Overview
We apply quantitative and computational methods from computing, physics, and engineering to describe aand study brains from first principles. We are especially interested in how the brain copes with uncertainty and noise (Faisal et al., 2008, Nature Rev Neurosci) when processing information. These two factors have profound implications for information processing and are bound to have shaped the design of the nervous system and the way it controls and learns (movement) behaviour.

Research in the Faisal Lab operates using a multi-resolution approach encompassing several levels of biological organisation: from molecules to whole body movements. This involves, on the one side, modelling from the bottom-up signalling molecules, neurons and neutral circuits from first biophysical principles (e.g. Faisal et al., 2007, PLOS CB). On the other side analysing from the top-down human learning and motor behaviour together with conducting psychophysics experiments using virtual reality and robotic interfaces to test these theories in a quantitative setting (e.g. Faisal & Wolpert, 2009, J.Neurophys.).

In four experimental collaborations we drive this approach to:

development of neural circuits
the link between genes and behaviour
electrophysiology in the sensorimotor loop
the evolution of skilled human tool manipulation
As part of this research programme the Faisal Lab is developing a Bioinformatics of Behaviour, i.e. methods to automatically annotate, quantify and analyse large-scale data sets of human and animal behaviour.

Our research has been featured both in the academic press (e.g Nature) as well as in print media (e.g. New Scientist) and TV (e.g. Discovery TV). More on our research programme is on the Faisal Lab website.