An architecture for distributed data analysis problem solving in neurophysiology

The growth of volume and variety of data in the field of neurophysiology increases the need of the application of computer science methods such as statistical analysis, machine learning, and neural networks for the data analysis. Infrastructures providing storage of a large volume of data in neurophysiology as well as data distributed processing and analysis are required. This article proposes a software architecture for the problem solving based on the Hadoop distributed storage and analysis framework and GPU-assisted high-performance computing technologies.