Research

Prescott TJ, Wilson SP (2023) Understanding brain functional architecture through robotics. Science Robotics: 8, eadg6014. doi:10.1126/scirobotics.adg60.

James SS, Englund M, Bottom RT,  Perez R, Conner KE, Huffman K, Wilson SP, Krubitzer LA (2022) Comparing the development of cortex-wide gene expression patterns between two species in a common reference frame. PNAS: 119(41), e2113896119. doi:10.1073/pnas.2113896119.

Brooke JM, James SS, Jiminez-Rodriguez A, Wilson SP (2022) Biological action at a distance: Correlated pattern formation in adjacent tessellation domains without communication. PLoS Computational Biology. doi:10.1371/journal.pcbi.1009963.

Wilson SP, Prescott TJ (2021) Scaffolding layered control architectures through constraint closure: Insights into brain evolution and development. Philosophical Transactions of the Royal Society B: 377, 20200519. doi:10.1098/rstb.2020.0519.

James SJ, Krubitzer LA, Wilson SP (2020) Modelling the emergence of whisker barrels. eLife: 55588. doi:10.7554/eLife.55588.

Wilson SP, James SJ, Whiteley DJ, Krubitzer LA (2019) Limit cycle dynamics can guide the evolution of gene regulatory networks towards point attractors. Scientific Reports 9: 16750. doi:10.1038/s41598-019-53251-w

Wilson SP, Wilson PN (2018) Failure to demonstrate short-cutting in a replication and extension of Tolman et al.'s spatial learning experiment with humans. PLoS ONE 13(12): e0208794. doi:10.1371/journal.pone.0208794

Wilson SP (2017) Modelling the emergence of rodent filial huddling from physiological huddling. Royal Society Open Science: 4, 170885. doi:10.1098/rsos.170885

Spigler G, Wilson SP (2017) Familiarisation: A theory of repetition suppression predicts interference between overlapping cortical representations. PLoS ONE 12(6): e0179306. doi:10.1371/journal.pone.0179306

Wilson SP (2017) Self-organised criticality in the evolution of a thermodynamic model of rodent thermoregulatory huddling. PLoS Computational Biology 13(1): e1005378. doi:10.1371/journal.pcbi.e1005378

Glancy J, Stone JV, Wilson SP (2016) How self-organization can guide evolution. Royal Society Open Science: 3, 160553. doi:10.1098/rsos.160553

Bednar JA, Wilson SP (2016) Cortical maps. The Neuroscientist, 22(6):604-617. doi:10.1177/1073858415597645

Glancy J, Gross R, Stone JV, Wilson SP (2015) A self-organising model of thermoregulatory huddling. PLoS Computational Biology 11(9): e1004283. doi:10.1371/journal.pcbi.1004283

Wilson SP, Bednar JA (2015) What, if anything, are topological maps for? Developmental Neurobiology, 75(6), 667-681. doi:10.1002/dneu.22281

Wilson SP, Moore CI (2015) S1 somatotopic maps Scholarpedia 10(4):8574. doi:10.4249/scholarpedia.8574

Wilson SP, Bednar JA, Prescott TJ, Mitchinson B (2011) Neural computation via neural geometry: A place code for inter-whisker timing in the barrel cortex? PLoS Computational Biology 7(10): e1002188. doi:10.1371/journal.pcbi.1002188

Wilson SP, Law JS, Mitchinson B, Prescott TJ, Bednar JA (2010) Modelling the emergence of whisker direction maps in rat barrel cortex. PLoS ONE 5(1): e8778. doi:10.1371/journal.pone.0008778

Alexander T, Wilson SP and Wilson PN (2009). Blocking of spatial learning based on shape. Journal of Experimental Psychology: Learning, Memory, & Cognition, 35, 694-708. doi:10.1037/a0015124

Stafford T and Wilson SP (2007). Self-organisation can generate the discontinuities in the somatosensory map. Neurocomputing, 70(10-12), 1932-1937. doi:10.1016/j.neucom.2006.10.134

Wilson SP, Verschure FMJ, Mura A, Prescott TJ (Eds.) Biomimetic and Biohybrid Systems, Fourth International Conference, Living Machines 2015 Proceedings, Lecture Notes in Artificial Intelligence, 9222, doi:10.1007/978-3-319-22979-9. 2015.

Prescott TJ, Mitchinson B, Lepora N, Wilson SP, Anderson SR, Porrill J, Dean P, Fox C, Pearson MJ, Sullivan JC, Pipe AG The robot vibrissal system: Understanding mammalian sensorimotor co-ordination through biomimetics, in Krieger P and Groh A, Eds. Sensorimotor Integration on the Whisker System. New York: Springer, 2014 (in press)

Wilson SP Self-organization, in Prescott TJ and Verschure P, Eds. Living Machines, 2015 (in press)

Wilson, S.P. (2017), Self-organising thermoregulatory huddling in a model of soft deformable littermates, Proceedings of Living Machines 6, Biomimetic and Biohybrid Systems (LNCS) 10384:487-496. (Download PDF, 375KB)

Urashima H, Wilson SP (2014) A self-organizing animat body map In Duff et al Eds.: Living Machines 2014, Biomimetic and Biohybrid Systems, Lecture Notes in Artificial Intelligence, 8608, 439-441. doi:10.1007/978-3-642-39802-5_64 (winner of best paper prize)

Wilson SP, Prescott TJ (2013) Evo-devo design for living machines. In Lepora et al Eds.: Living Machines 2013, Lecture Notes in Artificial Intelligence, 8064, 454-456. doi:10.1007/978-3-642-39802-5_64

Glancy J, Gross R, Wilson SP (2013) A minimal model of the phase transition into thermoregulatory huddling. In Lepora et al Eds.: Living Machines 2013, Lecture Notes in Artificial Intelligence, 8064, 381-383. doi:10.1007/978-3-642-39802-5_41

Wilson SP (2013) The synthetic littermate. In Lepora et al Eds.: Living Machines 2013, Lecture Notes in Artificial Intelligence, 8064, 450-453. doi:10.1007/978-3-642-39802-5_63

Wilson SP, Bertolin CB and Stafford T Musicians make more music mistakes, non-musicians make more motor mistakes. International conference on the multimodal experience of music, 2015.

Wilson SP, Mitchinson B, Pearson M, Bednar JA and Prescott TJ Learning multi-whisker spatial-temporal cortical receptive fields from robotic whisker input. In Society for Neuroscience Abstracts. Society for Neuroscience (Program No. 174.4), 2009.

Wilson SP, Mitchinson B, Pearson M, Bednar JA and Prescott TJ Learning multi-whisker spatial-temporal cortical receptive fields from robotic whisker input. Society for Neuroscience 2009: Media materials.

Wilson SP, Mitchinson B, Pearson M, Bednar JA and Prescott TJ Learning cortical representations from multiple whisker inputs. In BMC Neuroscience, volume 10(Suppl 1), page P334, 2009. Proceedings of the Eighteenth Annual Computational Neuroscience Meeting (CNS), 2009.

Wilson SP Self-organising computational models of cortical map development. Symposium on Data Modelling, Dept of Engineering, Sheffield University (Winner of best paper prize), 2008.

Wilson SP, Fox CW, Prescott TJ and Bednar JA A self-organizing model of whisker deflection maps in the barrel cortex. In Barrels XX (SfN Satellite Meeting), 2007.

Wilson SP (2011) Figuring time by space: Representing sensory motion in cortical maps PhD thesis, University of Sheffield, UK.

Wilson SP (2007) Self-organisation can explain the mapping of angular whisker deflections in the barrel cortex. Masters thesis, The University of Edinburgh, Scotland, UK.

Wilson SP (2006) Self-organisation can explain the discontinuities in the somatosensory map Undergraduate dissertation, University of Sheffield, UK.