Mammalian neuronal cells represent one of the most sophisticated and complex signaling and processing systems in any living organism. Many diseases, such as Alzheimer’s and Parkinson’s disease or amyotrophic lateral sclerosis, have their genesis in disturbed processes on nerve cells. The study of the mechanisms of the physiological changes in nerve cells, which are induced by stressors such as neuroinhibitors or analgesics, represents one way to obtain helpful information for understanding such neural disorders and opens the way for the development of treatments. However, new drugs for ef–cient treatments of such diseases are the products of a long development process, the –rst step of which is often the discovery of a new enzyme inhibitor. In the past, the only way to identify such novel inhibitors was a “trial and error” principle: screening huge libraries of compounds against a target enzyme and studying the response in the hope that useful results would emerge. This “brute force” approach is to some extent successful and has even been extended by combinatorial chemistry approaches capable of producing large numbers of novel compounds quickly, as well as by high-throughput screening technologies to rapidly screen these huge chemical libraries for useful inhibitors. However, despite the increasing demand for highthroughput functional screening methods in the areas of environmental protection, toxicology, and drug development [1-5], these methods are not yet ef–cient in the case of cellular measurements [3,5,6].