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 to develop mathematical models which not only can adequately fit physiological measurements (neural and haemodynmic signals) obtained from our physiological laboratory, but also incorporate physiologically plausible constraints so that the model parameters reflect aspects of the underlying physiological processes.

Dynamic model of neural activity
This part of my research focuses on the dynamic modelling of neural signals (in terms of field potentials and multi-unit acivity (MUA), evoked or spontaneous) which reflect the mechanisms that underlie the generation of these signals. Specifically we are investigating how intracellular findings of proportionally balanced excitatory and inhibitory membrane conductances can be utilised to establish models of extracellular field potentials. We aim to establish a mathematical model of local field potentials across cortical depths. The natural extension of this model is a mathematical model of the scalp EEG. Thus the medium to long term objective of this research is the interpretation of the scalp EEG signals in terms of nerual excitation and inhibition.

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. This research will provide insight for the interpretation of fMRI BOLD signals, both positive and negatice, in terms of neural excitation and inhibition.

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

MRC J Berwick, M Jones, A Kennerley, L Boorman, C Martin, P Redgrave, Y Zheng: "The neurophysiological basis of negative BOLD signals" (07/11/06/14) £655,000

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