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Zhe (Sage) Chen, PhD

Senior Research Fellow 




Research

My primary research interests and topics are neural signal processing and neural engineering. In the past, I have research experiences in machine learning, signal processing, and wired/wireless communication. Since joining the lab, I have been collaborating with colleagues at Harvard/MIT and working on several research projects.


1. Probabilistic inference for neural state-space models using neural spike trains
2. Probabilistic point process models in assessing heartbeat dynamics and cardiovascular functions
3. Stochastic model and data-driven Markov chain Monte Carlo method for Bayesian deconvolution in mPSC time series
4. Generalized linear models in precise visual receptive field mapping
5. Estimating Functional connectivity of ensemble neurons with sparse spiking data
6. Uncovering spatial topology and structured patterns of hippocampal ensemble neuronal codes
7. Hierarchical Bayesian inference for neuroscience problems
Curriculum Vitae (available upon request)
Professional Membership and Activities
  • Senior Member, IEEE; Member of Biomedical Engineering Society (BMES), Society for Neuroscience (SfN)
  • Guest editor for Special Issue on "Signal Processing for Neural Spike Trains",  Journal of Computational Intelligence and Neuroscience, 2010.
  • Guest editor for Special Topic on "Engineering Approaches to Study Cardiovascular Physiology: Modeling, Estimation, and Signal Processing'', Frontiers in Computational Physiology and Medicine, 2011.
  • Special Session organizer, EMBC'12, August, 2012, San Diego, CA.
  • Special Session organizer, ``Computational Methods for Modeling Sleep and Anesthesia'', EMBC'11, Sep 1, 2011, Boston, MA.
  • Special Session organizer, ```Multivariate and Multimodal Analysis of Brain Signals'', ICASSP'10, March 16, 2010, Dallas, TX.
  • Special Session organizer, ``Signal Processing for Neural Spike Trains'', ICASSP'09, April 24, 2009, Taipei.

Recent Publications (since joining NSRL)

More to come....[come back to check for update]

Z. Chen, F. Kloosterman, S. Layton, M. A. Wilson, and E. N. Brown (2011). Assessing mutual information between stimulus and neural spiking activity using a transductive approach.  Journal of Neural Engineering

M. A. Phillips, A. D. Bolton, S. Amico, C. Kussius, Z. Chen, E. N. Brown, G. K. Popescu, and M. Constantine-Paton. Subunit-specific gating of NMDA receptors is independent of NR2 intracellular domain identity.  Submitted to Frontiers in Cellular and Molecular Neuroscience.

S. Kodituwakku, S. W. Lazar, P. Indic, Z. Chen, E. N. Brown and R. Barbieri (2011). Point process time-frequency analysis of dynamic breathing patterns during meditation practice. Medical & Biological Engineering & Computing.

Z. Chen, H. Shimazaki, and E. N. Brown (2011). Nonparametric copula approaches for signal processing: theory and applications. IEEE Trans. Signal Processing, under review.

Z. Chen, E. N. Brown and R. Barbieri. A unified point process probabilistic framework to assess heartbeat dynamics and cardiovascular autonomic control. Invited contribution to Frontiers in Computational Physiology and Medicine.

Z. Chen, F. Kloosterman, E. N. Brown and M. A. Wilson (2011). Uncovering hidden spatial topology represented by  hippocampal population neuronal codes. Submitted to  Journal of Computational Neuroscience.

F. Kloosterman, S. Layton,  Z. Chen, and M. A. Wilson (2011). Bayesian decoding of unsorted spike trains. Submitted to Neuron.

G. Pipa, Z. Chen, S. Neuenschwander, B. Lima, and E. N. Brown (2011). Mapping of visual receptive fields by tomographic reconstruction.Submitted to Neural Computation (joint first author)

D. Putrino, Z. Chen, S. Ghosh,  and E. N. Brown (2011). Motor cortical networks for skilled movements have dynamic properties that are related to accurate reaching.  Neural Plasticity, vol. 2011, Article ID 413543 (joint first author)

S. Layton, F. Kloosterman, Z. Chen, and M. A. Wilson (2011). Bayesian decoding of unsorted spike trains. Computational and Systems Neuroscience (COSYNE'11), Feb. 24-27, 2011, Salt Lake City, UT, USA.

Z. Chen, L. Citi, P. Purdon, E. N. Brown and R. Barbieri (2011). Instantaneous assessment of  autonomic cardiovascular control during general anesthesia (invited).  Proc.  IEEE EMBC'11, Boston, MA.
 
Z. Chen, S. Vijayan, S. Ching, G. Hale, F. Flores, M. A. Wilson, and E. N. Brown (2011).  Assessing neuronal interactions of cell assemblies during general anesthesia.   Proc.  IEEE EMBC'11, Boston, MA.

Z. Chen, P. L. Purdon, E. N. Brown, and R. Barbieri (2010). (Invited) A differential autoregressive modeling approach within a point process framework for non-stationary heartbeat intervals analysis.  Proc. EEE EMBC'10, Aug 31-Sept 4, Buenos Aires, Argentina.

Z. Chen, D. Putrino, S. Ghosh, R. Barbieri, and E. N. Brown (2011). Statistical inference for assessing neuronal interactions and functional connectivity with sparse spiking data. IEEE Trans. Neural Systems and Rehabilitation Engineering, 19(2):121--135.

Z. Chen, P. L. Purdon, E. T. Pierce, G. Harrell, J. Walsh, E. N. Brown,  and R. Barbieri (2011). Dynamic assessment of baroreflex control of heart rate during induction of propofol anesthesia using a point process method.  Annals of Biomedical Engineering, 39(1): 260--276

W. Wu, Z. Chen, S. Gao, and E. N. Brown (2011). A hierarchical Bayesian approach for learning spatio-temporal decomposition of multichannel EEG..  NeuroImage, in press.

M. Philips, A. Bolton, S. Amico, C. Kussius, Z. Chen, E. N. Brown, G. K. Popescu, and M. Constantine-Paton (2010). Subunit-specific gating of NMDA receptors is independent of NR2 intracellular domain identity.  Submitted to Frontiers in Cellular and Molecular Neuroscience

Z. Chen, E. N. Brown and R. Barbieri (2011). Characterizing nonlinear heartbeat dynamics within a point process framework. IEEE Trans. Biomedical Engineering, 57(6), 1335--1347.

Z. Chen, F. Kloosterman, M. Wilson, and E. N. Brown (2010). Variational Bayesian inference for point process generalized linear models in neural spike train analysis. Proc. IEEE ICASSP'10, March 15-19, Dallas, TX. 
 
W. Wu, Z. Chen, S. Gao and E. N. Brown (2010). Hierarchical Bayesian modeling of intertrial variability and  variational Bayesian learning of common spatial patterns from multichannel EEG. Proc. IEEE ICASSP'10, March 15-19, Dallas, TX. 

Z. Chen, R. Barbieri, and E. N. Brown (2010). State space modeling and statistical inference in neuroscience. In K. Oweiss (Ed.)  Statistical Signal Processing for Neuroscience, Academic Press (Invited contribution), Chap. 6.

Z. Chen, P. L. Purdon, E. T. Pierce, G. Harrell, J. Walsh, A. F. Salazar, C. L. Tavares, E. N. Brown,  and R. Barbieri (2009). Linear and nonlinear quantification of respiratory sinus arrhythmia during propofol general anesthesia.  Proc. IEEE 31st Annual Conf. Engineering in Medicine and Biology (EMBC'09), Sept. 2-6, Minneapolis, MN. 

Z. Chen, D. Putrino, D. Ba, S. Ghosh, R. Barbieri, and E. N. Brown (2009).  A regularized point process generalized linear model for assessing the functional connectivity in the cat motor cortex. Proc. IEEE 31st Annual Conf. Engineering in Medicine and Biology (EMBC'09), Sept. 2-6, Minneapolis, MN. . 

W. Wu, Z. Chen, S. Gao and E. N. Brown (2009). A probabilistic framework for learning robust  common spatial patterns. Proc. IEEE 31st Annual Conf. Engineering in Medicine and Biology (EMBC'09), Sept. 2-6, Minneapolis, MN. 

G. Pipa, Z. Chen, S. Neuenschwander, B. Lima, and E. N. Brown (2009). Efficient spike encoding for mapping visual receptive fields. Computational and Systems Neuroscience (COSYNE'09),  Feb. 26-Mar. 1, 2009, Salt Lake City, UT, USA.

Z. Chen, E. N. Brown and R. Barbieri (2009). Assessment of autonomic control and respiratory sinus arrhythmia using point process models of human heart beat dynamics. IEEE Trans. Biomedical Engineering.

Z. Chen, S. Vijayan, R. Barbieri, M. A. Wilson, and E. N. Brown (2008). Discrete- and continuous-time probabilistic models and inference algorithms for neuronal decoding of UP and DOWN states. 
Neural Computation.

Z. Chen, E. N. Brown, and R. Barbieri (2009). A unified  point process framework for assessing heartbeat dynamics and cardiovascular control.   Proc. IEEE 35th Northeast Bioengineering Conf., April 3-5, Cambridge, MA.

Z. Chen, P. L. Purdon, E. T. Pierce,  G. Harrell, E. N. Brown, and  R. Barbieri (2008). Assessment of baroreflex control of heart rate during anesthesia using a point process method. Proc. ICASSP'2009, Taiwan.

Z. Chen, E. N. Brown, and  R. Barbieri (2008). A point process approach to assess dynamic baroreflex gain.  
Proc. Computers in Cardiology, Sept. 14-17, Bologna, Italy.

Z. Chen, E. N. Brown, and  R. Barbieri (2008). Characterizing nonlinear heartbeat dynamics within a point process framework. 
 Proc. IEEE 30th Annual Conf. Engineering in Medicine and Biology (EMBC'08), August 20-24, Vancouver, Canada. 

Z. Chen, E. N. Brown, and R. Barbieri (2008). A study of probabilistic models for characterizing human heart beat dynamics in autonomic blockade control. 
Proc. ICASSP'2008, pp. 481--484, March 30-April 4, Las Vegas, USA. 

Z. Chen, S. Haykin, J. J. Eggermont, and S. Becker. (2007). 
Correlative Learning: A Basis for Brain and Adaptive Systems (Wiley Series on Adaptive and Learning Systems for Signal Processing, Communications and Control). New York: Wiley Interscience.
Contact
43 Vassar Street, Rm 46-6057
Dept. Brain and Cognitive Sciences
Massachusetts Institute of Technology
Cambridge, MA 02139

Email: zhechen@mit.edu
Tel: 617-324-1882 (office)

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