MNE Scan

We are excited to present the newest addition to MNE-Scan: A plugin that utilizes the lab streaming layer (LSL) library in order to enable real-time streaming of EEG data. LSL is widely used in the field of electrophysiology and is supported by many EEG systems, either via vendor-provided software or dedicated programs supplied as part of the LSL distribution. The LSL library features extensive network support, thus enabling highly distributed […]

MNE Scan support for LSL

We are excited to present the newest feature of MNE-CPP: Real-Time capable visualization of EEG/MEG sensor data. During a student project several new key features were implemented, which are described below. First a method to project sensors to the mesh, which is to be interpolated on, was implemented.  The projection is needed because sensor positions may be somewhat above the vertices of the used mesh. In order to interpolate signals, […]

Visualization of EEG/MEG Sensor Data

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:  

MNE-CPP in the News

Our MNE Scan software can be used to acquire and process electrophysiological data in real-time. MNE Scan includes several sensor plugins, which can be used to connect to different devices. As of right now MNE Scan is able to connect to the following devices and thus provide an internal data stream for subsequent real-time processing: EEG devices EEGoSports (ANT Neuro) TMSI Refa gUSBAmo (g.Tec) BrainAmp (Brain Products) MEG Elekta Neuromag […]

MNE Scan: Improved Device Support

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

Brain-Computer-Interfaces (BCIs) provide a novel way of communication by  interpreting different types of brain states. This principle of reading minds makes BCIs a challenging but at the same time fascinating topic among the different disciplines of electrophysiology and biomedical-signal-processing. Every BCI is dependent on a specific mental strategy. The mental strategy, or paradigm, can be seen as the BCI’s core translation algorithm, which defines specific brain activation induced by the […]

MNE Scan: Merging Brain and Computer with BCIs