Geoffrey Goodhill, Ph.D.

Professor of Developmental Biology and Neuroscience

Research Interests

My overall goal is to understand the computational principles that underly brain development, using a combination of experimental and theoretical approaches. Previously I have studied how growing nerve fibers detect and respond to molecular gradients to find their targets, and how visual experience affects the development of maps in the developing brain. Currently we are using the larval zebrafish as a model to understand the links between the development of patterns of brain activity and complex behaviors and how the development of brain and behavior is altered in Autism Spectrum Disorders.

Education

1986 BSc Joint Mathematics and Physics, University of Bristol

1988 MSc Artificial Intelligence, University of Edinburgh

1992 PhD Cognitive Science, University of Sussex

Honors and Awards

1988 Rank Xerox Prize for best M.Sc. thesis in School of Information Technology at Edinburgh University

1992 Medical Research Council (UK) Postdoctoral Training Fellowship (Edinburgh University)

1995 Sloan Theoretical Neuroscience Postdoctoral Fellow (Salk Institute).

2012 Paxinos-Watson Prize by the Australasian Neuroscience Society for the most significant paper published annually by a member of the society.

2019 Elspeth McLachlan Plenary Lecture at the Australasian Neuroscience Society Annual Conference.

2020 Keynote lecture at the 29th annual Computational Neuroscience Meeting.

Selected publications

McCullough MH, Goodhill GJ. Unsupervised quantification of naturalistic animal behaviors for gaining insight into the brain. Current Opinion in Neurobiology. 2021; 70:89–100.

Avitan, L., Pujic, Z., Molter, J., Zhu, S., Sun, B. & Goodhill, G.J. (2021). Spontaneous and evoked activity patterns diverge over development. eLife, 10:e61942

Avitan, L., Pujic, Z., Molter, J., McCullough, M., Zhu, S., Sun, B., Myhre, A-E. & Goodhill, G.J. (2020). Behavioral signatures of a developing neural code. Current Biology, 30, 3352-3363.

Avitan, L. & Goodhill, G.J. (2018). Code under construction: neural coding over development. Trends in Neurosciences, 41, 599-609.

Triplett, M.A., Avitan, L. & Goodhill, G.J. (2018). Emergence of spontaneous assembly activity in developing neural networks without afferent input. PLoS Computational Biology, 14:e1006421.

Avitan, L., Pujic, Z., Moelter, J., Van De Poll, M., Sun, B., Teng, H., Amor, R., Scott, E.K. & Goodhill, G.J. (2017). Spontaneous activity in the zebrafish tectum reorganizes over development and is influenced by visual experience. Current Biology, 27, 2407-2419.

Hughes, N.J. & Goodhill, G.J. (2017). Multiple cortical feature maps in a joint Gaussian process prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1918-1928.

Bicknell, B.A. & Goodhill, G.J. (2016). The emergence of ion channel modal gating from independent subunit kinetics. Proc. Natl. Acad. Sci. USA, 113, E5288-97.

Cloherty, S.J., Hughes, N.J., Hietanen, M.A., Bhagavatula, P.S., Goodhill, G.J. & Ibbotson, M.R. (2016). Sensory experience modifies feature map relationships in visual cortex. eLife, 5:e13911.

Avitan, L., Pujic, Z., Hughes, N.J., Scott, E.K. & Goodhill, G.J. (2016). Limitations of neural map topography for decoding spatial information. Journal of Neuroscience, 36, 5385-5396.

Goodhill, G.J. (2016). Can molecular gradients wire the brain? Trends in Neurosciences, 39, 202-211.

Bicknell, B.A., Dayan, P. & Goodhill, G.J. (2015). The limits of chemosensation vary across dimensions. Nature Communications, 6, 7468.

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.

Sutherland, D.J., Pujic, Z. & Goodhill, G.J. (2014). Calcium signaling in axon guidance. Trends in Neurosciences, 37, 424–432.

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.

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.

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.

Mortimer, D., Fothergill, T., Pujic, Z., Richards, L.J. & Goodhill, G.J. (2008). Growth Cone Chemotaxis. Trends in Neurosciences, 31, 90-98.

Goodhill, G.J. (2007). Contributions of theoretical modelling to the understanding of neural map development. Neuron, 56, 301-311.

Xu, J., Rosoff, W.J., Urbach, J,S. & Goodhill, G.J. (2005). Adaptation is not required to explain the long-term response of axons to molecular gradients. Development, 132, 4545-4552.

Carreira-Perpinan, M.A., Lister, R. & Goodhill, G.J. (2005). A computational model for the development of multiple maps in primary visual cortex. Cerebral Cortex, 15, 1222-1233.

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.