Dr John Butcher

Title: Research Associate
Phone: +44 (0)1782 733678
Email: j.b.butcher@keele.ac.uk
Location: Huxley building: 214
Role: Record some neurons!
Contacting me: Send me an email

I've been fascinated in the brain, learning and computation since a young age.  I remember being taken in by illusions created by artists, such as Escher, the chessboard illusion and the McGurk effect.  Around the same time, I managed to get my hands on my Dad's Commadore 64 and became hooked on programming and computers.  Since then I’ve been rather fortunate (most days!) to conduct research in both of these fields where I currently investigate some of the many mechanisms of plasticity and navigational systems.  This knowledge can be used to shed more light on the brain as well as solve real-world problems.

I graduated from Keele University with 1st class honours in Computer Science and Management Science in 2007.   My PhD investigated the use of Artificial Neural Networks when applied to highly non-linear time-series datasets where it was shown that improved performance can be obtained using a novel reservoir with random static projections (R2SP).

After completing my PhD, I was eager to pursue my interest in understanding how the brain works and undertook a post doctorate in Neuroscience investigating astrocytes and plasticity in the barrel cortex in 2012.  I then moved into imaging of populations of neurons with novel voltage-sensitive dyes in-vitro using the stomatogastic ganglion (STG) of the brown crab (Cancer pagurus) as the model system.  Most recently I have become involved in a project investigating the effects of caffeine on learning.  As a fan of tea and coffee, this of particular interest to me! 

Here are my LinkedIn and Orcid profiles for those interested.

My interests lie in two fields which overlap greatly.  First, the brain and its underlying mechanisms.  To satisfy this interest I'm currently a post doc at Keele in Neuroscience where I study plasticity in the hippocampus.  I also am part of a project investigating the use of novel voltage-sensitive dyes in-vitro using the crab stomatogastric ganglion as the model system.  Additionally, I investigate plasticity models in the brain: an area of great interest in discovering how the brain works and adapts to our dynamic world.   This work has investigated the effect of astrocytes on plasticity, a largely understudied area in Neuroscience until recently, and showed that they are integral in homeostatic plasticity mechanisms.

Secondly, the field of Computational Intelligence, particularly anything to do with Neural Networks and the areas of Reservoir Computing and Echo State Networks.  A good introduction on Echo State Networks can be found on Scholarpedia. A free Matlab and Python toolkit, along with many publications using Reservoir Computing can be found on the Reservoir Lab website which is based at Ghent University, Belgium: http://reslab.elis.ugent.be/.

My other research interests lie in biologically plausible approaches at replicating how the brain functions (an intersection of my two interests), such as spiking neural networks and the fascinating field of Computational Neuroscience.  I am involved in research with colleagues in Computing that has used biologically inspired models for robot navigation.  Other areas of research include speech recognition, signal processing (e.g. stem cell classification and the forensic sciences) and generally finding out as much as I can on how the human brain works. 

To further my knowledge in Computational Neuroscience, I have attended several excellent summer schools including the course at the University of Ottawa, Canada (for more info see http://www.neurodynamic.uottawa.ca/summer.htm), CRCNS summer school (https://crcns.org/course/), CoSMo 2012 (http://www.compneurosci.com/CoSMo2012/) and the IBRO/UNESCO Interregional summer school on Computational Neuroscience in Hyderabad, India (IBRO summer school).  While intensive, these courses were very interesting where several topics regarding neural models, analysis of neural data and stochastic resonance, among others, were covered.  I would recommend these courses (as well as others) to anyone interested in this field.

Selected Publications

  • Butcher JB, Rutter AV, Wootton AJ, Day CR, Sule-Suso J. 2018. Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer. In Advances in Computational Intelligence Systems. UKCI 2017. Advances in Intelligent Systems and Computing. Chao F, Schockaert S, Zhang Q (Eds.). (vol. 650). Springer, Cham. doi> full text>
  • Moore HE, Butcher JB, Day CR, Drijfhout FP. 2017. Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species. Forensic Sci Int, vol. 280, 233-244. link> doi> full text>
  • Sirbu D, Butcher JB, Waddell PG, Andras P, Benniston AC. 2017. Locally Excited State-Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes. Chemistry, vol. 23(58), 14639-14649. link> doi> full text>
  • Wootton AJ, Butcher JB, Kyriacou T, Day CR, Haycock PW. 2017. Structural health monitoring of a footbridge using Echo State Networks and NARMAX. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 64, 152-163. link> doi> full text>
  • Scardapane S, Butcher JB, Bianchi FM, Malik ZK. 2017. Advances in Biologically Inspired Reservoir Computing. COGNITIVE COMPUTATION, vol. 9(3), 295-296. link> doi> full text>

Full Publications List show

Journal Articles

  • Moore HE, Butcher JB, Day CR, Drijfhout FP. 2017. Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species. Forensic Sci Int, vol. 280, 233-244. link> doi> full text>
  • Sirbu D, Butcher JB, Waddell PG, Andras P, Benniston AC. 2017. Locally Excited State-Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes. Chemistry, vol. 23(58), 14639-14649. link> doi> full text>
  • Wootton AJ, Butcher JB, Kyriacou T, Day CR, Haycock PW. 2017. Structural health monitoring of a footbridge using Echo State Networks and NARMAX. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol. 64, 152-163. link> doi> full text>
  • Scardapane S, Butcher JB, Bianchi FM, Malik ZK. 2017. Advances in Biologically Inspired Reservoir Computing. COGNITIVE COMPUTATION, vol. 9(3), 295-296. link> doi> full text>
  • Moore HE, Butcher JB, Adam CD, Day CR, Drijfhout FP. 2016. Age estimation of Calliphora (Diptera: Calliphoridae) larvae using cuticular hydrocarbon analysis and Artificial Neural Networks. Forensic Sci Int, vol. 268, 81-91. link> doi> full text>
  • Sims RE, Butcher JB, Parri HR, Glazewski S. 2015. Astrocyte and Neuronal Plasticity in the Somatosensory System. Neural Plast, vol. 2015, 732014. link> doi>
  • Butcher JB, Day CR, Austin JC, Haycock PW, Verstraeten D, Schrauwen B. 2014. Defect Detection in Reinforced Concrete Using Random Neural Architectures. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, vol. 29(3), 191-207. link> doi>
  • Butcher JB, Moore HE, Day CR, Adam CD, Drijfhout FP. 2013. Artificial Neural Network analysis of hydrocarbon profiles for the ageing of Lucilia sericata for Post Mortem Interval estimation. Forensic Science International, vol. 232(1-3), 25-31. doi>
  • Butcher JB, Verstraeten D, Schrauwen B, Day CR, Haycock PW. 2013. Reservoir Computing and extreme learning machines for non-linear time-series data analysis. Neural Networks, vol. 38, 76-89. doi>
  • Day CR, Austin JC, Butcher JB, Haycock PW, Kearon AT. 2009. Element-specific determination of X-ray transmission signatures using neural networks. NDT & E INTERNATIONAL, vol. 42(5), 446-451. link> doi>
  • Kitchenham BA, Brereton OP, Owen S, Butcher J, Jefferies C. 2008. Length and readability of structured software engineering abstracts. IET SOFTWARE, vol. 2(1), 37-45. link> doi>

Chapters

  • Butcher JB, Rutter AV, Wootton AJ, Day CR, Sule-Suso J. 2018. Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer. In Advances in Computational Intelligence Systems. UKCI 2017. Advances in Intelligent Systems and Computing. Chao F, Schockaert S, Zhang Q (Eds.). (vol. 650). Springer, Cham. doi> full text>

Other

  • Kyriacou T, Butcher JB, Day CR. 2011. A biologically inspired model of the head direction system of rats implemented on a robot. International Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems 2011.
  • Butcher JB, Verstraeten D, Schrauwen B, Day CR, Haycock, P.W.. 2010. Extending reservoir computing with random static projections: a hybrid between extreme learning and RC. 18th European Symposium on Artificial Neural Networks (ESANN 2010) (pp. 303-308). Evere, Belgium: D-Side.
  • Butcher JB, Lion M, Day CR, Haycock PW, Hocking MJ. 2009. A Low Frequency Electromagnetic Probe for Detection of Corrosion in Steel-Reinforced Concrete. In M. Grantham & C. Majorana (Eds.). Concrete Solutions (pp. 446-451). CRC Press.
  • Butcher JB, Verstaeten D, Schrauwen B, Day CR, Haycock PW. Pruning reservoirs with random static projections. Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on (pp. 250-255).