Neuroscientists at the Neuronano Research Centre at Lund University in Sweden have developed and tested an ambitious new design for processing and storing the massive amounts of data expected from future implantable brain machine interfaces (BMIs) and brain-computer interfaces (BCIs).
The system would simultaneously acquire data from more than 1 million neurons in real time. It would convert the spike data (using bit encoding) and send it via an effective communication format for processing and storage on conventional computer systems. It would also provide feedback to a subject in under 25 milliseconds — stimulating up to 100,000 neurons.
Monitoring large areas of the brain in real time. Applications of this new design include basic research, clinical diagnosis, and treatment. It would be especially useful for future implantable, bidirectional BMIs and BCIs, which are used to communicate complex data between neurons and computers. This would include monitoring large areas of the brain in paralyzed patients, revealing an imminent epileptic seizure, and providing real-time feedback control to robotic arms used by quadriplegics and others.
“A considerable benefit of this architecture and data format is that it doesn’t require further translation, as the brain’s [spiking] signals are translated directly into bitcode,” making it available for computer processing and dramatically increasing the processing speed and database storage capacity.
“This means a considerable advantage in all communication between the brain and computers, not the least regarding clinical applications,” says Bengt Ljungquist, lead author of the study and doctoral student at Lund University.
“The demands on hardware and software used in the context of BMI/BCI are already high, as recent studies have used recordings of up to 1792 channels for a single subject,” the researchers note in an open-access paper published in the journal Neuroinformatics.
That’s expected to increase. In 2016, DARPA (U.S. Defense Advanced Research Project Agency) announced its Neural Engineering System Design (NESD) program*, intended “to develop an implantable neural interface able to provide unprecedented signal resolution and data-transfer bandwidth between the human brain and the digital world.