The classification of cell types that make up the brain has long been recognized as a prerequisites to understanding brain function. In addition, relating identified neurons to neural function has relied heavily on their inactivation. To answer such questions a tool that allows one to reliably target specific cells for recording, labeling and manipulation is needed. Here I describe a multidisciplinary approach that will allow us to both identify and characterize local interneurons, as well as determine their role in specific neuronal circuits. The methodology makes use of transgenic technologies to identify and label specific neurons and manipulate local circuit activity, electrophysiology and functional imaging to monitor the activity of labeled cells and computational modeling to understand the information processing performed. Our model system is the mouse retina because it is easy to isolate, maintain in vitro and its neural activity can be easily monitored. Transgenic technologies will play two key roles in this project. First, transgenic mice with genetically labeled cells will be used to classify single neuronal types, allowing us to repeatedly record from the identified cells. Second, genetically identified amacrine cells will be endowed with exogenous proteins that allow for either their reversible activation or inactivation. The specific activation of identified amacrine cells will allow us identify the ganglion cells they innervate, while their inactivation gives a tool to assess their role in the local circuit. By monitoring the affects on ganglion cells of activating and inactivation identified amacrine cells we will be able to define a local neuronal circuit, determine the circuits role in retinal visual processing and ascertain how the specified interneuron affects visual processing. This work will take our understanding of retinal visual information forward while the techniques developed will be applicable to studying other brain regions