In Silico: Simulators, Emulators and the Human Brain Project
The European Human Brain Project, a flagship project of the European Union, recently ended after 10 years of research and development. The goals of the HBP were to (1) explore the complexity of the human brain in space and time; (2) to transfer the knowledge broadly; (3) to provide research infrastructure for neuro-science; and (4) to create a community of researchers. One of the major challenges is to model neural activity, from micro- to macro-scale, in a way that enables simulation of the human brain. This leads to so-called in silico experiments, which will be used “to validate models, and to perform investigations that are not possible in the laboratory”. I will present examples of such experiments and discuss how they relate to, and can benefit from, statistical research on the design and analysis of computer experiments. My students and colleagues and I have been working on the potential advantages of replacing a slow/expensive simulator with a much faster and cheaper statistical emulator. Emulators are empirical replicas trained on data generated with the simulator. We have often used Gaussian process regression for this purpose, but in some applications other methods (random forests, polynomial regression) proved more effective. Emulators can be especially useful when the simulator runs are matched to data in the context of statistical inference. I will discuss the modeling options and present examples, including simulation of neural basket cells, calcium induced neural reactions, and stochastic simulators like the Hodgkin-Huxley model.