Gatsby Computational Neuroscience Unit


Sainsbury Wellcome Centre

We share a purpose-designed building and have strong working relationship with the Sainsbury Wellcome Centre for Neural Circuits and Behaviour.


The Sainsbury Wellcome Centre for Neural Circuits and Behaviour (SWC), funded by the Gatsby Charitable Foundation and the Wellcome Trust, aims to understand how computation in neural circuits gives rise to flexible, complex behaviour.

The brain is remarkable in its ability to produce a rich array of inbuilt and learned behaviours, which are deployed flexibly to meet individuals’ needs and environmental demands. Behaviour emerges from distributed computations in specialised neural circuits across brain regions, with the same regions often contributing to multiple behaviours. How networks of neurons give rise to this adaptive and complex repertoire of function is a fundamental scientific question of our era. Research at SWC seeks to identify a set of elemental neural computations that underlie different behaviours and determine how they are implemented at the level of circuits, cells and synapses, with the long-term goal to use this knowledge to build a coherent theoretical framework that combines these neural computations and explains how complex behavioural processes relate to neural circuit mechanisms.

For more information, please visit its official website www.sainsburywellcome.org/web.


Linking theoretical and experimental research

Experimentalists are generating more and more data as recording techniques become more advanced. This large amount (and variety) of data will require sophisticated data analysis tools that can pick up meaningful signals from a lot of noise. Equally, analysis of existing datasets can also motivate new questions that can be be tested/validated experimentally. One of the goals of the Gatsby Computational Neuroscience Unit (GCNU) is to bridge the gap between theoretical and experimental neuroscience, and we have been working closely with SWC colleagues to develop mechanisms in which we can collaborate and interact to move neuroscience forward. 

  • To train a new generation of neuroscientists, we have developed parallel PhD programmes (ours and SWC's) that incorporates courses on Systems and Theoretical Neuroscience (jointly taught), Experimental Neuroscience and Machine Learning. 
  • We have designed a joint GCNU-SWC postdoctoral fellowship for early career researchers who are seeking to build research independence and are interested in working at the interface between theoretical and experimental neuroscience.
  • We have created a joint GCNU-SWC Group Leader position for Machine Learning applied to Neuroscience (Andrew Saxe), with the ambition to apply theoretical and machine learning tools to systems neuroscience questions.
  • In addition, our faculty members are actively collaborating and engaging with SWC colleagues with joint research projects and working group.