Neuroinformatics interfaces the fields of neuroscience with mathematics and computer science. Questions in neuroinformatics are particularly involved with understanding and modeling learning and information processing in biologically plausible networks of neurons. Many such processes are still poorly understood, and experimental neuroscience data is often open to different interpretations. Mathematical modeling combined with insights and techniques from statistical machine learning and estimation are key methods for progress in this area (Bothe, S. 2016).

Neuroinformatics is a research field rooted in classical disciplines like signal processing, biology, physics, computer science and engineering. Neuroinformatics combines learning from the brain and learning about the brain. By studying information processing in the brain neuroinformatics invents new computing paradigms (e.g., artificial neural networks) with the objective of understanding the dynamics of the conscious mind (THOR Center for Neuroinformatics, 2016).