Geoffrey Goodhill, PhD

Professor of Neuroscience & Professor of Developmental Biology

Goodhill Lab


The Goodhill laboratory’s overall goal is to understand the computational principles that underlie brain development, using a combination of experimental and theoretical approaches. Previously the lab has 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.

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 GJ. Spontaneous and evoked activity patterns diverge over development. eLife. 2021; 10:e61942.
  • Avitan L, Pujic Z, Molter J, McCullough M, Zhu S, Sun B, Myhre A-E, Goodhill GJ. Behavioral signatures of a developing neural code. Current Biology. 2020; 30:3352-3363.
  • Triplett M, Pujic Z, Sun B, Avitan L, Goodhill GJ. Model-based decoupling of evoked and spontaneous neural activity in calcium imaging data. PLoS Computational Biology. 2020; 16:e1008330.
  • Avitan L, Goodhill GJ. Code under construction: neural coding over development. Trends in Neurosciences. 2018; 41:599-609.
  • Triplett MA, Avitan L, Goodhill GJ. Emergence of spontaneous assembly activity in developing neural networks without afferent input. PLoS Computational Biology. 2018; 14:e1006421.
  • Avitan L, Pujic Z, Moelter J, Van De Poll M, Sun B, Teng H, Amor R, Scott EK, Goodhill GJ. Spontaneous activity in the zebrafish tectum reorganizes over development and is influenced by visual experience. Current Biology. 2017; 27:2407-2419.
  • Hughes NJ, Goodhill GJ. Estimating cortical feature maps with dependent Gaussian processes. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2017; 39(10):1918-1928.
  • Bicknell BA, Goodhill GJ. The emergence of ion channel modal gating from independent subunit kinetics. Proc Natl Acad Sci USA. 2016; 113:E5288-97.
  • Cloherty SJ, Hughes NJ, Hietanen MA, Bhagavatula PS, Goodhill GJ, Ibbotson MR. Sensory experience modifies feature map relationships in visual cortex. eLife.2016; 5:e13911.
  • Avitan L, Pujic Z, Hughes NJ, Scott EK, Goodhill GJ. Limitations of neural map topography for decoding spatial information. Journal of Neuroscience. 2016; 36:5385-5396.
  • Goodhill GJ. Can molecular gradients wire the brain? Trends in Neurosciences. 2016; 39:202-211.
  • Bicknell BA, Dayan P, Goodhill GJ. The limits of chemosensation vary across dimensions. Nature Communications. 2015; 6:7468.
  • Suarez R, Fenlon LR, Marek R, Avitan L, Sah P, Goodhill GJ, Richards LJ. Balanced interhemispheric cortical activity is required for correct targeting of the corpus callosum. Neuron. 2014; 82:1289-1298.
  • Sutherland DJ, Pujic Z, Goodhill GJ. Calcium signaling in axon guidance. Trends in Neurosciences. 2014; 37:424–432.
  • Forbes EM, Thompson AW, Yuan J, Goodhill GJ. Calcium and cAMP levels interact to determine attraction versus repulsion in axon guidance. Neuron. 2012; 74:490-503.
  • Mortimer D, Pujic Z, Vaughan T, Thompson AW, Feldner J, Vetter I, Pujic Z, Goodhill GJ. Axon guidance by growth-rate modulation. Proc Natl Acad Sci USA. 2010; 107:5202-5207.
  • Mortimer D, Feldner J, Vaughan T, Vetter I, Pujic Z, Rosoff WJ, Burrage K, Dayan P, Richards LJ, Goodhill GJ. A Bayesian model predicts the response of axons to molecular gradients. Proc Natl Acad Sci USA. 2009; 106:10296-10301.
  • Mortimer D, Fothergill T, Pujic Z, Richards LJ, Goodhill GJ. Growth cone chemotaxis. Trends in Neurosciences. 2008; 31:90-98.
  • Goodhill GJ. Contributions of theoretical modelling to the understanding of neural map development. Neuron. 2007; 56:301-311.
  • Xu J, Rosoff WJ, Urbach JS, Goodhill GJ. Adaptation is not required to explain the long-term response of axons to molecular gradients. Development. 2005; 132:4545-4552.
  • Carreira-Perpinan MA, Lister R, Goodhill GJ. A computational model for the development of multiple maps in primary visual cortex. Cerebral Cortex. 2005; 15:1222-1233.
  • Rosoff WJ, Urbach JS, Esrick M, McAllister RG, Richards LJ, Goodhill GJ. A new chemotaxis assay shows the extreme sensitivity of axons to molecular gradients. Nature Neuroscience. 2004; 7:678-682.

See a complete list of Dr. Goodhill’s publications on Google Scholar.


1986 BSc Joint Mathematics and Physics, University of Bristol

1988 MSc Artificial Intelligence, University of Edinburgh

1992 PhD Cognitive Science, University of Sussex

Selected honors

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