The Unit shares a purpose-designed building and has close research links with the Sainsbury Wellcome Centre for Neural Circuits and Behaviour.
The Sainsbury Wellcome Centre for Neural Circuits and Behaviour (SWC), jointly 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 the Centre 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.
Linking theoretical and experimental research
Experimental research is producing more and more data as recording techniques become more advanced. This vast amount 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 generate new questions which can be experimentally tested. One of our goals is to bridge the gap between theoretical and experimental neuroscience, and the Unit has been working closely with SWC colleagues to develop ways in which we can collaborate and interact to move neuroscience forward.
We created parallel PhD programmes that incorporates taught courses on Systems and Theoretical Neuroscience (jointly taught), Experimental Neuroscience and Machine Learning in order to train a new generation of neuroscientists.
We designed a joint Gatsby-SWC postdoctoral fellowship for early career researchers who are seeking to build independence and are interested in working at the interface between experimental and theoretical neuroscience.
We developed a new joint faculty position for Machine Learning applied to Neuroscience, 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.