The University of Sheffield
Department of Psychology

Dr Ying Zheng BEng, PhD

Ying ZhengAddress
The University of Sheffield
Sheffield S10 2TP, UK
Tel: (+44) 0114 222 6511
Fax: (+44) 0114 276 6515
Email ying.zheng@sheffield.ac.uk
Room: 2-19
 

Qualifications

BEng, PhD (Sheffield)

Research Interests

The main direction of my research is the development of mathematical modelling and system identification methodologies with applications to neuro-imaging and biophysical modelling of brain functions. The main strength of our approach is to incorporate physiological constraints in our model in order to provide insight and generate hypotheses for neuroscientists working at cellular and molecular level to conduct future experiments.

Dynamic model of neural activity
This part of my research focuses on the dynamic modelling of evoked neural signals (in terms of field potentials and multi-unit acivity (MUA)) to reflect the mechanisms that underlies the generation of such signals, i.e., in terms of the excitatory and inhibitory postsynaptic potentials. The temporal characteristics of the field potentials may hold the key to our ability to decompose the neural signals into its excitatory and inhibitory components. These components in turn may provide information about the nature of the MUA which we measure at different layers of the cortex.
 

Dynamic model of neurovascular coupling
We have shown that the temporal characteristics of the cerebral blood flow (CBF) maybe the result of simultaneous blood vessel dilation and constriction. The question is: what drives the blood vessel to dilate and constrict? This part of my research is very much linked to the above neural model which we will develop. The decomposed excitatory and inhibitory components in the neural signal will form the inputs to the current neurovascular coupling model. We will investigate the neural origin of the blood vessel dilation and constriction and their relationships spatially and temporarily.

Modelling the visco-elastic properties of blood vessels
Understanding the characteristics of blood vessels during static and dynamic phases can help us understand how blood flow and volume are related during evoked stimulation, and how the circulation system works. I am currently investigating possibilities of extending our visco-elastic windkessel model to incorporate blood pressure measurements, and applying this model to study normal and diseased circulation systems.

Inverting the haemodynamic model
Within the above framework, I am also working on how to invert a haemodynamic model using the Expectation Maximisation algorithm with model parameters constrained by their priors. This part of the work is crucial in recovering neural activity from the measured BOLD signals.

Grants

EPSRC Y Zheng, S Billings, D Coca, J Martindale, J Mayhew: "System identification and signal processing for neuro imaging data analysis" (05/06-04/09) £264,000

MRC- CooP Group J Mayhew, P Redgrave, P Coffey, P Overton, N Papadakis, Y Zheng: "Optical and fMRI signal sources in brain imagery" (01/04-12/08) £452,000

NIH J Mayhew, Y Zheng: "The haemodynamic response to neural activity in brain" (09/02-08/07) £556,000

Activities and Distinctions

Key Publications

Y Zheng, Y. Pan, S. Harris, S. Billings, D. Coca, J. Berwick, M. Jones, A. Kennerley, D. Johnston, C. Martin, I. M. Devonshire, J. Mayhew. (2010)
A dynamic model of neurovascular coupling: implications for blood vessel dilation and constriction.
NeuroImage special issue: Computational models of the brain, 52(3): 1135-1147.

Zheng, Y. and Mayhew, J.E.W. (2009)
A time-invariant visco-elastic windkessel model relating blood flow and blood volume.
NeuroImage, 47: 1371-1380. A supplementary note can be downloaded from my downloads panel on the right.

Kennerley A. J., Berwick J., Martindale J., Johnston D., Zheng Y. and Mayhew J. (2009)
Refinement of optical imaging spectroscopy algorithms using concurrent BOLD and CBV fMRI.
NeuroImage, 47(4): 1608-19.

Lefebvre, V., Zheng, Y., Martin, C., Devonshire, I., Harris, S. and Mayhew, J.E.W. (2009)
A Dynamic Model of the Coupling between Pulse Stimulation and Neural Activity.
Neural Computation, 21: 2846-2868.

Wei, H., Zheng, Y., Pan, Y., Coca, D., Li, L., Mayhew, J.E.W. and Billings, S.A. (2009)
Model estimation of cerebral hemodynamics between blood flow and volume changes: a data-based modelling approach.
IEEE Trans. Biomedical Engineering, 56(6): 1606-1615.

Martindale, J., Kennerley, A., Johnston, D., Zheng, Y. and Mayhew, J. (2008)
Theory and generalization of monte carlo models of the BOLD signal source.
Magnetic Resonance in Medicine, 59(3): 607-618

ZHENG, Y., JOHNSTON, D., BERWICK, J., CHEN, D., BILLINGS, S. AND MAYHEW, J. (2005)
A three-compartment model of the hemodynamic response and oxygen delivery to brain.
NeuroImage, 28(4): 925-939.

KONG, Y., ZHENG, Y., JOHNSTON, D., MARTINDALE, J., JONES, M., BILLINGS, S. AND MAYHEW, J. (2004)
A Model of the Dynamic Relationship between Blood Flow and Volume Changes During Brain Activation.
J Cereb Blood Flow Metabol 24: 1382-1392.

HUNTER MD, GRIFFITHS TD, FARROW TFD, ZHENG Y, WILKINSON ID, HEGDE N, WOODS W, SPENCE SA, WOODRUFF PWR (2003).
A neural basis for the perception of voices in external auditory space.
Brain. 126: 161-169.

ZHENG, Y., MARTINDALE, J., JOHNSTON, D., JONES, M., BERWICK, J. AND MAYHEW, J. (2002).
A model of the hemodynamic response and oxygen delivery to brain.
NeuroImage 16: 617-637.

Zheng, Y., Johnston, D., Berwick, J. and Mayhew, J. (2001).
Signal source separation in the analysis of neural activity in brain.
Neuroimage 13: 447-58.
 

View a full list of Ying Zheng's publications.

Postgraduate Students

Research Assistant