While space engineers these days unite in their dream of a future Mars mission, neural engineers share the same enthusiasm for exploring our internal human universe, our brain. By making devices small enough to be implanted within the tissue, it is possible to tap into the circuitry of the brain, even down to the level of the single neurons. As engineers, such neural probes are our “admission tickets” to the field trip of neuroscience, into the unexplored mysteries of our most fascinating organ.
Most of our work is focussed at the interface between technology and biology, both literally and figuratively speaking. The smaller we can make the electrodes, the better chances we have, not only to resolve signalling patterns in their finest detail, but also in sustaining the contact to single neurons over long periods of time. This has spurred amazing creativity, and a growing community working towards refined electrode surfaces. The ultimate goal would be a seamless interconnect over which technology and biology exchange just as effortlessly as a regular data stream.
What until now conspicuously has been missing is a shared agreement on what “better electrodes” means. How can we best measure and define performance of neural electrodes, so that we know when and if we are making progress? To quote the man sometimes referred to as the inventor of modern business management, Peter Drucker: “You can't improve what you can't measure.” While Peter Drucker was referring to qualities challenging to put in numbers (e.g. success), engineers are fortunate enough to work on things that can be both measured and compared.
In our tutorial we share our view on “best practice” performance tests for neural interfaces and bioelectronics with the hope that more labs will join in on our efforts to standardize things. The EMBC chapter of the IEEE recently initiated a work group (WG 2794) targeting “Reporting Standards for in vivo Neural Interface Research” an initiative that we strongly support. Although the knowledge is out there in the community, it is rarely put on paper, which makes it difficult for newcomers to join the “field trip”. Most importantly, comparable and transparent definitions of what “better neural electrodes” mean would make us more efficient as a community. While we deeply admire those who discover the world through theory- we have learnt to appreciate a good measurement setup. Indeed, this is actually the difference between iterative progress and running in circles.