Professor Goodhill did a Joint Honours BSc in Mathematics and Physics at Bristol University (UK), followed by an MSc in Artificial Intelligence at Edinburgh University and a PhD in Cognitive Science at Sussex University. Following a postdoc at Edinburgh University he moved to the USA in 1994, where he did further postdoctoral study in Computational Neuroscience at Baylor College of Medicine and the Salk Institute. Professor Goodhill formed his own lab at Georgetown University in 1996, where he was awarded tenure in the Department of Neuroscience in 2001. In 2005 he moved to a joint appointment between the Queensland Brain Institute and the School of Mathematical and Physical Sciences at the University of Queensland.
From 2005-2011 Professor Goodhill was Editor-in-Chief of the journal Network: Computation in Neural Systems. He is currently an Associate Editor of Neural Computation, and on the Editorial Board of Nature Scientific Reports.
Professor Goodhill's lab is interested in how brains process information, particularly during development. This includes how growing nerve fibres use molecular cues to make guidance decisions, how map-like representations of visual inputs form in the optic tectum and visual cortex, and how these maps code sensory information. The lab is addressing these questions using a combination of experimental, mathematical and computational techniques. Members of the lab come from diverse backgrounds including biology, mathematics, physics and computer science.
- Frank Sengpiel- University of Cardiff
- Linda Richards - The University of Queensland
- Michael Ibbotson - ANU
- Peter Dayan - University College London
- Ethan Scott - The University of Queensland
Goodhill, G.J. (2016). Can molecular gradients wire the brain? Trends in Neurosciences, in press.
Nguyen, H., Dayan, P.,Pujic, Z., Cooper-White, J. & Goodhill, G.J. (2016). A mathematical model explains saturating axon guidance responses to molecular gradients. eLife, 5:e12248. PDF
Bicknell, B.A., Dayan, P. & Goodhill, G.J. (2015). The limits of chemosensation vary across dimensions. Nature Communications, 6, 7468. PDF
Suarez, R., Fenlon, L.R., Marek, R., Avitan, L., Sah, P., Goodhill, G.J. & Richards, L.J. (2014). Balanced interhemispheric cortical activity is required for correct targeting of the corpus callosum. Neuron, 82, 1289-1298. PDF
Sutherland, D.J., Pujic, Z. & Goodhill, G.J. (2014). Calcium signaling in axon guidance. Trends in Neurosciences, 37, 424-432. PDF
Forbes, E.M., Thompson, A.W., Yuan, J, & Goodhill, G.J. (2012). Calcium and cAMP levels interact to determine attraction versus repulsion in axon guidance. Neuron, 74, 490-503. PDF SI
Mortimer D, Pujic Z, Vaughan T, Thompson AW, Feldner J, Vetter I, Pujic Z, & Goodhill GJ (2010). Axon guidance by growth rate modulation. Proc. Natl. Acad. Sci. USA, 107, 5202-5207. PDF
Mortimer D, Feldner J, Vaughan T, Vetter I, Pujic Z, Rosoff WJ, Burrage K, Dayan P, Richards LJ, Goodhill GJ (2009). A Bayesian model predicts the response of axons to molecular gradients. Proc. Natl. Acad. Sci. USA, 106, 10296-10301. PDF
Mortimer, D., Fothergill, T., Pujic, Z., Richards, L.J. & Goodhill, G.J. (2008). Growth Cone Chemotaxis. Trends in Neurosciences, 31, 90-98. PDF
Goodhill, G.J. (2007). Contributions of theoretical modelling to the understanding of neural map development. Neuron, 56, 301-311. PDF
Rosoff, W.J., Urbach, J.S., Esrick, M., McAllister, R.G. Richards, L.J. & Goodhill, G.J. (2004). A new chemotaxis assay shows the extreme sensitivity of axons to molecular gradients. Nature Neuroscience, 7, 678-682. PDF