School of Computing and Mathematics
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- / Faculty of Natural Sciences /
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- Centre for Computer Science Research /
- Computational Neuroscience and Biomedical Engineering
Computational Neuroscience and Biomedical Engineering
We use computational modelling and analysis to understand how neural systems work and to design engineering solutions for biomedical problems that involve abnormal or lacking neural control.
Neural systems control the behaviour of animals and provide the ability for adaptive behaviour. Understanding and modelling how neural systems work and how they control behaviour is a major scientific challenge. Over a billion pound funding has been recently committed by the governments of the US, EU and Japan to support fundamental neuroscience and computational modelling of neural systems.
Our work covers several strands of research in this area. We aim to build physiologically realistic models of small neural systems to understand how the functionality of these systems emerges through interactions of neurons in response to synaptic inputs and neuromodulation from higher neural centres. We work on the building of biologically inspired models of neural systems that can control virtual or real muscles and deliver physiologically meaningful behaviours through these actuators. We also work on developing biologically inspired controllers for robots, on tracing and modelling growth of neurons and biological tissues, and on the analysis of bio-imaging data.
We generate some of the data in our neuroscience and physiology labs and we also collaborate with other wet-lab groups who provide us data.
Our research has a huge potential for impact in biomedical context and also in terms of innovative bio-inspired solutions to practical engineering problems. For example, our work may lead to novel bio-inspired controllers and sensors for artificial limbs that connect to nerves and muscles to deliver sensation and to allow direct neuro-muscular control. Our work on small biological neural systems may pave the way towards novel neuro-implants that can restore the functionality of diseased or damaged internal organs.
- Dr Charles Day, Lecturer
- Professor Peter Andras
- Dr Charles Day, Lecturer
- Dr Theocharis Kyriacou, Lecturer
- Dr KP Lam, Lecturer
- Dr Shailesh Naire, Lecturer
- Mr David Collins, Teaching Fellow
- Dr Michel Mickael, Research Fellow
- Dr Ed Chadwick, Lecturer (Institute of Science and Technology in Medicine)
- Dr Stas Glazewski, Lecturer (School of Life Sciences)
- John Butcher, Research Associate (School of Life Sciences)
- Dr Dimitra Blana, Research Associate (Institute of Science and Technology in Medicine)
- Dr Jannetta Steyn
- Designing and validating novel voltage sensitive dyes for neuroscience research, Leverhulme Trust 2015-17, GBP 178K - Prof Peter Andras (PI, Keele University), Prof Andrew Benniston (CI, Newcastle University).
- Restoration of normal activity in damaged neural systems using multi-electrode arrays and FPGA neurons, EPSRC (eFuturesXD), 2013-2014, GBP 60k – Prof Peter Andras (PI, Newcastle University).
- Development of novel voltage-sensitive dyes for neuroimaging, EPSRC (IAA), 2012-2013, GBP 30k – Prof Peter Andras (PI, Newcastle University).
- Grid-enabled neuroscience, MRC, 2002-2006, GBP 168k – Prof Peter Andras (PI; Newcastle University).
- Simulation of shoulder and upper limb musculoskeletal dynamics, collaboration with Case Western Reserve University, NIH funded – Dr Ed Chadwick (Keele PI), Dr Dimitra Blana (Co-I).
- Real-time human hand model for prosthesis control, collaboration with Rehabilitation Institute of Chicago, NIH funded – Dr Ed Chadwick (Keele PI), Dr Dimitra Blana (Co-I).
- Ms Katy Dempsey (supervisors: Dr KP Lam, Mr Dave Collins)
- Mr George Joseph (supervisors: Dr Theocharis Kyriacou, XXXX)
- Ms Filipa dos Santos (supervisors: Prof Peter Andras, Dr Charles Day)
- Ms Shaima Jabbar (supervisors: Dr Ed Chadwick, Dr Charles Day)
- Dr Jannetta Steyn (supervisor: Prof Peter Andras; Newcastle University 2015)
- Mr David Fourie – MPhil (supervisor: Prof Peter Andras; Newcastle University, 2008)
- Dr Wolfgang Stein (Illinois State University)
- Professor Andrew Benniston (Newcastle University)
- Professor George Kemenes (University of Sussex)
- Dr Ildiko Kemenes (University of Sussex)
- Professor Robert Kozma (Memphis University)
- Professor Peter Erdi (Kalamazzoo College)
- Professor Alan Roberts (University of Bristol)
- Professor Allen Selverston (University of California at San Diego)
- Professor Thomas Nowotny (University of Sussex)
- Professor Alex Yakovlev (Newcastle University)
- Dr Patrick Degenaar (Newcastle University)
- Dr Terrence Mak (The Chinese University of Hong Kong)
- Dr Carmen Wellman (University of Cologne)
- Professor Sylvie Renaud (University of Bordeaux)
- Dr Andras Lõrincz (Eötvös Lóránd University – Budapest)
- Professor Robert Kirsch (Case Western Reserve University, USA)
- Professor Ton van den Bogert (Cleveland State University, USA)
- Dr Wendy Murray (Rehabilitation Institute of Chicago, USA)
Andras, PE (2018) Random Projection Neural Network Approximation. 2017 International Joint Conference on Neural Networks (IJCNN 2017).
Andras, PE (2018) High-Dimensional Function Approximation with Neural Networks for Large Volumes of Data. IEEE Transactions on Neural Networks and Learning Systems, 29 (2). pp. 500-508. ISSN 2162-237X
Dos Santos, F and Andras, PE and Lam, KP (2017) Towards an Accurate Identification of Pyloric Neuron Activity with VSDi. In: 26th International Conference on Artificial Neural Networks, 11-15 September 2017, Alghero, Sardinia, Italy.
Scardapane, S and Butcher, JB and Bianchi, F and Malik, ZK (2017) Advances in Biologically Inspired Reservoir Computing. Cognitive Computation. ISSN 1866-9956 Item availability may be restricted.
Day, CR and Jabbar, SI and Heinz, N and Chadwick, EK (2016) Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images. In: International Joint Conference on Neural Networks, 25-29 Jul 2016, Vancouver.
Steyn, JS and Andras, PE (2016) Analysis of the dynamics of temporal relationships of neural activities using optical imaging data. Journal of Computational Neuroscience. ISSN 1573-6873
Fisher, JM and Hammerla, NY and Rochester, L and Andras, P and Walker, RW (2016) Body-Worn Sensors in Parkinson's Disease: Evaluating Their Acceptability to Patients. Telemedicine and e-Health, 22 (1). 63 -69. ISSN 1556-3669
Hammerla, N, Fisher, J, Andras, P, Rochester, L, Walker, R, Ploetz, T (2015). PD disease state assessment in naturalistic environments using deep learning. Accepted for publication in the Proceedings of the AAAI – 2015.
Chadwick EK, Blana D, Kirsch RF, van den Bogert AJ. 2014. Real-Time Simulation of Three-Dimensional Shoulder Girdle and Arm Dynamics. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 61(7), 1947-1956.
Cutti AG and Chadwick EK. 2014. Shoulder biomechanics and the success of translational research. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, vol. 52(3), 205-210.
Bai, D, Benniston, AC, Clift, S, Baisch, U, Steyn, J, Everitt, N, Andras, P (2014). Low molecular weight Neutral Boron Dipyrromethene (Bodipy) dyads for fluorescence-based neural imaging. Journal of Molecular Structure, 1065-1066: 10-15.
Smith WA, Lam K-P, Dempsey KP, Mazzocchi-Jones D, Richardson JB, Yang Y. 2014. Label free cell tracking in 3-D tissue engineering constructs with high resolution imaging. DYNAMICS AND FLUCTUATIONS IN BIOMEDICAL PHOTONICS XI (vol. 8942).
Dempsey KP, Richardson JB, Lam KP. 2014. On measuring cell confluence in phase contrast microscopy.IMAGING, MANIPULATION, AND ANALYSIS OF BIOMOLECULES, CELLS, AND TISSUES XII (vol. 8947)
Marchi J, Blana D, Chadwick EK. 2014. Glenohumeral stability during a hand-positioning task in previously injured shoulders. Med Biol Eng Comput, vol. 52(3), 251-256.
Bolsterlee B, Veeger DH, Chadwick EK. 2013. Clinical applications of musculoskeletal modelling for the shoulder and upper limb. Med Biol Eng Comput, vol. 51(9), 953-963.
Blana D, Hincapie JG, Chadwick EK, Kirsch RF. 2013. Selection of muscle and nerve-cuff electrodes for neuroprostheses using customizable musculoskeletal model. J Rehabil Res Dev, vol. 50(3), 395-408.
Lam K, Smith WA, Collins DJ, Richardson JB. 2013. On 2.5D Surface Reconstruction of Cell Cultures. In G. Ramponi, S. Loncaric & A. Carini (Eds.). University of Zagreb, Croatia: IEEE Signal Processing Society.
Lam K and Collins DJ. 2013. FACE: Fractal Analysis in Cell Engineering. In K. Elleithy (Ed.). Innovations and Advances in Computer, Information, Systems Sciences, and Engineering Lecture Notes in Electrical Engineering Volume 152, 2013, pp 1151-1164 (vol. 152, pp. 1151-1164). USA: Springer New York.
Lam KP, Dempsy KP, Smith WA, Wright KT, Masri WE, Richardson JB, IEEE. 2013. A Computational Approach to Quantifying Axon Regeneration in the Presence of Mesenchymal Stem Cells (MSCs). 2013 6TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER) (pp. 1541-1544)
Städele, C, Andras, P, Stein, W (2012). Simultaneous measurement of membrane potential changes in multiple pattern generating neurons using voltage sensitive dye imaging. Journal of Neuroscience Methods, 203: 78-88.
Kyriacou T. (2012) Using an Evolutionary Algorithm to Determine the Parameters of a Biologically Inspired Model of Head Direction Cells. Journal of Computational Neuroscience, 32:281-295.
Lam K, Smith, WA, Collins, DJ. 2012. FORTHCOMING: Scalable 2-1/2D Reconstruction of Cell Objects.International Journal on Industrial Electronics, Technology and Automation.
Hidalgo-Bastida LA, Thirunavukkarasu S, Griffiths S, Cartmell SH, Naire S. 2012. Modeling and design of optimal flow perfusion bioreactors for tissue engineering applications. BIOTECHNOLOGY AND BIOENGINEERING, vol. 109(4), 1095-1099.