Hi! The

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郭大庆（Daqing Guo）

 
 
Research Interests
 

Computational neuroscience, Neural data analysis, Neuromorphic engineering
 

For potential students and postdocs

We use both computational methods and techniques related to information inference to study how neuronal ensembles operate in our complicated brain. Established computational models in our lab may range from the single neuron level to local neural circuits and, sometimes, even to the whole-brain level, depending on different investigated scientific questions. To test our theory proposed in computational models, we also combine the electrophysiological experiments and record multichannel data (spike and local field potential) from the rodents, and these data will be further analyzed with advanced signal processing techniques. Graduate students, doctoral students and postdocs with some background in applied mathematics, computer science, electrical engineering or physics, interested in theoretical brain and cognitive sciences are welcome to join our lab. We will also consider those with biological or medical background given that they show proof of basic mathematical knowledge (i.e. linear algebra, calculus, in particular ordinary differential equation). Recently, we start to shift our interest to deep learning as well, and our goal is to establish the new generation of deep network using biological spiking neurons. Please direct questions to: dqguo@uestc.edu.cn
 
 
Biography
 

I am currently an associate professor at school of life science and technology, University of Electronic Science and Technology of China (UESTC). I obtained a Master degree in Computer Science from the University of Chinese Academy of Sciences, and a Ph.D. degree in Circuits and Systems from the University of Electronic Science and Technology of China. I had several years of visiting research experiences in Zhejiang University in the past, and received my postdoc training at the Computational Neuroscience Unit (Erik De Schutter’s Lab), Okinawa Institute of Science and Technology. My current research interests include computational neuroscience, neural data analysis and neuromorphic engineering.

 

EDUCATION：
University of Electronic Science and Technology of China (UESTC), Chengdu 07/2007- 06/2011
Ph.D. in Circuits and systems
Thesis: Research on Signal Transmission and Processing in Complex Neural Systems

Advisor: Prof. Chunguang Li

 

Graduate School of the Chinese Academy of Sciences (GSCAS), Peking 09/2004 – 07/2007
M.S. in Computer Science
Thesis: The Study and Improvement of Particle Swarm Optimization (Grade: excellent)
Advisor: Prof. Yingfan Li

 

University of Electronic Science and Technology of China, Chengdu 09/2000 – 07/2004
B.S. both in Automation and in Computer Science

 

 

PROFESSIONAL POSITIONS：

Associate Professor (06/2013-present, PhD supervisor since 2017)
Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, UESTC

 

Assistant Professor (10/2012-06/2013)
Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, UESTC

 

Postdoctoral Research Fellow (06/2011-09/2012)
Computational Neuroscience Unit, Okinawa Institute of Science and Technology (OIST), Japan. Supervisor: Prof. Erik De Schutter
 
 
 
Recent publications
 
  1. S Wu, Y Zhang, Y Cui, H Li, J Wang, L Guo, Y Xia, D Yao, P Xu, D Guo*. Heterogeneity of Synaptic Input Connectivity Regulates Spike-based Neuronal Avalanches, submitted to Neural Networks, 2018.
  2. Y Zhang, E Yin, F Li, Y Zhang, T Tanaka, Q Zhao, Y Cui, P Xu, D Yao, D Guo*. Two-stage frequency recognition method based on correlated component analysis for SSVEP-based BCI, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(7),1314-1323, 2018.
  3. Y Cui, S Yu, T Zhang, Y Zhang, Y Xia*, D Yao, D Guo*. Altered activity and information flow in the default mode network of pilocarpine-induced epilepsy rats, Brain Research, 2018, in press.
  4. Y Zhang, D Guo*, F Li, E Yin, Y Zhang, P Li, Q Zhao, T Tanaka, D Yao*, P Xu*, Correlated Component Analysis for Enhancing the Performance of SSVEP-Based Brain-Computer Interface, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(5), 948-956, 2018.
  5. D Guo#*, F Guo#, Y Zhang, F Li, Y Xia, P Xu, D Yao, Periodic Visual Stimulation Induces Resting-State Brain Network Reconfiguration, Frontiers in Computational Neuroscience, 12, 21, 2018.
  6. SK Sudhakar, S Hong, I Raikov, R Publio, C Lang, T Close, D Guo, M Negrello, Erik De Schutter, Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer, PLoS Computational Biology, 13(9), e1005754, 2017.
  7. D Guo*, M Perc, Y Zhang, P Xu, D Yao, Frequency-difference-dependent stochastic resonance in neural systems, Physical Review E, 96 (2), 022415, 2017.
  8. Y Zhang*, D Guo, D Yao, P Xu*. The extension of multivariate synchronization index method for ssvep-based BCI, Neurocomputing 269, 226-231, 2017.
  9. D Guo*, C Xia, S Wu, T Zhang, Y Zhang, Y Xia*, D Yao. Stochastic fluctuations of permittivity coupling regulate seizure dynamics in partial epilepsy, Science China Technological Sciences, 60(7), 995-1002, 2017.
  10. M Chen, D Guo*, Y Xia, D Yao*, Control of Absence Seizures by the Thalamic Feed-forward Inhibition, Frontiers in Computational Neuroscience, 11:31, 2017.
  11. W Jing, D Guo, Y Zhang, F Guo, PA Valdes-Sosa, Y Xia, D Yao, Reentrant Information Flow in Electrophysiological Rat Default Mode Network, Frontiers in Neuroscience, 11, 93, 2017.
  12. D Guo*, S Wu, M Chen, M Perc, Y Zhang, J Ma, Y Cui, P Xu, Y Xia, D Yao. Regulation of irregular neuronal firing by autaptic transmission, Scientific Reports, 6:26096, 2016.
  13. D Guo*, M Chen, M Perc, S Wu, C Xia, Y Zhang, P Xu, Y Xia, D Yao. Firing regulation of fast-spiking interneurons by autaptic inhibition, EPL (Europhysics letters), 114(3):30001, 2016.
  14. Y Zhang*, D Guo*, P Xu, Y Zhang, D Yao, Robust frequency recognition for SSVEP-based BCI with temporally local multivariate synchronization index, Cognitive neurodynamics 10 (6), 505-511, 2016.
  15. M Chen#, D Guo#*, M Li, T Ma, S Wu, J Ma, Y Cui, Y Xia, P Xu, D Yao*. Critical Roles of the Direct GABAergic Pallido-cortical Pathway in Controlling Absence Seizures, PLoS Computational Biology, 11(10): e1004539, 2015.
  16. Y Zhang, D Guo*, K Cheng, D Yao, P Xu*, The graph theoretical analysis of the SSVEP harmonic response networks, Cognitive Neurodynamics 9 (3), 305-315, 2015
  17. M Chen#, D Guo#*, T Wang, W Jing, Y Xia, P Xu, C Luo, PA Valdes-Sosa, D Yao*. Bidirectional Control of Absence Seizures by the Basal Ganglia: A Computational Evidence. PLoS Computational Biology, 10(3): e1003495, 2014.
  18. Y Zhang, P Xu, D Guo, D Yao*, Prediction of SSVEP-based BCI performance by the resting-state EEG network, Journal of Neural Engineering, 10 (6), 066017, 2013.
  19. D Guo, C Li, Stochastic resonance in Hodgkin–Huxley neuron induced by unreliable synaptic transmission, Journal of Theoretical Biology 308, 105-114, 2012.
  20. D Guo*, Q Wang, M Perc. Complex synchronous behavior in interneuronal networks with delayed inhibitory and fast electrical synapses, Physical Review E, 85 (6), 061905, 2012.
  21. D Guo, C Li*. Population rate coding in recurrent neuronal networks with unreliable synapses, Cognitive Neurodynamics 6 (1), 75-87, 2012.
  22. D Guo*. Inhibition of rhythmic spiking by colored noise in neural systems, Cognitive Neurodynamics 5 (3), 293-300, 2011.
  23. D Guo, C Li*, Signal propagation in feedforward neuronal networks with unreliable synapses, Journal of computational neuroscience, 30 (3), 567-587, 2011.
  24. D Guo, C Li*. Self-sustained irregular activity in 2-D small-world networks of excitatory and inhibitory neurons, IEEE Transactions on Neural Networks, 21(6):895-905, 2010.
  25. D Guo, C Li*. Stochastic and coherence resonance in feed-forward-loop neuronal network motifs, Physical Review E, 79 (5), 051921, 2009.

 

For more publications, please see my CV or Google Scholar
 

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