional Brain Activity in Patients with Chronic Primary Insomnia: Evidence from a Resting-State fMRI Study. J Clin Sleep Med. 2016, 12(3): 363–374.
12. Zhan Y*. Theta frequency prefrontal hippocampal driving relationship during free exploration in mice, Neuroscience, 2015, 300:554 565.
13. Amendola E, Zhan Y, Mattucci C, Castroflorio E, Calcagno E, Fuchs C, Lonetti G, Silingardi D, Farley D, Ciani E, Pizzorusso T, Giustetto M, Gross C*. Mapping pathological phenotypes in a mouse model of CDKL5 disorder. PLoS ONE. 2014, 9(5), e91613.
14. Zhan Y, Paolicelli RC, Gozzi, A, Pagani F, Gozzi A, Vyssotski A, Bifone A, Ragozzino D, and Gross C*. Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior, Nature Neurosci. 2014,17(3): 400-406.
15. Zhang X, Kendrick KM, Zhou H, Zhan Y, Feng J*. A Computational Study on Altered Theta-Gamma Coupling during Learning and Phase Coding, PLoS ONE, 2012,7(6), e36472.
16. Kendrick KM, Zhan Y, Fischer H, Nicol AU, Zhang X Feng J*. Learning alters theta amplitude, theta- gamma coupling and neuronal synchronization in inferotemporal cortex. BMC Neurosci. 2011,12:55.
17. Zhan Y*, Kendrick KM, and Feng J. Filtering Noise for Synchronised Activity in Multi-trial Electrophysiology Data using Wiener and Kalman filters. BioSystems. 2009,96:1-13.
18. Zhan Y, Halliday D, Jiang P, Liu X and Feng J*. Detecting time-dependent coherence between non-stationary electrophysiological signals-A combined statistical and time-frequency approach. J. Neurosci. Methods. 2006,156: 322-332.