Dr Andrew Lin

Andrew Lin

Vice-Chancellor's Fellow
Department of Biomedical Science
University of Sheffield
Western Bank
Sheffield S10 2TN
United Kingdom

Room: B2 228 Alfred Denny building
Telephone: +44 (0) 114 222 3643
Email: andrew.lin@sheffield.ac.uk

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Centre for Sensory Neuroscience

Brief career history

  • 2015 - present: Vice-Chancellor’s Fellow, University of Sheffield
  • 2009 - 2015: Postdoctoral fellow, University of Oxford. Advisor: Gero Miesenböck
  • 2004 - 2009: PhD, University of Cambridge. Advisor: Christine Holt
  • 2000 - 2004: AB Biology, Harvard University

Research interests

We study how the brain represents sensory information to allow it to store unique memories, using the olfactory system of the fruit fly Drosophila melanogaster as a model system.

Full Publications


Olfactory sensory coding and memory

How does the brain recognise sensory stimuli? How does it form distinct memories for different stimuli, even very similar ones? And how does it wire itself up to process information in the best way to achieve these remarkable feats? Our research addresses these fundamental questions using the olfactory system of the fruit fly Drosophila melanogaster. Flies have a much simpler nervous system than humans but are still capable of complex behaviours such as associative memory. This simplicity, combined with the power of fly genetics, makes Drosophila an excellent model system for tackling basic questions about neural circuit function.

Flies can form distinct associative memories for different odours, even very similar ones, and this stimulus-specificity depends on ‘sparse coding’, in which Kenyon cells, the neurons that encode olfactory associative memories, respond sparsely to odours, i.e. only a few neurons in the population respond to each odour. This sparse coding in turn depends on a delicate balance of excitation and inhibition onto Kenyon cells. We are studying how this balance is created and maintained. By improving our understanding of how the brain balances excitation and inhibition, this work may shed light on neurological disorders, like epilepsy, where this balance goes wrong.

Some methods we use:

  • In vivo two-photon imaging
  • Patch-clamp electrophysiology
  • Individual-fly behavioural experiments
  • Genetic manipulation of identified neurons
  • Transcriptional profiling
  • Computational modelling

Undergraduate and postgraduate taught modules

Level 3:

  • BMS349 Extended Library Project
  • BMS355 Sensory Neuroscience

Phd Project

Title: Maintaining effective sensory coding in the face of inter-neuronal variation

Supervisor 1: Dr Andrew Lin

Supervisor 2: Professor Mikko Juusola and Professor Eleni Vasilaki

Funding status: Directly funded project European/UK students only

Fully funded for 4 years, the studentship covers: (i) a tax-free stipend at the standard Research Council rate (at least £14,553/year for 2018-2019), (ii) research costs, and (iii) tuition fees at the UK/EU rate. The studentship is available to UK and EU students who meet the UK residency requirements, see http://www.bbsrc.ac.uk/documents/studentship-eligibility-pdf/. Students from EU countries who do not meet residency requirements may still be eligible for a fees-only award. See also https://www.whiterose-mechanisticbiology-dtp.ac.uk/

Project Description

When building a brain, you might think neurons should be wired together very precisely and accurately to ensure optimal performance. But nature is never perfect, and developmental variability is inevitable. How can neurons have consistent properties to allow effective sensory coding, in the face of this inherent inter-neuronal variability? This fundamental problem occurs across species, and we will address it in Drosophila, where ~2000 neurons called Kenyon cells encode olfactory associative memories.

To accurately distinguish learned associations for different odours, Kenyon cell population responses to odours must be decorrelated, i.e. different odours activate non-overlapping subsets of Kenyon cells. This inter-odour decorrelation requires Kenyon cells to be roughly equally excitable: if some Kenyon cells are more excitable than others, these same cells tend to dominate all odour responses, which increases overlap between odour representations. Yet recent work shows that Kenyon cells receive extremely variable amounts of excitatory input.

Our computational models suggest that this variability impairs odour decorrelation unless Kenyon cells compensate for variability along one parameter (e.g., amount of excitatory input) with counteracting variability along another parameter (e.g., spiking threshold). In this project, the student will test whether and how such compensatory variability occurs, and will computationally model how it would affect circuit function.

We seek a motivated and creative student with a strong interest in how the brain works. We welcome applications from candidates from a range of backgrounds (from biology to computer science or physics). In carrying out this interdisciplinary project, the student will learn a range of cutting-edge techniques, including multiphoton imaging, patch-clamp electrophysiology, fly genetics, and computational modelling. This research will have broad implications for how neurons develop and maintain the correct electrical and synaptic properties to effectively encode information and carry out behaviourally relevant computations.

Keywords: Bioinformatics, Biophysics, Cell Biology / Development, Genetics, Molecular Biology, Neuroscience/Neurology, Zoology/Animal Science, Applied Mathematics, Data Analysis


  • About the model system: Lin, A.C., Bygrave, A.M., de Calignon, A., Lee, T., Miesenböck, G. (2014). Sparse, decorrelated odor coding in the mushroom body enhances learned odor discrimination. Nature Neuroscience, 17, 559-68.
  • About compensatory variability: Marder, E., and Goaillard, J.-M. (2006). Variability, compensation and homeostasis in neuron and network function. Nat Rev Neurosci 7, 563–574.

Contact information:

For informal enquiries about the project or application process, please feel free to contact

To find out more about these projects and how to apply see our PhD opportunities page:

PhD Opportunities

Selected publications

Journal articles