Professor Geoffrey Goodhill

NHMRC Leadership Fellow

Queensland Brain Institute

NHMRC Leadership Fellow

Mathematics
Faculty of Science
g.goodhill@uq.edu.au
+61 7 334 66431

Overview

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. He is addressing these questions using a combination of mathematical, experimental and computational techniques. Members of the lab come from diverse backgrounds including biology, mathematics, physics and computer science.

Prof Goodhill originally trained in Mathematics, Physics, Artificial Intelligence and Cognitive Science in the UK. He then spent 10 years in the USA, including 8 as Professor at Georgetown University in Washington DC, where he was awarded tenure 2 years early. He moved to the University of Queensland in 2005. He has published over 100 peer-reviewed papers including in Nature Neuroscience, 4 in Neuron, 4 in PNAS and 8 in Trends in Neurosciences. In 2014 he received the Paxinos-Watson prize from the Australasian Neuroscience Society for a paper in Neuron. Since moving to Australia he has been awarded an NHMRC Investigator grant, 12 ARC Discovery and NHMRC Project grants and a Simons Foundation grant as Chief Investigator A, as well as numerous other national and international grants as a co-CI. He has trained over 30 PhD students and postdocs, many of whom are now faculty members in universities worldwide, or work as scientists in tech companies such as Google Deepmind. From 2005-2010 he was Editor-in-Chief of the journal Network: Computation in Neural Systems, and he is currently on the Editorial Boards of Neural Computation and Brain Informatics. He has reviewed manuscripts for over 60 different journals and grants for 15 different research agencies worldwide. In 2006 he founded the Australian Workshop on Computational Neuroscience which now runs annually, and in 2015 he founded the Systems and Computational Neuroscience DownUnder (SCiNDU) conference which now runs bi-annually. During his career he has taught courses in Medical Neuroscience, Developmental Neuroscience, Mathematical Neuroscienc, Numeral Methods and Scientific Computing. Besides giving many radio interviews and public lectures about his work he has also written several articles for The Conversation and given a TEDx talk.

Research Interests

  • Computational Neuroscience / Systems Neuroscience / Neural Development
    See www.goodhill.org

Qualifications

  • Master of Information Technolohy, University of Edinburgh
  • Doctor of Philosophy, University of Sussex
  • Bachelor of Science, University of Bristol

Publications

  • Avitan, Lilach, Pujic, Zac, Mölter, Jan, McCullough, Michael, Zhu, Shuyu, Sun, Biao, Myhre, Ann-Elin and Goodhill, Geoffrey J. (2020). Behavioral signatures of a developing neural code. Current Biology, 30 (17), 3352-3363.e5. doi: 10.1016/j.cub.2020.06.040

  • Mölter, Jan, Avitan, Lilach and Goodhill, Geoffrey J. (2018). Detecting neural assemblies in calcium imaging data. BMC Biology, 16 (1) 143, 143. doi: 10.1186/s12915-018-0606-4

  • Avitan, Lilach and Goodhill, Geoffrey J (2018). Code under construction: neural coding over development. Trends in Neurosciences, 41 (9), 599-609. doi: 10.1016/j.tins.2018.05.011

  • Hughes, Nicholas J. and Goodhill, Geoffrey J. (2017). Estimating cortical feature maps with dependent Gaussian processes. IEEE Transactions On Pattern Analysis and Machine Intelligence, 39 (10) 7731172, 1918-1928. doi: 10.1109/TPAMI.2016.2624295

  • Avitan, Lilach, Goodhill, Geoffrey J., Pujic, Zac, Molter, Jan, Van De Poll, Matthew, Sun, Biao, Teng, Haotian, Amor, Rumelo and Scott, Ethan K. (2017). Spontaneous Activity in the Zebrafish Tectum Reorganizes over Development and Is Influenced by Visual Experience. Current Biology, 27 (16), 2407-2419. doi: 10.1016/j.cub.2017.06.056

  • Cloherty, Shaun L., Hughes, Nicholas J., Hietanen, Markus A., Bhagavatula, Partha S., Goodhill, Geoffrey J. and Ibbotson, Michael R. (2016). Sensory experience modifies feature map relationships in visual cortex. eLife, 5 (JUN2016) e13911. doi: 10.7554/eLife.13911

  • Avitan, Lilach, Pujic, Zac, Hughes, Nicholas J., Scott, Ethan K. and Goodhill, Geoffrey J. (2016). Limitations of neural map topography for decoding spatial information. Journal of Neuroscience, 36 (19), 5385-5396. doi: 10.1523/JNEUROSCI.0385-16.2016

  • Goodhill, Geoffrey J. (2016). Can molecular gradients wire the brain?. Trends in Neurosciences, 39 (4), 202-211. doi: 10.1016/j.tins.2016.01.009

  • Bicknell, Brendan A. and Goodhill, Geoffrey J. (2016). Emergence of ion channel modal gating from independent subunit kinetics. Washington, DC, United States: National Academy of Sciences. doi: 10.1073/pnas.1604090113

  • Bicknell, Brendan A., Dayan, Peter and Goodhill, Geoffrey J. (2015). The limits of chemosensation vary across dimensions. Nature Communications, 6 (7468) 7468, 1-8. doi: 10.1038/ncomms8468

  • Goodhill, Geoffrey J., Faville, Richard A., Sutherland, Daniel J., Bicknell, Brendan A., Thompson, Andrew W., Pujic, Zac, Sun, Biao, Kita, Elizabeth M. and Scott, Ethan K. (2015). The dynamics of growth cone morphology. BMC Biology, 13 (10) 10, 1-16. doi: 10.1186/s12915-015-0115-7

  • Suarez, Rodrigo, Fenlon, Laura R., Marek, Roger, Avitan, Lilach A, Sah, Pankaj, Goodhill, Geoffrey J. and Richards, Linda J. (2014). Balanced interhemispheric cortical activity is required for correct targeting of the corpus callosum. Neuron, 82 (6), 1289-1298. doi: 10.1016/j.neuron.2014.04.040

  • Sutherland, Daniel J., Pujic, Zac and Goodhill, Geoffrey J. (2014). Calcium signaling in axon guidance. Trends in Neurosciences, 37 (8), 424-432. doi: 10.1016/j.tins.2014.05.008

  • Forbes, Elizabeth M., Thompson, Andrew W., Yuan, Jiajia and Goodhill, Geoffrey J. (2012). Calcium and cAMP levels interact to determine attraction versus repulsion in axon guidance. Neuron, 74 (3), 490-503. doi: 10.1016/j.neuron.2012.02.035

  • Mortimer, D., Pujic, Z., Vaughan, T., Thompson, A. W., Feldner, J., Vetter, I. and Goodhill, G. J. (2010). Axon guidance by growth-rate modulation. Proceedings of the National Academy of Sciences of the United States of America, 107 (11), 5202-5207. doi: 10.1073/pnas.0909254107

  • Mortimer, Duncan, Feldner, Julia, Vaughan, Timothy, Vetter, Irina, Pujic, Zac, Rosoff, William J., Burrage, Kevin, Dayan, Peter, Richards, Linda J. and Goodhill, Geoffrey J. (2009). A Bayesian model predicts the response of axons to molecular gradients. Proceedings of the National Academy of Sciences of the United States of America, 106 (25), 10296-10301. doi: 10.1073/pnas.0900715106

  • Mortimer, Duncan, Fothergill, Thomas, Pujic, Zac, Richards, Linda J. and Goodhill, Geoffrey J. (2008). Growth cone chemotaxis. Trends in Neurosciences, 31 (2), 90-98. doi: 10.1016/j.tins.2007.11.008

  • Goodhill, G. J. (2007). Contributions of theoretical modeling to the understanding of neural map development. Neuron, 56 (2), 301-311. doi: 10.1016/j.neuron.2007.09.027

  • Rosoff, W. J., Urbach, J. S., Esrick, M. A., McAllister, R. G., Richards, L. J. and Goodhill, G. J. (2004). A new chemotaxis assay shows the extreme sensitivity of axons to molecular gradients. Nature Neuroscience, 7 (6), 678-682. doi: 10.1038/nn1259

View all Publications

Publications

Featured Publications

Book Chapter

  • Pujic, Zac, Nguyen, Huyen, Glass, Nick, Cooper-White, Justin and Goodhill, Geoffrey J. (2016). Axon guidance studies using a microfluidics-based chemotropic gradient generator. In 2nd (Ed.), Chemotaxis: methods and protocols (pp. 273-285) New York, NY United States: Springer New York. doi:10.1007/978-1-4939-3480-5_20

  • Mortimer, Duncan, Simpson, Hugh D. and Goodhill, Geoffrey J. (2012). Axonal growth and targeting. Computational systems neurobiology. (pp. 429-458) edited by Nicolas Le Novère. Dordrecht, Netherlands: Springer. doi: 10.1007/978-94-007-3858-4_14

  • Mortimer, D. and Goodhill, G. J. (2009). Axonal Pathfinding. Encyclopedia of Neuroscience. (pp. 1133-1138) edited by Marc D. Binder, Nobutaka Hirokawa and Uwe Windhorst. Berlin, Germany: Elsevier Ltd. doi: 10.1016/B978-008045046-9.01412-1

  • Rosoff, William J., McAllister, Ryan G., Goodhill, Geoffrey J. and Urbach, Jeffrey S. (2009). Quantitative studies of neuronal chemotaxis in 3D. Chemotaxis: methods and protocols. (pp. 239-254) edited by Tian Jin and Dale Hereld. New York, United States: Humana Press. doi: 10.1007/978-1-60761-198-1

Journal Article

Conference Publication

  • Bicknell, Brendan A., Dayan, Peter and Goodhill, Geoffrey J. (2017). Sensitivity and Robustness in an Axon Guidance Signaling System. 61st Annual Meeting of the Biophysical-Society, New Orleans La, Feb 11-15, 2017. CAMBRIDGE: CELL PRESS. doi: 10.1016/j.bpj.2016.11.752

  • Bicknell, Brendan A. and Goodhill, Geoffrey J. (2016). Emergence of ion channel modal gating from independent subunit kinetics. Washington, DC, United States: National Academy of Sciences. doi: 10.1073/pnas.1604090113

  • Huang, Jackson Y., Hughes, Nicholas J. and Goodhill, Geoffrey J. (2016). Segmenting neuronal growth cones using deep convolutional neural networks. International Conference on Digital Image Computing - Techniques and Applications (DICTA), Gold Coast, Australia, 30 November-2 December 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/DICTA.2016.7797081

  • Goodhill, Geoff (2012). Computational models of map development in visual cortex. The Royal Australian and New Zealand College of Ophthalmologists 44th Annual Scientific Congress, Melbourne, Australia, 24-28 November 2012. Richmond, VIC., Australia: Wiley-Blackwell Publishing Asia. doi: 10.1111/ceo.12011

  • Carreira-Perpinan, M., Dayan, P. and Goodhill, G. J. (2005). Differential Priors for Elastic Nets. IDEAL 2005, Brisbane Australia, July 6-8. Berlin: Springer. doi: 10.1007/11508069_44

  • Urbach, JS and Goodhill, GJ (1999). Limitations on detection of gradients of diffusible chemicals by axone. 7th Annual Computational Neuroscience Meeting (CNS 98), Santa Barbara Ca, Jul, 1998. AMSTERDAM: ELSEVIER SCIENCE BV.

  • Goodhill, GJ (1998). A mathematical model of axon guidance by diffusible factors. 11th Annual Conference on Neural Information Processing Systems (NIPS), Denver Co, Dec 01-06, 1997. CAMBRIDGE: M I T PRESS.

  • Goodhill, Geoffrey J. (1998). Gradients for retinotectal mapping. 11th Annual Conference on Neural Information Processing Systems, NIPS 1997, , , December 1, 1997-December 6, 1997. Neural information processing systems foundation.

  • Goodhill, GJ and Sejnowski, TJ (1997). Objective functions for topography: A comparison of optimal maps. 4th Neural Computation and Psychology Workshop (NCPW4), London England, Apr 09-11, 1997. GODALMING: SPRINGER-VERLAG LONDON LTD.

  • Goodhill, GJ, Finch, S and Sejnowski, TJ (1996). Optimizing cortical mappings. 9th Annual Conference on Neural Information Processing Systems (NIPS), Denver Co, Nov 27-30, 1995. CAMBRIDGE: M I T PRESS.

  • Goodhill, G.J. and Sejnowski, T.J. (1996). Quantifying neighbourhood preservation in topographic mappings. 3rd Joint Symposium on Neural Computation, La Jolla, CA United States, 1 June 1996. La Jolla, CA United States: University of California.

  • Zamoraramos, C and Goodhill, GJ (1994). A Neural Computation - Spatial to Temporal Transformation. Satellite Workshop on Information Processing Underlying Gaze Control, at the 16th European-Neuroscience-Association Meeting, Seville Spain, Sep 22-24, 1993. OXFORD: PERGAMON PRESS LTD.

  • Dayan, P and Goodhill, G (1992). Perturbing Hebbian Rules. 5Th Conf On Neural Information Processing Systems - Natural and Synthetic ( Nips-91 ), Denver Co, Dec 02-05, 1991. SAN MATEO: MORGAN KAUFMANN PUB INC.

  • Goodhill, G (1991). Topography and Ocular Dominance Can Arise From Distributed Patterns of Activity. International Joint Conf On Neural Networks ( Ijcnn-91-Seattle ), Seattle Wa, Jul 08-12, 1991. NEW YORK: I E E E.

  • Hinton, Geoffrey E., McClelland, James L. and Goodhill, Geoffrey J. (1987). LEARNING REPRESENTATIONS BY RECIRCULATION. 1987 IEEE Conference on Neural Information Processing Systems - Natural and Synthetic., , , IEEE.

Other Outputs

Grants (Administered at UQ)

PhD and MPhil Supervision

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.