Prof Kevin Gurney (ABRG Co-director)

Contact

Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.

Tel: +44 (0) 114 222 6566

Fax: +44 (0) 114 276 6515 (shared with department)

Email: k.gurney/at/sheffield.ac.uk

Summary

I am a Professor of Computational Neuroscience at Sheffield and co-Director of the ABRG. My formal education and research experience have spanned a variety of disciplines including mathematical physics, digital systems, neural networks, experimental psychology, and computational neuroscience. Over the last decade I have specialised in the �action selection� problem and its solution in the basal ganglia and associated brain circuits. Recently this has expanded to include an investigation of sensorimotor loops controlling visual gaze. I am also interested in plasticity in basal ganglia and its role in developing new action repertoires. I have worked on models at many levels of description - from single neurons to brains systems and robots; each level of description has a role to play in our understanding of the brain. I am a firm believer in data sharing, and the need to develop powerful and widely used tools for building models in neuroscience.

Research Interests

• Computational models at multiple levels of description
• Specific brain areas/functions include basal ganglia and action selection, active vision, and intrinsically motivated learning
• Automated parameter optimization methods for conductance-based models
• Neuroinformatics: Middle-ware, high-level model description languages
• Principal Investigator on the REVERB Project
• Co-Investigator on the CARMEN e-Science Project
• Co-Investigator on the IM-CLeVeR Project

Web resources

• Computational Neuroscience lecture notes
• Best-selling Introductory book on neural networks
• InsideTrak An interactive art-meets-science exhibition of active vision
• Direct link to YouTube video of InsideTrak

Forthcoming work

• Lepora N, Blomeley C, Hoyland D, Bracci P, Overton P and Gurney K (2011), A simple method for characterizing passive and active neuronal properties applied to striatal neurons, European Journal of Neuroscience, in press.

Peer-reviewed print articles

2011

• Lepora N, Fox C, Evans M, Mitchinson B, Motiwala A, Sullivan J, Pearson M, Welsby J, Pipe T, Gurney K and Prescott T (2011), A general classifier of whisker data using stationary naïve Bayes: Application to BIOTACT robots, Springer LNCS proceedings of Towards Autonomous Robotic Systems (TAROS), 6856/2011:13-23.
• Lepora N, Overton P and Gurney K (2011), Efficient fitting of conductance-based model neurons from somatic current clamp, Journal of Computational Neuroscience.
• Tom Stafford and Kevin N. Gurney (2011), Additive factors do not imply discrete processing stages: a worked example using models of the Stroop task, Frontiers in Psychology, 2:287.
• Tom Stafford, Leanne Ingram and Kevin N. Gurney (2011), Pieron’s Law holds during Stroop conflict: insights into the architecture of decision making, Cognitive Science 35, 1553–1566.

2010

• Ben Mitchinson, Tak-Shing Chan, Jon Chambers, Martin Pearson, Mark Humphries, Charles Fox, Kevin Gurney, Tony J. Prescott (2010), BRAHMS: Novel middleware for integrated systems computation, Advanced Engineering Informatics, 24(1):49-61.
• Lepora N, Pearson M, Mitchinson B, Evans M, Fox C, Pipe T, Gurney K and Prescott T (2010), Naive Bayes novelty detection in a whiskered moving robot, IEEE procedings of International Conference on Robotics and Biomimetics (ROBIO 2010).
• Stewart, R.D. and K.N. Gurney (2010), Spiking neural network simulation: memory-optimal synaptic event scheduling, Journal of Computational Neuroscience, 30(3):721-728.
• Humphries, M D, Wood, R. and Gurney, K. (2010), Reconstructing the three dimensional GABAergic microcircuit of the striatum, PLoS Computational Biology, 6:e1001011. [Code]
• Lepora, N, M Evans, C. Fox, M.E. Diamond, K.N. Gurney and T.J. Prescott (2010), Naive Bayes texture classification applied to whisker data from a moving robot, IEEE World Congress on Computational Intelligence.

2009

• Stafford, T., Gurney, K.N. & Ingram, L. (2009), Pieron’s Law holds in conditions of response conflict, Proceedings of the 31th Annual Conference of the Cognitive Science Society, (pp 2238-2243, eds N.A. Taatgen & H. van Rijn). Cognitive Science Society.
• Humphries, M. D., Lepora, N., Wood, R. and Gurney, K. (2009), Capturing dopaminergic modulation and bimodal membrane behaviour of striatal medium spiny neurons in accurate, reduced models, Frontiers in Computational Neuroscience, 3:26. [Code]
• Gurney, K.N. (2009), Computational Models in Neuroscience: From membranes to Robots, Computational Modelling in Behavioural Neuroscience: Closing the gap between neurophysiology and behaviour, 107-136, Advances in Behavioural Brain Science. East Sussex, UK: Psychology Press.
• Gurney, K., A. Hussain, J. Chambers, and R. Abdullah (2009), Controlled and automatic processing in animals and machines with application to autonomous vehicle control, Lecture Notes in Computer Science, 5768 LNCS, 198-207, Springer.
• Humphries, M. D., Wood, R. and Gurney, K. (2009), Dopamine-modulated dynamic cell assemblies generated by the GABAergic striatal microcircuit, Neural Networks, 22:1174-1188. [Code]
• Gurney, K.N. (2009), Reverse Engineering the Vertebrate Brain: Methodological Principles for a Biologically Grounded Programme of Cognitive Modelling, Cognitive Computation, 1 (1) 29-41.

2008

• Humphries, M. D. & Gurney, K. (2008), Network `small-world-ness': a quantitative method for determining canonical network equivalences, PLoS One, 3:e0002051.
• Hussain, A., K.N. Gurney, R. Abdullah, and J.M. Chambers (2008), Emergent Common Functional Principles in Control Theory and the Vertebrate Brain: A Case Study with Autonomous Vehicle Control, Proceedings of the 18th international conference on Artificial Neural Networks, Part II, 949-958, Springer.
• Redgrave, P., K.N. Gurney, and J. Reynolds (2008), What is reinforced by phasic dopamine signals?, Brain Research Reviews, 58, (2), 322-339.

2007

• Humphries, M. D., Gurney, K. & Prescott, T. J. (2007), Is there a brainstem substrate for action selection?, Philosophical Transactions of the Royal Society B: Biological Sciences, 362(1485):1627-1639. [Code]
• Pearson M. J., Pipe A. G., Mitchinson B., Gurney K., Melhuish C., Gilhespy I., & Nibouche M. (2007), Implementing spiking neural networks for real-time signal-processing and control applications: A model-validated FPGA approach, IEEE Transactions on Neural Networks, 18(5):1472-1487.
• Humphries, M. D. & Gurney, K. (2007), Solutions methods for simple model neurons, Neural Computation, 19:3216-3225. [Code]
• Bogacz R, Gurney K (2007), The basal ganglia and cortex implement optimal decision making between alternative actions. 19:442-477., Neural Computation, 19:442-477.
• Humphries, M. D., & K.N.Gurney (2007), A means to an end: validating models by fitting experimental data, Neurocomputing, 70:1892-1896. [Code]
• Stafford, T. & Gurney, K.N. (2007), Biologically constrained action selection improves cognitive control in a model of the Stroop task, Philosophical Transactions of the Royal Society B: Biological Sciences, 362 (1485), 1671-1684.

2006

• Humphries, M. D., Gurney, K. & Prescott, T. J. (2006), The brainstem reticular formation is a small-world, not scale-free, network, Proceedings of the Royal Society B: Biological Sciences, 273:503-511. [Code]
• Humphries, M. D., Stewart, R. D. & Gurney, K. (2006), A physiologically plausible model of action selection and oscillatory activity in the basal ganglia, Journal of Neuroscience, 26(50):12921-42. [Code]
• Gurney K.N, Prescott AJ, Redgrave P (2006), A Theoretical Treatment of Basal Banglia Function, Nova Science Pub Inc., (Bezard E, ed).
• Prescott, T. J., Montes-Gonzalez, F., Gurney, K., Humphries, M. D. and Redgrave, P. (2006), A robot model of the basal ganglia: Behavior and intrinsic processing, Neural Networks, 19:31-61.
• Redgrave, P. & Gurney, K. (2006), The short-latency dopamine signal: a role in discovering novel actions? , Nature Reviews Neuroscience, 7:967-975..
• Stafford, T. & Gurney, K.N. (2006), Computational Models of Cognition, An Introduction to Cognitive Psychology: Processes and Disorders. Second Edition, Ed. David Groome. Hove, UK: Psychology Press..
• Humphries, M.D, and K.N. Gurney (2006), A means to an end: validating models by fitting experimental data, Neurocomputing , 20 (10, 1892-1896.
• Gurney K.N. (2006), Neural networks for perceptual processing: from simulation tools to theories. , Philos Trans R Soc Lond B Biol Sci , 362:339-353..

2005

• Stafford, T, & Gurney, K. (2005), The basal ganglia as the selection mechanism in a cognitive task, Modelling Natural Action Selection, J. J. Bryson, T. J. Prescott & A. Seth (Eds.), pp. 77-83, AISB Press.
• Humphries, M. D., Gurney, K. & Prescott, T. J. (2005), Is there an integrative center in the vertebrate brain-stem? A robotic evaluation of a model of the reticular formation viewed as an action selection device, Adaptive Behaviour, 13:97-113.
• Chambers, J. M., Gurney, K., Humphries, M. & Prescott, T. (2005), Mechanisms of choice in the primate brain: a quick look at positive feedback, Modelling Natural Action Selection, J. J. Bryson, T. J. Prescott & A. Seth, pp. 45-52, AISB Press..
• Humphries, M., Gurney, K. & Prescott, T. (2005), Action selection in a macroscopic model of the brainstem reticular formation, Modelling Natural Action Selection, J. J. Bryson, T. J. Prescott & A. Seth, pp. 61-68, AISB Press.
• Stafford, T., and K.N. Gurney (2005), The role of response mechanisms in determining reaction time performance: Pieron's law revisited, Psychon Bull Rev, 11, no. 6: 975-987.
• Pearson M, Gilhespy I, Gurney K, Melhuish C, Mitchinson B, Nibouche M, Pipe A (2005), A real-time, FPGA based, biologically plausible neural network processor, Proceedings of International Conference on Artificial Neural Networks (ICANN), LNCS 3697, pp. 1021-1026, Springer-Verlag: Berlin.

2004

• Wood, R., Gurney, K. N. & Wilson, C. J. (2004), A novel parameter optimisation technique for compartmental models applied to a model of a striatal medium spiny neuron, Neurocomputing, 58-60:1109-1116.
• Gurney, K., Prescott, T.J., Wickens, J. R. & Redgrave, P. (2004), Computational models of the basal ganglia: from robots to membranes, Trends in Neurosciences, 27:453-459.
• Gurney, K., Humphries, M., Wood, R., Prescott, T.J. & Redgrave, P. (2004), Testing computational hypotheses of brain systems function: a case study with the basal ganglia, Network: Computation in Neural Systems, 15:263-290. [Code]
• Stafford, T. & Gurney, K. N. (2004), The role of response mechanisms in determining reaction time performance: Pieron’s Law revisited, Psychonomic Bulletin & Review, 11:975-987.
• Mitchinson, B. M., Gurney, K. N., Redgrave, P., Melhuish, C., Pipe, A. G., Pearson, M., Gilhespy, I. & Prescott, T. J. (2004), Empirically inspired simulated electro-mechanical model of the rat mystacial follicle-sinus-complex, Proceedings of the Royal Society B: Biological Sciences, 271:2509-2516.
• Gurney, K. N. & Overton, P. G. (2004), A model of short and long range selective processing in neostriatum, Neurocomputing, 58-60:555-562.

2003

• Prescott, T. J., Gurney, K., and Redgrave, P. (2003), Basal Ganglia, The Handbook of Brain Theory and Neural Networks, M. A. Arbib (Ed.), 2nd Edition .
• Redgrave, P., Prescott, T.J. & Gurney, K. (2003), Selection and the basal ganglia: A role for dopamine, Basal Ganglia VI,, Graybiel, A.M and DeLong, M. (Eds.). New York: Kluwer.
• Girard B, Cuzin V, Guillot A, Gurney KN, Prescott TJ (2003), Comparison of a “winner-takes-all” and a vertebrate inspired model of action selection embedded in a Lego Mindstorms robot , Journal of Integrative Neuroscience , 2:179-200.
• Humphries, M. D., Prescott, T. J. & Gurney, K. N. (2003), The interaction of recurrent axon collateral networks in the basal ganglia, Artifical Neural Networks and Neural Information Processing, O. Kaynak, E. Alpaydin, E. Oja & L. Xu (Eds.), ICANN/ICONIP 2003 (LNCS 2714) pp. 797-804, Berlin: Springer-Verlag.

2002

• Prescott, T. J., Gurney, K., Montes-Gonzalez, F., Humphries, M. and Redgrave, P. (2002), The robot basal ganglia: Action selection by an embedded model of the basal ganglia, Basal Ganglia VII, L. F. B. Nicholson and R. Faulls (Eds.) New York: Plenum Press.
• Prescott, T.J., K.N. Gurney, and P. Redgrave (2002), The Basal Ganglia, The Handbook of Brain Theory and Neural Networks. MIT Press..
• Humphries, M. D. & Gurney, K. N. (2002), The role of intra-thalamic and thalamocortical circuits in action selection, Network: Computation in Neural Systems, 13:131-156. [Code]
• Girard, B., Cuzin, V., Guillot, A., Gurney, K., and Prescott, T.J. (2002), Comparing a brain-inspired robot action selection mechanism with winner-takes-all, From Animals to Animats 7: Proceedings of the Seventh International Conference on Simulation of Adaptive Behaviour, MIT Press, Cambridge, MA, pp. 75–84.

2001

• Gurney, K., Redgrave, P. & Prescott, T.J. (2001), A computational model of action selection in the basal ganglia I. A new functional anatomy, Biological Cybernetics, 84:401-410.
• Humphries, M. D. & Gurney, K. N. (2001), A pulsed neural network model of bursting in the basal ganglia, Neural Networks, 14:845-863.
• Gurney, K. N. (2001), Information processing in dendrites II. Information theoretic complexity, Neural Networks, 14:1005-1022.
• Gurney, K. N. (2001), Information processing in dendrites I. Input pattern generalisation, Neural Networks, 14:991-1004.
• Gurney, K., Redgrave, P. & Prescott, T.J. (2001), A computational model of action selection in the basal ganglia II. Analysis and simulation of behaviour, Biological Cybernetics, 84:411-423.

2000

• Montes Gonzalez, F. Prescott, T.J., Gurney, K. Humphries, M., & Redgrave, P. (2000), An embodied model of action selection mechanisms in the vertebrate brain, From Animals to Animats 6: Proceedings of the Sixth International Conference on Simulation of Adaptive Behaviour, J-A. Meyer, A. Berthoz, D. Floreano, H. Roitblat, & S. W. Wilson (Eds.), Cambridge MA: MIT Press.

1999

• Groome, D., H. Dewart, A. Esgate, K.N. Gurney, and N. Towell (1999), Computational Models of Cognition, An Introduction to Cognitive Psychology: Processes and Disorders, 261-291. Psychology Press, 1st Ed..
• Redgrave, P., Prescott, T.J. & Gurney, K. (1999), Is the short latency dopamine burst too short to signal reinforcement error?, Trends in Neurosciences, 22:146-151.
• Wright, M.J., and K.N. Gurney (1999), Visual discrimination of direction changes based upon two types of angular motion, Vision Research, 39, 1927-1941.
• Redgrave, P., Prescott, T.J. & Gurney, K. (1999), The basal ganglia: a vertebrate solution to the selection problem?, Neuroscience, 89:1009-1023.
• Prescott, T.J., Redgrave, P., & Gurney, K. (1999), Layered control architectures in robots and vertebrates, Adaptive Behavior, 7:99-127.

1998

• Gurney, K., Prescott, T.J., & Redgrave, P. (1998), The basal ganglia viewed as an action selection device, The Proceedings of the International Conference on Artificial Neural Networks, Springer-Verlag: Berlin, pp1033-1038.

1997

• Wright, M.J., and K.N. Gurney (1997), Coherence and motion transparency in rigid and non-rigid plaids, Perception , 553-567.
• Gurney, K.N. (1997), An Introduction to Neural Networks, UCL Press (Taylor and Francis group)..

1996

• Gurney, K.N., and M.J. Wright (1996), A model for the spatial integration and differentiation of velocity signals, Vision Research, 36: 2939-2955.
• Gurney, K.N., and M.J. Wright (1996), A biologically plausible model of early visual motion processing II: Psychophysical application, Biological Cybernetics, 74: 349-358.
• Gurney, K.N., and M.J. Wright (1996), A biologically plausible model of early visual motion processing I: Theory and implementation, Biological Cybernetics, 74: 339-348..
• Gurney, K.N., and M.J. Wright (1996), Rotation and radial motion thresholds support a 2-stage model of differential motion analysis, Perception, 25: 5-26.

1995

• Wright, M.J., and K.N. Gurney (1995), From spatiotemporal tuning to velocity analysis, Basic and Clinical Perspectives on Vision Research. Plenum Press..
• Wright, M.J., and K.N. Gurney (1995), The discrimination of dynamic orientation changes in gratings and plaids, Perception , 24: 665-679.

1994

• Hui, T., P. Morgan, H. Bolouri, and K.N. Gurney (1994), VLSI Implementation of a digital neural network with Reward-Penalty learning, In VLSI for Neural Networks and Artificial Intelligence, Plenum Press..
• Bolouri, H., P. Morgan, and K.N. Gurney (1994), Design, manufacture and evaluation of a scalable high-performance neural system, Electronics Letters, 30: 426..

1992

• Gurney, K.N. (1992), Training Recurrent Nets of Hardware realisable Sigma-Pi Units, International Journal of Neural Systems, 3: 31-42.
• Wright, M.J., and K.N. Gurney (1992), Dependence of stereomotion on the orientation of spatial frequency components, Journal of Physiological and Ophthalmic Optics Journal of Physiological and Ophthalmic Optics, 12: 264-268.
• Gurney, K.N. (1992), Weighted Nodes and RAM-Nets: A Unified Approach, Journal of Intelligent Systems, 2: 155-186.
• Gurney, K.N. (1992), Training Nets of Stochastic Units using System Identification, Neural Networks, 6: 133-145.
• Gurney, K.N. (1992), Training Nets of Hardware Realisable Sigma-Pi Units, Neural Networks, 5: 289-303.
• Gurney, K.N., and M.J. Wright (1992), A self-organising neural network model of image velocity encoding, Biological Cybernetics, 68: 173-181.
• Hui, T., P. Morgan, K.N. Gurney, and H. Bolouri (1992), A cascadable 2048-neuron VLSI artificial network with on-board learning, ICANN , Aleksander and Taylor, editors, Artificial Neural Networks 2.
• Wright, M.J., and K.N. Gurney (1992), Lower threshold of motion for one- and two- dimensional patterns in central and peripheral vision, Vision Research, 32: 121-134.
• Gurney, K.N., and M.J. Wright (1992), Digital Nets and intelligent systems, Journal of Intelligent Systems, 2, 1-10.

Other work

• Javier A. Caballero, Nathan Lepora and Kevin N. Gurney (2011), Sequential tests and biologically grounded multi-alternative decision making, BMC Neuroscience, 12(Suppl 1):P137.
• Brohan, K., A. Cope, and K.N. Gurney (2010), Robotic Implementation of Visual Attention Based on Reward Modulated self-Organised Map of Feature Space, EPIROB 2010. Orenas Slott, Sweden.
• Gurney, K.N. (2010), Dopamine-modulated dynamics of the GABAergic striatal microcircuit, 10th IBAGS Meeting. New Jersey..
• Cope, A., J.M. Chambers, D Barr, P. Dudek, and K. N. Gurney (2010), Systems level model integration and embodiment: a case study with gaze control, Bernstein Conference on Computational Neuroscience 2010 (BCCN 2010). Berlin..
• Gurney, K.N. (2010), Implications of recent experimental findings for models of the basal ganglia, Physiological Society Meeting 2010, Manchester.
• Javier A. Caballero and Kevin N. Gurney (2010), Optimal decision making with biologically realistic neural signals, BMC Neuroscience, 11(Suppl 1):P25.
• Brohan, K., K.N. Gurney, and P. Dudek (2010), Using reinforcement learning to guide the development of self-organising feature maps for visual orienting, ICANN 2010, Thessaloniki.
• Bolado-Gomez, R., J.M. Chambers, and K.N. Gurney (2009), The basal ganglia and the 3-factor learning rule: reinforcement learning during operant conditioning, Frontiers in Computational Neuroscience, Proceedings of BCCN Conference.
• Wood, R,, M.D. Humphries, and K.N. Gurney (2009), Does striatum support competitive dynamics? A test of this hypothesis using a biologically realistic model of the striatal microcircuit, BMC Neuroscience, 10, page 317.
• Humphries, M.D., N. Lepora, R. Wood, and K.N. Gurney (2009), Reduced models of striatal neurons: dopamine modulation and dynamics, BMC Neuroscience, 10, (1) 321.
• Gurney, K.N., M.D. Humphries, and P. Redgrave (2009), Cortico-striatal plasticity for action-outcome learning using spike timing dependent eligibility, BMC Neuroscience, 10, (1) 135.
• Lepora, N,, P. Overton, and K.N. Gurney (2009), Efficient current-based optimization techniques for parameter estimation in multi-compartment neuronal models, BMC Neuroscience, 10 (1) 247.
• Cope, A., J.M. Chambers, and K.N. Gurney (2009), Object-based biasing for attentional control of gaze: a comparison of biologically plausible mechanisms, BMC Neuroscience, 10, (1) 19.
• Gurney, K.N., and P Redgrave (2008), A model of sensory reinforced corticostriatal plasticity in the anaesthetised rat, SfN 2008, Washington, Neuroscience Meeting Planner Poster 180.6/RR3.
• Hoyland, D.S., N Lepora, R Wood, P.G. Overton, and K.N. Gurney (2008), Integrated data collection and automated parameter estimation in the construction of conductance-based models of neostriatal neurons, SfN 2008, Washington, Neuroscience Meeting Planner, Poster 694.4/UU65.
• Fox, C., N. Girdhar, and K.N. Gurney (2008), A causal Bayesian network view of reinforcement learning, Proceedings of the 21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21, 109-110.
• Chambers, J.M., and K.N. Gurney (2008), A computational model of ‘inaction-selection’ in multiple domains of basal ganglia, SfN 2008 Washington., Neuroscience Meeting Planner, Poster 472.7/NN28.
• Humphries, M.D, P Redgrave, and K.N. Gurney (2008), Action-outcome contingency and stimulus-response habits as an exploration/exploitation action selection trade-off, SfN 2008 Washington., Neuroscience Meeting Planner Poster 98.3/UU33.
• Mitchinson, B., T.S. Chan, J.M. Chambers, M D Humphries, C. Fox, K.N. Gurney, and T J Prescott (2008), BRAHMS: Novel middleware for integrated systems computation, SfN 2008 Washington, Neuroscience Meeting Planner, Poster 798.10/VV3.
• Wood, R, M. D Humphries, P.G. Overton, and K.N. Gurney (2008), Validation and dynamics of a computational model of the neostriatal microcircuit, SfN 2008, Washington, Neuroscience Meeting Planner, Poster 578.13/QQ15.
• Gurney, K., J. Chambers, and P. Redgrave (2007), A model of reinforcement learning in basal ganglia for action-outcome association, IBAGS IX Meeting.
• Bogacz, R., and K.N. Gurney (2007), The basal ganglia and cortex implement optimal decision making between alternative actions, SfN San Diego 2007, Neuroscience Meeting Planner 622.23/TT8.
• Gurney, K., J. Chambers, and P. Redgrave (2007), A model of reinforcement learning in basal ganglia for action-outcome association, IBAGS IX Meeting.
• Humphries, M.D, and K.N. Gurney (2007), Deep brain stimulation of the subthalamic nucleus causes paradoxical inhibition of output in a computational model of the “parkinsonian” basal ganglia, SfN San Diego 2007, Neuroscience Meeting Planner #622.
• Stewart, R.D, and K.N. Gurney (2007), Flexible, extensible, spiking neural network simulation, SfN SanDiego 2007, Neuroscience Meeting Planner 102.19/ZZ21.
• Redgrave, P., and K.N. Gurney (2006), Timing is everything: Dopamine signals in temporal difference learning, 15thth Annual Computational Neuroscience Meeting, Edinburgh.
• Bogacz, R., K.N. Gurney, and T Larsen (2006), The brain implements optimal decision making mechanisms, 15th Annual Computational Neuroscience Meeting, Edinburgh.
• Wood, R., M.D Humphries, P. Overton, R. Stewart, and K.N. Gurney (2006), Selection in a model of striatum with fast spiking interneurons, 15thth Annual Computational Neuroscience Meeting, Edinburgh.
• Pearson, M., I. Gilhespy, K.N. Gurney, C. Melhuish, B. Mitchinson, M. Nibouche, and A.J. Pipe (2006), Design and FPGA Implementation of an Embedded Real-Time Biologically Plausible Spiking Neural Network Processor, 15th International Conference on Field Programmable Logic and Applications (FPL).
• Bogacz, R., and K.N. Gurney (2006), The Brain Implements Optimal Decision Making between Alternative Actions, 28th Annual Conference of the Cognitive Science Society.
• Pearson, M., M. Nibouche, I. Gilhespy, K.N. Gurney, C. Melhuish, B. Mitchinson, and A.J. Pipe (2006), A Hardware Based Implementation of a Tactile Sensory System for Neuromorphic Signal Processing Applications, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Toulouse.
• Gurney, K.N., M.D. Humphries, and R. Stewart (2005), A spiking neuron model of basal ganglia for action selection can account for dopamine - modulated oscillatory phenomena, SfN 2005, Washington, Neuroscience Meeting Planner #517.
• Pipe, A.J., C. Melhuish, M. Pearson, I. Gilhespy, B. Mitchinson, K.N. Gurney, and A.J. Prescott (2005), Artificial, active vibrissal array modeling the mechanics and neurology of rat whisking, SfN 2005, Washington.
• Mitchinson, B., A.J. Prescott, K.N. Gurney, M. Pearson, I. Gilhespy, and A.J. Pipe (2005), A computational model of a brainstem loop for whisker pattern generation, SfN 2005, Washington.
• Humphries, M., R. Stewart, T.J. Prescott, P. Redgrave, and K.N. Gurney (2004), A spiking neuron model of basal ganglia demonstrating plausible action selection and switching, International Basal Ganglia Society (IBAGS) VIIIth International Triennial Meeting. Crieff, Scotland..
• Gurney, K. N., A.J. Prescott, J.R. Wickens, and P Redgrave (2004), Mechanism mining and mapping in models of the basal ganglia, 8th IBAGS Meeting, Crieff, Scotland.
• Stewart, R., K.N. Gurney, and M.D Humphries (2004), A spiking neuron model of cortically-evoked response patterns in the basal ganglia, International Basal Ganglia Society (IBAGS) VIIIth International Triennial Meeting. Crieff, Scotland..
• Pegg, E.J., K.N. Gurney, R.W. Parks, and A.J. Prescott (2003), Reliability and Validity of a Paced Computer Stroop Task for fMRI Reliability and validity of a paced computer Stroop task for fMRI, Archives of Clinical Neuropsychology, 18, (7), 755.
• Wood, R. & Gurney, K.N. (2003), A Rapid Search Technique for Finding Maximal Conductances in Biophysical Models of Neural Membranes, British Neurosci. Assoc. Abstr., 17:111.
• Parks, R.W., M.D. Hunter, K.N. Gurney, T.J. Prescott, D.S. Levine, I.D. Wilkinson, F. Clay, E. Pegg, P.W.R. Woodruff, and S.A. Spence (2003), A stroop task protocol with overt verbal response during fMRI, uman Brain Mapping Conference, New York, USA..
• Prescott, T. J. Gurney, K. Gonzalez, F. M., Humphries, M. & Redgrave, P. (2003), Action selection in a robot model of the basal ganglia: The role of simulated dopamine, Society for Neuroscience, Program No. 915.5.
• Wood, R. & Gurney, K.N. (2002), A New Parametric Search Technique for Biophysical Models: A Study in the Rat Neostriatal Projection Neuron, Society For Neuroscience Abstracts, Program No. 764.16, Washington, DC..
• Prescott, T.J., K.N. Gurney, F. Montes-Gonzalez, M. Humphries, and P. Redgrave (2001), The robot basal ganglia: Control of action selection by an embedded model of the basal ganglia, VIth Triennial neeting of the International basal Ganglia Society. Bay of Islands, New Zealand..
• Humphries, M.D., and K.N. Gurney (2001), Slow oscillatory activity in a computational model of the basal ganglia, BNA 16th National Meeting, Harrogate, UK .
• Wood, R., Gurney, K. & Redgrave, P. (2001), 'Direct Pathway' Connections to Globus Pallidus in a Computational Model of the Basal Ganglia, British Neurosci. Assoc. Abstr., 16:79.
• Gurney, K.N., R. Wood, and P. Redgrave (2001), 'Direct pathway' connections to globus pallidus in a computational model of the basal ganglia, SfN 2001 Meeting San Diego, Neuroscience Meeting Planner #514.
• Prescott, T.J., F. Montes-Gonzales, K.N. Gurney, M. Humphries, and P. Redgrave (2001), Why is efference copy information sent to the basal ganglia? inspiration from an embodied model, BNA 16th National Meeting, 91.
• McHaffie, G.J., T.J. rescott, F. Montes-Gonzales, K.N. Gurney, M. Humphries, T.R. Stanford, and P Redgrave (2001), Why is efference copy information directed to the basal ganglia? Inspiration from an embodied model, SfN 2001 Meeting San Diego, Neuroscience Meeting Planner #514.
• Humphries, M. D. & Gurney, K. (2000), A computational model of action selection in the basal ganglia: Thalamic and cortical interactions, European Journal of Neuroscience, 12, supp. 11, 260.10.
• Gonzalez, F.Montes, T.J. Prescott, K.N. Gurney, M. Humphries, and P. Redgrave (2000), The robot basal ganglia: control of robot action selection by an embodied model of the vertebrate basal ganglia, In Federation of European Neurosciences Meeting, Brighton, UK, vol 12, supp 11.
• Stafford, T., and K.N. Gurney (2000), A computational model of response selection in the Stroop task, BPS Cognitive Psychology Section 17th Annual Conference, Essex, UK, British Psychological Society Vol 9, No 2.
• Humphries, M. D. & Gurney, K. (1999), A computational model of action selection in the basal ganglia: Thalamic and cortical interactions, Technical Report AIVRU132, The University of Sheffield.
• Gurney, K., Redgrave, P. & Prescott, T.J. (1998), Analysis and simulation of a model of intrinsic processing in the basal ganglia, Technical Report AIVRU131, The University of Sheffield.
• Redgrave, P., T.J. Prescott, and K.N. Gurney (1998), Selection and the basal ganglia: A Role for Dopamine, Vth Triennial neeting of the International basal Ganglia Society. Basal Ganglia. Cape Cod, USA..
• Gurney, K.N., P. Redgrave, and T.J. Prescott (1998), computational model of selective properties within basal ganglia: a reinterpretation of functional anatomy, SfN 1998, Los Angeles, Neuroscience Meeting Planner #24:649.
• Gurney, K.N., T.J. Prescott, and P. Redgrave (1998), A model of intrinsic processing in the basal ganglia, Second International conference on cognitive and neural systems, pp47. Boston..
• Redgrave, P., Prescott, T.J., & Gurney, K. (1997), The basal ganglia: a neural architecture for conflict resolution, Soc Neurosci Abstr, 23:192.
• Wright, M.J., and K.N. Gurney (1996), Thresholds for detecting change in shape, Applied Vision Association Newsletter, 117: 33-34.
• Wright, M.J., and K.N. Gurney (1995), Discrimination of changes in direction of motion, AVA conference on motion perception. Reading, UK..
• Wright, M.J., and K.N. Gurney (1995), Discrimination of direction changes in drifting plaids and gratings, 18th European Conference on Visual Perception, Tubingen, 24:(supplement):103. Perception. .
• Gurney, K.N (1995), Towards a theory of neural-processing complexity, International Workshop on Information Processing in Cells and Tissues. Liverpool..
• Wright, M.J., and K.N. Gurney (1995), Discrimination of rotation sense in gratings and plaids, ARVO, Vol. 34. Investigative Ophthalmology & Visual Science,.
• Wright, M.J., and K.N. Gurney (1994), Discrimination of dynamic orientation changes, 17th European Conference on Visual Perception: Eindhoven, Perception Vol 23.
• Walpole, T., K.N. Gurney, and M.J. Wright (1994), Phenomenology of transient motion coherence, 17th European Conference on Visual Perception: Eindhoven, Perception Vol 23.
• Gurney, K.N., and M.J. Wright (1994), Spatial integration of velocity signals via Markov Random Fields, 17th European Conference on Visual Perception: Eindhoven, Perception Vol 23.
• Wright, M.J., and K.N. Gurney (1994), Is there a special motion system for detecting orientation change, AVA conference on motion perception. UK..
• Ferguson, A., P. Morgan, H. Bolouri, and K.N. Gurney (1993), Learning and topology organisation in large scale hypernets, Weightless Neural Network Workshop. York..
• Gurney, K.N., and M.J. Wright (1993), A quantitative model of early vision accounts for velocity discrimination performance of windowed gratings, 15th European Conference on Visual Perception. Edinburgh, Perception, 22:(supplement):90-91.
• Gurney, K.N., and M.J. Wright (1992), Representing Image velocity in a self-organised neural network, Physiology Society Meeting, Newcastle, Journal of the Physiological Society 452, p287.
• Gurney, K.N., and M.J. Wright (1992), The detection and analysis of local optic flow, 15th European Conference on Visual Perception, Pisa, Italy, Perception, 21:(supplement) p40.
• Wright, M.J., and K.N. Gurney (1992), Coherence, transparency and the discrimination of rigid and non-rigid motion, ARVO Sarasota, Florida., pp 1050.
• Gurney, K.N., and M.J. Wright (1991), Coherence and transparency in non-rigid plaid motion, 14th European Conference on Visual Perception, Vilnius, Perception, 20:(supplement).
• Hui, T., I. Wilkes, P. Morgan, H. Bolouri, and K.N. Gurney (1991), Design of a VLSI-based Artificial Neural Network System by a Student Group, IEE Colloquium on the Eurochip project: VLSI design in education. London..
• Wright, M.J., and K.N. Gurney (1990), Speed Discrimination and Motion Detection in 2-D Patterns, 13th European Conference on Visual Perception, Paris, Perception, 19:(supplement).
• Penney, W., K.N. Gurney, and J. Stonham (1990), Reward-Penalty training for logical neural networks, IASTED International conference, Artificial Intelligence applications and neural networks. Zurich..
• Gurney, K.N., and M.J. Wright (1990), A neural model of velocity encoding, 13th European Conference on Visual Perception, Paris, Perception, 19:(supplement).
• Gurney, K.N., and M.J. Wright, A neural model of velocity encoding, International Joint Conference on Neural Networks, Seattle, I677-I682.