Prof. Tony J. Prescott

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    Dept Psychology, Univ of Sheffield, UK

    Current Appointments

    Education

    • MA Psychology (honours), University of Edinburgh, 1984.
    • MSc Applied Artificial Intelligence, University of Aberdeen, 1989.
    • PhD, University of Sheffield, 1994.

    Homepage

    Research Interests
    My research is concerned with understanding brain function using methods in the computational, neural, and behavioural sciences. An important focus is on comparing the control problems faced by animals and robots: (i) using insights from robotics and artificial intelligence to understand the control architecture of the brain (e.g. 10), (ii) using evidence from brain evolution to inspire the design of robot control systems (6), and (iii) using robots to evaluate computational models of neural systems and to test hypotheses that are difficult to investigate in vivo (4, 8). A key focus of this work has been to understand the neural substrates of action selection in the vertebrate brain, particularly the basal ganglia (1, 8, 9, 11) and the reticular formation (7). I have also applied this general approach to the understanding of active sensing in mammals, particularly in the context of vibrissal (whisker) sensing in rats (2, 4, 5). I co-cofounded the conference series "Living Machines" which focuses on research in biomimetic and biohybrid systems (1), and currently direct the Sheffield Centre for Robotics.

    Selected Bibliography

    1. Arkley, K., Grant, R. A., Mitchinson, B. and Prescott, T. J. (2014). Strategy change in vibrissal active sensing during rat locomotion. Current Biology.
    2. Grant, R. A., Sharp, P. S., Kennerley, A. J.,, Berwick, J., Grierson, A., Ramesh, T., Prescott, T. J. (2014). Abnormalities in whisking behaviour are associated with lesions in brain stem nuclei in a mouse model of amyotrophic lateral sclerosis. Behavioural Brain Research. 259, 274-283.
    3. Mitchinson, B., Pearson, M. J., Pipe, A. G., Prescott, T. J. (2014). Biomimetic tactile target acquisition, tracking and capture, Robotics and Autonomous Systems.
    4. Mitchinson, B., Prescott T. J. (2013). Whisker Movements Reveal Spatial Attention: A Unified Computational Model of Active Sensing Control in the Rat. PLoS Comput Biol 9(9): e1003236. doi:10.1371/journal.pcbi.1003236
    5. Grant, R. A., Haidarliu, S., Kennerley, N. J., Prescott, T. J. (2013). The evolution of active vibrissal sensing in mammals: evidence from vibrissal musculature and function in the marsupial opossum Monodelphis domestica. Journal of Experimental Biology. doi: 10.1242/jeb.087452
    6. Prescott, T. J., Lepora, N., Mura, A. and Verschure, P. M. J. (2012) Biomimetic and Biohybrid Systems, LNAI vol. 7375.
    7. Prescott, T. J., Diamond, M. E. and Wing, A. M. (2011) Theme issue on Active Touch Sensing. Philosophical Transactions of the Royal Society B: Biological Sciences.
    8. Prescott, T. J., Bryson, J. J., Seth, A. (2007). Theme issue on modelling natural action selection. Philosophical Transactions of the Royal Society B: Biological Sciences.
    9. Pearson, M. J., Mitchinson, B., Pipe, A. G., Melhuish, C., and Prescott, T. J. (2007). Whiskerbot: A robotic active touch system modelled on the rat whisker sensory system. Adaptive Behavior, 15:223-240.
    10. Mitchinson, B., Martin, C. J., Grant, R., and Prescott (2007). Feedback control in active sensing: Tactile exploration in the rat is modulated by environmental contact. Proceedings of the Royal Society. B: Biological Sciences, 274(1613), 1035-41.
    11. Prescott, T. J. (2007). Forced moves or good tricks in design space? Landmarks in the evolution of neural mechanisms for action selection. Adaptive Behavior. 15: 9-31.
    12. 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. 273, 503-511.
    13. Prescott, T. J., Gonzalez, F. M., Gurney, K., Humphries, M. D., & Redgrave, P. (2006). A robot model of the basal ganglia: behavior and intrinsic processing. Neural Networks, 19, 31-61.
    14. Gurney, K., Prescott, T. J., Wickens, J., and Redgrave, P. (2004). Computational models of the basal ganglia: from membranes to robots. Trends in Neurosciences, 27, 453–459.
    15. Prescott, T.J., Redgrave, P., & Gurney, K. (1999). Layered control architectures in robots and vertebrates, Adaptive Behavior, 7, 99-127.
    16. Redgrave, P., Prescott, T.J. and Gurney, K. (1999). The basal ganglia: a vertebrate solution to the selection problem?, Neuroscience, 89, 1009–1023.
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