Brain functions such as perception, learning and emotion are generated by the activity patterns of neurons dynamically interacting within their circuits. Today we have a detailed understanding of the computational capacity of single neurons. In contrast, the principles governing information processing once neurons are connected into circuits are still poorly understood. Research addressing this question has recently received a strong boost through the development of several new experimental approaches that allow high-resolution dissection of circuit function (in vivo 2-photon microscopy, transgenic mouse lines, viral vectors and optogenetics). We apply these techniques to investigate information processing in sensory areas of neocortex during perception and learning. Our research is guided by some key principles:
1. Circuits are best studied in their native environment, with inputs and outputs intact- i.e. we perform most experiments in vivo.
2. Circuits are composed of a rich diversity of neuron types with highly specialized function. We perform cell-type specific experiments to determine each neuron type’s contribution to circuit function.
3. Circuits are complex systems, making it difficult to extrapolate or generalize their function between different conditions. Thus, our experiments aim to model the brain function under investigation as closely as possible- mainly we study circuit activity during behavior.