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Developed by neurophysiologist and clinical epilepsy researcher, Matt Stead MD, PhD,
specifically for the collection, analysis and sharing of continuous, long term big data.
See Example Datasets
"Our lab is is mix of Linux, Windows, & Mac platforms, using Python & Matlab tools for analysis. The MED format & free tools from Dark Horse Neuro make this combination seamless. MED's compression & throughput make storing & analyzing our large, varied data sets simple & fast. We are aware of no comparable data solutions."
Mayo Clinic, Rochester MN, United States
"When we started using MED in our signal-processing lab, it was like someone took care of almost all our problems. I have worked with EEG signals for more than ten years, tried different formats: (EDF, BrainVision, etc.), MED is revolutionary, straightforward, fast, and has unbelievably good compression. It seems like the only option, especially when sharing data."
Czech Academy of Sciences, Brno, Czech Republic
"We are currently converting all of our data to the MED format and are pleased with the results. The MED format is very efficient and allows for a great gain in storage capacity. DHN is also very helpful and open to suggestions for enhancing the MED tools."
Centre National de la Recherche Scientifique, Toulouse, France
"Dark Horse Neuro is the choice solution for high-density electrophysiological recordings. Intuitive interfaces with viewing and processing tools in Matlab & Python make all the steps from channel labeling to storing and analyzing data foolproof and straightforward. We have been working with Matt and colleagues for over a decade at Mayo Clinic and now in Poland and Czech Republic. I am not aware of a better solution for large scale intracranial human recordings."
Gdansk University of Technology, Gdansk, Poland
"We converted all of our data to MED format a year ago. We greatly benefit from the compression capabilities of the format which allows us to save money on unnecessary storage. On top of that MED format allows us to process our data in parallel on an HPC cluster using our own Python tools."
International Clinical Research Center, Brno, Czech Republic
"We use the Dark Horse Neuro MED acquisition system to save our Neuralynx research data. It is reliable and efficient. I analyze the data with Python and Matlab. The read and write speed is excellent. I appreciate the well designed encryption levels and metadata. I've also found it easy to work with the team at DHN."
Mayo Clinic, Rochester MN, United States
Incorporating this small but mighty, preloaded and configured computer into your neurophysiology system can increase the performance of every other process in your downstream workflow.
High-performance, networked compression and encryption processing that fits easily on existing Neuralynx racks.
"Dark Horse Neuro has vastly improved our workflow via compression and conversion tools and the MED format provides useful metadata necessary for alignment of external events and experimental processing. Being able to use both Python and Matlab workflows is a significant benefit. The Dark Horse team is highly responsive and quick to troubleshoot and add features. Recording from Neuralynx directly into MED with the DHN acquisition software is intuitive, powerful, and streamlines data flow from acquisition to analysis."
University of Colorado, Aurora CO, United States