MNE Lib


Elon Musk and Facebook recently presented their fascinating ideas to connect the computer directly with the brain. In this context, the MDR a central German broadcasting station featured MNE-CPP in their article about Brain Computer interfaces. Link to article: http://www.mdr.de/wissen/faszination-technik/computer-gehirn-anschluss-100.html  

MNE-CPP in the News


In the latest release (MNE-CPP v1.0.0-beta 3.0) we incorporated a technical preview of MNE Deep a deep learning library which facilitates Microsoft’s CNTK. CNTK is a framework which allows to analyze and reveal relations in massive datasets through deep learning by providing uncompromised scaling, speed and accuracy. The new MNE Deep library is used in the Brain Inside Out (BIO) project for modeling of brain structures with deep neuronal networks. MNE Deep also […]

Deep Learning with MNE-CPP


Magnetoencephalography (MEG) and Electroencephalography (EEG) provides high temporal resolution which allows a detailed investigation of time related neuronal activation properties. In real-time analysis two major challenges have to be handled: the low signal-to-noise ratio (SNR) and the limited time available for computations. We recently proposed Real-Time Clustered Multiple Signal Classification (RTC-MUSIC) as a real-time source localization algorithm, which can handle low SNRs and can cope with the high computational effort. It […]

RTC-MUSIC: Real-Time Source Localization



Together with our partners at the Boston Children’s Hospital (Harvad Medical School) we provided the software MNE Scan to acquire and process data from the novel BabyMEG system in real-time. The BabyMEG is a wohle head pediatric MEG system, which is able to measure kids up to three years of age. The BabyMEG is equipped with 270 inner layer magnetometers and 35×3-axis outer layer sensors. By using a recycling system, […]

BabyMEG: Real-Time Data Processing


In the past months the MNE-CPP team has been improving the disp3D library and adding new features for better data visualization. The recent release of Qt 5.7 brought much anticipated updates and new modules into the field. QtCharts module was implemented for data analysis in the form of distribution histogram. This will show the distribution of EEG and MEG data. In addition, users will now be able to effortlessly hide […]

New 3D Visualization Features


During the last week the MNE-CPP team started to work on the new 3D library, called disp3D. The library is based on the new Qt3D module, which just has been released as a module in the current Qt version. The main benefit when using the Qt3D module is the fact that we do not have to work with low level OpenGL routines. This makes handling 3D stuff way easier, especially for none OpenGL experts. Also, […]

Real-Time 3D Visualization with MNE-CPP



RAP-MUSIC Algorithm GPU (CUDA 4.0) implementation is finished. To realize RAP-MUSIC real-time source localization we reduce in a first step the computational costs by modifying and pre-calculating components of the subspace correlation. In a second step we apply to the accelerated algorithm a modified Powell’s Conjugate Gradient Method, which highly optimizes the search process. Since the subspace correlations of the RAP-MUSIC algorithm are independent, they are predestined to be computed […]

RAP-MUSIC GPU Implementation