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+layout: page
+title: SPAD-baseed high speed imaging
+importance: 1
+category: work
+related_publications: true
+img: assets/img/grid_cell.png
+---
+
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+Recent progress towards understanding the biological basis for cognition and its disorders has been driven by advances in molecular tools for labelling and manipulation of defined populations of neurons. However, brain circuits operate at a millisecond time scales and our ability to resolve this activity is limited. Electrophysiological methods have the required temporal precision, but do not reliably identify multiple individual neurons within large populations, a pre-requisite for many important questions. In contrast, imaging approaches based on detection of intracellular Ca2+ signals can track activity in large populations of neurons but give only an indirect readout of neuronal activity with limited temporal resolution. New genetically encoded voltage indicators (GEVIs) address many of the shortcomings of Ca2+ imaging. Crucially, they report both action potentials and subthreshold electrical activity in defined neurons with millisecond resolution. However, application of GEVIs will require a new generation of cameras with frame rates sufficient to monitor millisecond scale changes.
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+We propose to validate cameras based on Single Photon Avalance Diode (SPAD) sensor technology developed in the School of Engineering by Robert Henderson and colleagues. SPADs are electronic devices that when activated by a single photon cause an avalanche of electrons and a large electric current. Because SPADs detect the time at which individual photons arrive, they are well suited to extremely high speed and low light imaging. In contrast, standard camera sensors must bin photons across a time window, which limits their sensitivity and temporal resolution. In our prototype SPAD-based cameras, the sensor chip is a similar size to sensors used in miniature microscopes we currently use for Ca2+ imaging in behaving rodents. It is therefore physically feasible to use SPADs to image activity even in freely behaving animals.
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+What are the obstacles to application of SPAD technology and how can we overcome them? The key immediate challenge addressed here is to obtain proof-of-principle data that SPAD-based cameras can detect neuronal activity reported with GEVIs. This requires that we introduce viruses encoding GEVIs into a mouse brain, generate known activity patterns in neurons expressing the GEVIs and use the SPAD cameras to image the signal from the GEVIs. With these data, we will be in a strong position to obtain larger funding to develop and validate SPAD-based cameras suitable for widespread use (see Exit Strategy).
+