Professor Roman Borisyuk
Profiles

Professor Roman Borisyuk

Professor of Computational Neuroscience

School of Computing, Electronics and Mathematics (Faculty of Science and Engineering)

  • A 224, Portland Sq, Drake Circus, Plymouth, Devon, PL4 8AA
  • +44 1752 584949

Role

Professor of Computational Neuroscience
School of Computing and Mathematics
Centre for Robotics and Neural Systems

Qualifications

Diploma of Higher Education in Mathematics (equivalent to MSc) from Moscow State University, USSR, 1973

Candidate of Physical and Mathematical Sciences in Biophysics and Mathematical Biology (equivalent to PhD) from the Institute of Biological Physics of the USSR Academy of Sciences, 1984

Doctor of Physical and Mathematical Sciences in Biophysics and Mathematical Biology (equivalent to DSc) from the Institute of Experimental and Theoretical Biophysics of the Russian Academy of Sciences, 1996.

BACKGROUND

I have been working in the field of neural networks, mathematical and computational neuroscience since 1973. The main direction of my research has been related to modelling the functional behaviour of structures in the central nervous system. I was among the first in the world to apply new mathematical tools – multidimensional interacting Markovian processes and fields - to the analysis of dynamical regimes in stochastic neural networks.

I was engaged at Moscow in pioneer research concerned with developing numerical algorithms to investigate the bifurcations of steady states and limit cycles in nonlinear dynamical systems under parameter variation. These investigations showed that cooperative effects like physical phase-transitions and synchronisation phenomena occur normally in biological neural networks despite a very chaotic spike activity of single neurons. In addition, metastable states of neural networks were proved to be useful to model short-term memory in a series of theoretical and simulation works.

RESEARCH GOALS

I am currently study neurodynamics and synchronisation in neural networks with various types of elements and architectures. The rhythm and waves in the brain are of special interest. The fulfilment of this program will form a unified approach to the modelling of various cognitive functions such as attention, memory, and decision making.

Another important direction of my research relates to the “structure – function” problem. In collaboration with neurobiologists from Universities of Bristol and St Andrews we are developing biologically realistic detailed anatomical and physiological models of the tadpole nervous system which are able to execute information processing and control swimming behaviour.

Professional membership

1990-2000 Member of International Neural Network Society
2000-date Member of Society for Industrial and Applied Mathematics (SIAM)
1990-date Member of the Russian Neural Network Society
2003-date Memeber of Theoretical (Mathematical) Neuroscience Network (supported by Leverhulme Trust, EPSRC)

Roles on external bodies

1990-date Member of Editorial Board of "Neural Networks" - the official Journal of International Neural Network Society (Elsevier) 
2005-date Member of Editorial Board of  "Cognitive Neurodynamics" journal (Springer)
2002-2012 Member of Editorial Board of International Journal of Integrative Neuroscience (Imperial College Press)
2006-date Member of Scientific Council, European Complex Systems Society
1990-2010 Member of Executive Board of the Russian Neural Network Society
2003-date Member of Scientific Panels, European Commission, Brussels
2010-date Member of EPSRC college
1985-96 Member of Scientific Council of Institute of Mathematical Problems of Biology of the Russian Academy of Sciences
Scholarship from NSF, Invited Visiting Professor, Mathematical Biosciences Institute, Ohio State University, Columbus, Ohio, USA, April-June 2003

Teaching interests

Mathematical and Computational Neuroscience
Mathematical Modelling
Dynamical Systems
Bifurcation Theory

Research interests

CURRENT PROJECTS 

Study of tadpole nervous system
In collaboration with University of Bristol and University of St Andrews. Supported by BBSRC grants 2009,-2012, 2014-2017.

Borisyuk R.
, Al Azad A.K., Conte D., Roberts A., Soffe S.R. (2011) Modeling the connectome of a simple spinal cord. Front Neuroinform. 2011;5:20
Li W.-C., Cooke T., Sautois B., Soffe S., Borisyuk R., Roberts A. (2007) Axon and dendrite geography predict the specificity of synaptic connections in a functioning spinal cord network. Neural Development, 2:17
Roberts A., Conte D., Hull M., Merrison R., Al Azad A.K., Buhl E., Borisyuk R., Soffe S.R. (2014) Building the early nervous system: simple rules control development of a vertebrate connectome generating behaviour. Journal of Neuroscience

Mathematical and computational modelling of the Basal Ganglia in norm and Parkinson disease including models of Deep Brain Stimulation
In collaboration with Imperial College London; Freiburg University; Toronto University; and Institute of Mathematics of the Ukrainian Academy of Sciences. Supported by the Faculty of Science and Technology studentship (2011-2014).

Merrison-Hort RJ, Yousif N, Njap F, Hofmann UG, Burylko O, Borisyuk R. (2013) An interactive channel model of the Basal Ganglia: Bifurcation analysis under healthy and Parkinsonian conditions. J Math Neurosci. 3(1):14
Yousif N, Borisyuk R., Pavese N, Nandi D, Bain P. (2012) Spatiotemporal visualization of deep brain stimulation-induced effects in the subthalamic nucleus. Eur J Neurosci., 36(2):2252-9

Synchronization based modelling of cognitive functions
In collaboration with Institute of Mathematical Problems in Biology, Russian Academy of Science, Frankfurt Institute for Advanced Studies, Max-Plank-Institute for Brain Research, Humboldt University. Supported by the University of Plymouth studentship, EU CogNovo project, 2014-2018 (Project Leader – Prof. Sue Denham)

Borisyuk R., Chik D., Kazanovich Y., da Silva Gomes J. (2013) Spiking neural network model for memorizing sequences with forward and backward recall. Bio Systems; 112(3):214-23.
Chik D, Borisyuk R, Kazanovich Y. (2009) Selective attention model with spiking elements. Neural Networks, 22:890-900
Borisyuk R., Kazanovich Y., Chik D., Tikhanoff V. and Cangelosi A. (2009). A neural model of selective attention and object segmentation in the visual scene: An approach based on partial synchronization and star-like architecture of connections. Neural Networks, 22(5-6):707-19
Borisyuk R., Chik D, Kazanovich Y. (2009). Visual perception of ambiguous figures: synchronization based neural models. Biological Cybernetics,100(6):491- 504

Development of new methods for spike train analysis
In collaboration with SoC&M (Dr Liz Stuart) and University of Newcastle. Supported by EPSRC CARMEN grant

Masud MS, Borisyuk R. (2011) Statistical technique for analysing functional connectivity of multiple spike trains. J Neurosci Methods. 196(1):201-19.
Somerville J, Stuart L, Sernagor E, Borisyuk R. (2010) iRaster: a novel information visualization tool to explore spatiotemporal patterns in multiple spike trains. J Neurosci Methods. 194(1):158-71

Complex nonlinear dynamics and bifurcations of coupled oscillators
In collaboration with Institute of Mathematical Problems in Biology, Russian Academy of Science and Institute of Mathematics, Ukrainian Academy of Science; Supported by the Travel grants from the Royal Society (2010) and Plymouth University (2012).

Kazanovich Y, Burylko O., Borisyuk R. (2013) Competition for synchronization in a phase oscillator system. PhysicaD, 261, 114-124.
Burylko O., Kazanovich Y., Borisyuk R. (2012) Bifurcations in phase oscillator networks with a central element. PhysicaD, 241 (12), 1072-1089.