Dr Stuart Wilson
Department of Computer Science
Senior Lecturer in Computational Neuroscience
+44 114 222 1913
Full contact details
Department of Computer Science
Regent Court (DCS)
Stuart studied Psychology & Cognitive Neuroscience at the University of Sheffield (2006) and Bioinformatics & Neuroinformatics at the University of Edinburgh (2007) before completing a PhD in Theoretical Neuroscience at the University of Sheffield (2011). He was appointed as a Lecturer in the Department of Psychology at the University of Sheffield in 2012, and as a Senior Lecturer in 2020. Stuart joined the Department of Computer Science in 2023.
- Research interests
Stuart is interested in how self-organisation and natural selection interact to shape complex systems, including brains. He explores this interaction through computational neuroscience modelling, and by connecting artificial neural networks to the physical world through robotics.
- Understanding brain functional architecture through robotics. Science Robotics, 8(78).
- Comparing the development of cortex-wide gene expression patterns between two species in a common reference frame. Proceedings of the National Academy of Sciences, 119(41).
- Biological action at a distance: correlated pattern formation in adjacent tessellation domains without communication. PLoS Computational Biology, 18(3).
- Scaffolding layered control architectures through constraint closure : insights into brain evolution and development. Philosophical Transactions of the Royal Society B: Biological Sciences, 377(1844).
- Modelling the emergence of whisker barrels. eLife, 2020(9).
- Limit cycle dynamics can guide the evolution of gene regulatory networks towards point attractors. Scientific Reports, 9(1).
- Failure to demonstrate short-cutting in a replication and extension of Tolman et al.'s spatial learning experiment with humans. PLoS One, 13(12).
- Modelling the emergence of rodent filial huddling from physiological huddling. Royal Society Open Science, 4, 170885-170885.
- Familiarization: A theory of repetition suppression predicts interference between overlapping cortical representations. PLoS ONE, 12(6).
- How self-organization can guide evolution. Royal Society Open Science, 3.
- Cortical Maps. Neuroscientist.
- A Self-Organising Model of Thermoregulatory Huddling. PLOS Computational Biology, 11(9).
- What, if anything, are topological maps for?. Developmental Neurobiology, 75(6), 667-681.
- Neural computation via neural geometry: a place code for inter-whisker timing in the barrel cortex?. PLoS Comput Biol, 7(10), e1002188.
- Modeling the emergence of whisker direction maps in rat barrel cortex.. PLoS One, 5(1), e8778.
- Learning cortical representations from multiple whisker inputs. BMC Neuroscience, 10(Suppl ), P334.
- Blocking of Goal-Location Learning Based on Shape. Journal of Experimental Psychology: Learning Memory and Cognition, 35(3), 694-708.
- Self-organisation can generate the discontinuities in the somatosensory map. NEUROCOMPUTING, 70(10-12), 1932-1937.
- Self-organised criticality in the evolution of a thermodynamic model of rodent thermoregulatory huddling. PLoS Computational Biology, 13(1).
- Self-organization Oxford University Press
- S1 Somatotopic Maps, Scholarpedia of Touch (pp. 565-576). Atlantis Press
- The robot vibrissal system: Understanding mammalian sensorimotor co-ordination through biomimetics In Krieger P & Groh A (Ed.), Sensorimotor Integration in the Whisker System (pp. 213-240). New York: Springer.
- Preface In Wilson S, Verschure P, Mura A & Prescott A (Ed.), 4th International Conference, Living Machines 2015, Barcelona, Spain, July 28 - 31, 2015, Proceedings (pp. v-vi). Springer International Publishing
Conference proceedings papers
- A framework for resolving motivational conflict via attractor dynamics. Biomimetic and Biohybrid Systems : 9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings(12413) (pp 192-203). Freiburg, Germany, 28 July 2020 - 28 July 2020.
- Self-organising Thermoregulatory Huddling in a Model of Soft Deformable Littermates. Living Machines 2017: Biomimetic and Biohybrid Systems (pp 487-496). Stanford, CA, USA, 26 July 2017 - 26 July 2017.
- Biomimetic and Biohybrid Systems
- A Self-organising Animat Body Map (pp 439-441)
- Evo-devo design for living machines. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8064 LNAI (pp 454-456)
- A minimal model of the phase transition into thermoregulatory huddling. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8064 LNAI (pp 381-383)
- The synthetic littermate. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8064 LNAI (pp 450-453)
- Research group
Complex Systems Modelling research group
Affiliated member of the Machine Learning research group