Professor Kevin N Gurney, BSc, MSc, PhD
PHD Neural Networks, Dept of Electronic Engineering (Brunel), MSc Digital Systems (Brunel), BSc Mathematical Physics (Sussex)
I am co-leader of the Adaptive Behaviour Research Group, where I focus on computational modeling but interact with, and support, experimental work in human psychophysics, neuroscience and robotics. One of the hallmarks of my research is building models at different levels of description: from individual conductance-based neurons, through microcircuits of reduced neuron models and large scale spiking networks, to population-based (rate-coded) models with robotic embodiment, and abstract mathematical descriptions. Specific areas of interest include:
This has been my main focus for over a decade. I am seeking to answer question such as: how do we ‘decide what to do next’, given the plethora of behavioural demands at any moment, and how do we make perceptual decisions when confronted with noisy, ambiguous stimuli. This work is predicated on the hypothesis that the basal ganglia (BG) play a key role in these processes and my lab has developed several models at many scales of description including: population level models of BG and its loops with cortex – a compartmental model of individual neurons in striatum , a spiking model of the BG , and models of the striatal microcircuit , . The models have also been subject to Bayesian analysis , .
Closely linked with action selection, this work seeks to answer the question: how do we learn new skills and actions and how can we use the resulting knowledge in goal-directed behaviour? The initial focus here was a critique of the role of phasic dopamine in learning . The main ideas have been tested in a large scale model  and a simulated autonomous robot .
This work grew out of work to test our models of action selection in complete, biologically grounded sensorimotor loops – in this case visual perception and gaze control –. I am also interested in understanding the minimal substrate required for aspects of cognitive vision as demonstrated in the honeybee - a topic within the recently awarded Green Brain project.
What principled approaches should we use in building computational models of the brain? How should we integrate models at different scales of description? These are questions addressed in , .
Neuroinformatics and software tool development
Science has often made step changes when the appropriate tools have been invented. I am interested in developing high throughput parameter fitting techniques for conductance-based models , , ) and model description languages .
Please see the Adaptive Behaviour Research Group page
Recent Research Grants
2013-2016 EPSRC “Green Brain”; CI
2011-2014, EPSRC “Dual Process Control Models in the Brain and Machines with Application to Autonomous Vehicle Control”; CI.
2011-2012 EPSRC Delivery Plan ‘Kickstart’ funding. A neural microcircuit in silico: biologically realistic neuromorphic engineering at Sheffield; PI.
2009 – 2013, EU-FP7 “IM-CLeVeR: Intrinsically Motivated Cumulative Learning Versatile Robots”; Ci.
2007-2009 EPSRC "CARMEN: Code analysis, repository, and modelling for e-Neuroscience." CI
2005-2010 EPSRC "REVERB: Computation for Autonomous Agents: A Novel Approach based on the Vertebrate Brain”; PI
2005-2009 EU FP6 "ICEA: Integrating Emotion, Cognition and Autonomy"; CI
Teaching and administrative duties
I am a Director of the MSc in Cognitive and Computational Neuroscience (CCN) MSc, sit on the Postgraduate Studies Committee, and chair the Computing Committee. At postgraduate level I teach the entirety of PSY6307 (computational neuroscience I) on CCN and contribute to the modules on neuroscience and cognitive neuroscience.
Activities and Distinctions
- Elected as Fellow of the Society of Biology
- Editorial panel: Journal of Intelligent Systems
- Editorial panel: Journal of Cognitive Computation
- Selected speaking invitations: International Basal Ganglia Society (IBAGS) meeting, 2010, British Neuroscience Association 2009, International symposium on motivation, learning and memory, Lund, Sweden, 2005.
- IBAGS symposium organizer 2007
- National policy and practice. Neuroinformatics Network Inaugural Workshop 2005.
- Invited articles: include the keynote introduction “Neural networks for perceptual processing: from simulation tools to theories” Philosophical Transactions of the Royal Society London B special issue on 'Use of Neural Networks to Studying Perception in Animals' (2007)
- Public engagement with science: InsideTrak exhibit; see this YouTube clip
- Member of the Sheffield Centre for Robotics (SCentRo)
- Member of Sheffield Institute for in silico medicine (INSIGNEO)
A list of key publications can be found below. For a full list of publications please click here
- Caballero JA, Lepora NF & Gurney KN (2015) Probabilistic Decision Making with Spikes: From ISI Distributions to Behaviour via Information Gain. PLOS ONE, 10(4), e0124787-e0124787. View this article in WRRO
- Gurney KN, Humphries MD & Redgrave P (2015) A New Framework for Cortico-Striatal Plasticity: Behavioural Theory Meets In Vitro Data at the Reinforcement-Action Interface. PLoS Biology, 13(1). View this article in WRRO
- Tomkins A, Vasilaki E, Beste C, Gurney K & Humphries MD (2013) Transient and steady-state selection in the striatal microcircuit.. Front Comput Neurosci, 7, 192. View this article in WRRO
- Mannella F, Gurney K & Baldassarre G (2013) The nucleus accumbens as a nexus between values and goals in goal-directed behaviour: a review and a new hypothesis. FRONTIERS IN BEHAVIORAL NEUROSCIENCE, 7. View this article in WRRO
- Bolado-Gomez R & Gurney K (2013) A biologically plausible embodied model of action discovery.. Front Neurorobot, 7, 4. View this article in WRRO
- Lepora NF & Gurney KN (2012) The basal ganglia optimize decision making over general perceptual hypotheses.. Neural Comput, 24(11), 2924-2945.
- Humphries MD & Gurney K (2012) Network effects of subthalamic deep brain stimulation drive a unique mixture of responses in basal ganglia output.. Eur J Neurosci, 36(2), 2240-2251.
- Humphries MD, Khamassi M & Gurney K (2012) Dopaminergic control of the exploration-exploitation trade-off via the basal ganglia. Frontiers in Neuroscience(FEB). View this article in WRRO
- Lepora NF, Overton PG & Gurney K (2012) Efficient fitting of conductance-based model neurons from somatic current clamp.. J Comput Neurosci, 32(1), 1-24.
- Lepora NF, Blomeley CP, Hoyland D, Bracci E, Overton PG & Gurney K (2011) A simple method for characterizing passive and active neuronal properties: application to striatal neurons.. Eur J Neurosci, 34(9), 1390-1405.
- Stafford T, Ingram L & Gurney KN (2011) Piéron's Law holds during stroop conflict: insights into the architecture of decision making.. Cogn Sci, 35(8), 1553-1566.
- Humphries MD, Wood R & Gurney K (2010) Reconstructing the three-dimensional GABAergic microcircuit of the striatum.. PLoS Comput Biol, 6(11), e1001011. View this article in WRRO
- Humphries MD, Wood R & Gurney K (2009) Dopamine-modulated dynamic cell assemblies generated by the GABAergic striatal microcircuit.. Neural Netw, 22(8), 1174-1188. View this article in WRRO
- Gurney KN (2009) Reverse engineering the vertebrate brain: Methodological principles for a biologically grounded programme of cognitive modelling. Cognitive Computation, 1(1), 29-41.
- Redgrave P, Gurney K & Reynolds J (2008) What is reinforced by phasic dopamine signals?. Brain Res Rev, 58(2), 322-339.
- Humphries MD & Gurney K (2008) Network 'small-world-ness': a quantitative method for determining canonical network equivalence.. PLoS One, 3(4), e0002051. View this article in WRRO
- Bogacz R & Gurney K (2007) The basal ganglia and cortex implement optimal decision making between alternative actions. NEURAL COMPUT, 19(2), 442-477.
- Redgrave P & Gurney K (2006) The short-latency dopamine signal: a role in discovering novel actions?. Nat Rev Neurosci, 7(12), 967-975.
- Humphries MD, Stewart RD & Gurney KN (2006) A physiologically plausible model of action selection and oscillatory activity in the basal ganglia. Journal of Neuroscience, 26(50), 12921-12942.
- Gurney K, Prescott TJ, Wickens JR & Redgrave P (2004) Computational models of the basal ganglia: from robots to membranes.. Trends Neurosci, 27(8), 453-459.
- Gurney K, Prescott TJ & Redgrave P (2001) A computational model of action selection in the basal ganglia. II. Analysis and simulation of behaviour.. Biol Cybern, 84(6), 411-423.
- Gurney K, Prescott TJ & Redgrave P (2001) A computational model of action selection in the basal ganglia. I. A new functional anatomy.. Biol Cybern, 84(6), 401-410.
- Gurney KN (2001) Information processing in dendrites: II. Information theoretic complexity. Neural Networks, 14(8), 1005-1022.
- Gurney KN (2001) Information processing in dendrites: I. Input pattern generalisation. Neural Networks, 14(8), 991-1004.
- Redgrave P, Prescott TJ & Gurney K (1999) The basal ganglia: a vertebrate solution to the selection problem?. Neuroscience, 89(4), 1009-1023. View this article in WRRO