Stereology is a valuable tool for scientists, allowing them to make 3-D reconstructions of the brain from 2-D data (as usually obtained from PET or MRI scans). Such 3-D reconstructions allow a far greater understanding of brain function. However, in carrying out such reconstructions, often based on limited or incomplete data, there is always a risk of experimenter bias. An important function of stereology is to eliminate bias in the data. With many of the major neuroscience journals now insisting that data be presented in this way, there is a greater need than ever for neuroscientists to understand 'unbiased' quantitative methods, such as those offered by stereology. This volume is a cookbook of stereological methods written especially for neuroscientists. It provides clear and accessible advice about when and when not to use stereology. Throughout the book, the emphasis is on practical guidance, rather than discussions and formulae. Written by leading scientists in the field of stereology, the book will be a valuable introduction to these methods for neuroscientists, and all those involved in development of new drug programmes.