The Human Neocortical Neurosolver (HNN) is a new user-friendly software package for circuit level interpretation of human EEG/MEG data. The foundation of HNN is a computational neural model that simulates the electrical activity of the neocortical cells and circuits that generate the primary electrical currents underlying EEG/MEG recordings. HNN is a free open source package that was designed for researchers and clinicians, without computational neural modeling experience, to develop and test hypothesis on the circuit origin of their data. Tutorials are provided on how to import your data and to begin to understand the underlying neural mechanisms. The tutorials focus on some of the most commonly measured signals, including event related potentials and low frequency alpha, beta, and gamma rhythms. HNN developers are eager to help users get started and have developed a user forum for feedback and questions. HNN is distributed at https://hnn.brown.edu.
HNN is being developed by a collaborative team at Brown, MGH, and Yale. HNN developments are funded by the National Institute of Biomedical Imaging and Bioengineering through the BRAIN Initiative: Theories, Models, and Methods of Analysis of Complex Data from the Brain. Contact: Dr. Stephanie R. Jones (Stephanie_Jones@Brown.edu).