Michael Hull PhD

Mike Hull


Publications:
2016
  Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity
Hull, MJ, Soffe, SR, Willshaw, DJ & Roberts, A 2016, 'Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity' PLoS Computational Biology, vol 12, no. 1, e1004702. DOI: 10.1371/journal.pcbi.1004702

What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition.


General Information
Organisations: School of Informatics.
Authors: Hull, Michael J, Soffe, Stephen R, Willshaw, David J & Roberts, Alan.
Publication Date: 29 Jan 2016
Publication Information
Category: Article
Journal: PLoS Computational Biology
Volume: 12
Issue number: 1
ISSN: 1553-734X
Original Language: English
DOIs: 10.1371/journal.pcbi.1004702
2011
  Infandango: automated grading for student programming
Hull, M, Powell, D & Klein, E 2011, Infandango: automated grading for student programming. in ITiCSE '11 Proceedings of the 16th annual joint conference on Innovation and technology in computer science education . ACM Association for Computing Machinery, pp. 330. DOI: 10.1145/1999747.1999841
Infandango1 is an open source web-based system for automated grading of Java code submitted by students. Uploaded Java les are compiled and run against a set of unit tests on a central server, with results being stored in a database. Students gain near-instant feedback on the correctness of their code, and instructors are able to monitor the progress of students in the class.
General Information
Organisations: Institute of Language, Cognition and Computation .
Authors: Hull, Mike, Powell, Dan & Klein, Ewan.
Number of pages: 1
Pages: 330
Publication Date: 2011
Publication Information
Category: Conference contribution
Original Language: English
DOIs: 10.1145/1999747.1999841
2010
  Algorithms for automatic neuron tracing in noisy 3D image stacks
Knowles-Barley, S, Phillipson, G, Teriakidis, A, Sterratt, D, Larkworthy, T, O'Leary, T, Down, MP, Hennig, M, Withers, JPJ & Hull, M 2010, 'Algorithms for automatic neuron tracing in noisy 3D image stacks' Neuroscience Day 2010, Edinubrgh, United Kingdom, 29/03/10 - 29/03/10, .
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Knowles-Barley, Seymour, Phillipson, Graeme, Teriakidis, Adrianna, Sterratt, David, Larkworthy, Thomas, O'Leary, Timothy, Down, Matthew P., Hennig, Matthias, Withers, James P. J. & Hull, Michael.
Publication Date: 2010
Publication Information
Category: Poster
Original Language: English
  A roles for ratios? How ion channel densities could define neuronal firing properties
Hull, M, Willshaw, D, Winlove, C & Roberts, A 2010, 'A roles for ratios? How ion channel densities could define neuronal firing properties' 40th Society for Neuroscience Annual Meeting, San Diego, United States, 13/11/10 - 17/11/10, .
In Xenopus laevis hatchling tadpoles, locomotion is produced and sustained though a central pattern generating network comprising of the neurons in the brain and spinal cord. Experimental data has shown that these neurons can be subdivided into classes based on morphology and electrical firing characteristics which are found grouped in columns along the rostrocaudal axis. Voltage clamp traces from disassociated neurons and in-vivo recordings have shown the existence of sodium, calcium and potassium currents. In this work, we investigate whether the distinct firing characteristics of each neuron type can be explained by adjusting the ratio of channel densities of a small number of ion channels in a single compartmental neuron model. In particular, we investigate the circumstances under which a neuron firing only once in response to a step current injection, up to twice rheobase, can be turned into a multiple-spiking neuron simply by reducing the density of slow potassium channels; a phenomenon which has been observed in pharmacological studies. Hogkin-Huxley style models of individual ion channels were built based on voltage clamp data and estimates made of the channel densities for each ion channel in a typical neuron. Next, large parameter sweeps around these channel densities were run; at each point in the parameter space, a model neuron was built and tested by injecting current steps of various magnitudes. The traces were classified automatically and the parameter space summarised by simplifying each trace to a set of key features, such as the number of spikes and the spike heights. Simulation administration and analysis code was written in python, simulations distributed over a cluster of computers and run in NEURON and simulation information stored in MySQL and sqlite databases. Based on the observed voltage traces, regions of the parameter space were found which defined single-spike or multiple-spike neurons. In this poster we will discuss the results from this parameter sweep, and the tools and techniques used to run it.
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Hull, Michael, Willshaw, David, Winlove, Crawford & Roberts, Alan.
Publication Date: 2010
Publication Information
Category: Poster
Original Language: English

Projects:
Configurations of neurons in networks are able to create specific behaviours (PhD)