Great efforts are being made to map the "connectome" the neuronal wiring diagram of brain circuits. But mapping the static connectome will not suffice for an understanding of the computations that these circuits perform, because during these computations the static connectome is dynamically modified by a complex network of diffusible modulatory neurochemicals. As yet, no experimental system has come close to providing a full understanding of this modulatory system and its functional role. The problem is that there are invariably many modulators present simultaneously, with mutually interacting effects. To understand the operation of the entire modulatory system, a global overview of the simultaneous effects of all possible modulator combinations is required. By brute force, this would take a vast number of experiments.
This project will test a simple yet powerful solution to this problem. The heart of the solution lies in a combinatorial algorithm that compacts all of the modulator combinations to a tractably small number of combinations whose testing is sufficient. Using mathematical modeling in conjunction with experimental neurophysiological methods, this approach will be developed and tested in a neuromuscular system that is simple and experimentally tractable, yet can yield generally relevant principles. The larger goal of the work is to demonstrate a coherent, integrated strategy for the study of highly multidimensional modulatory systems. This strategy will allow the full modulatory complexity of brain circuits to be studied for the first time and answer broader questions about the design of neural systems and their modulatory control. This project will integrate experiments with mathematical modeling and theory, and train students, including minorities and women, in both areas. Furthermore, cross-fertilization is anticipated with areas of technology in which a compact combinatorial test set can simplify work with the complex, dynamic, modulated systems that are becoming common also in today's technological environment.
