Towards reliable spike-train recordings from thousands of neurons with multielectrodes

The new generation of silicon-based multielectrodes comprising hundreds or more electrode contacts offers unprecedented possibilities for simultaneous recordings of spike trains from thousands of neurons. Such data will not only be invaluable for finding out how neural networks in the brain work, but will likely be important also for neural prosthesis applications. This opportunity can only be realized if efficient, accurate and validated methods for automatic spike sorting are provided. In this review we describe some of the challenges that must be met to achieve this goal, and in particular argue for the critical need of realistic model data to be used as ground truth in the validation of spike-sorting algorithms.

Graphical abstractDownload high-res image (125KB)Download full-size imageHighlights► New silicon multielectrodes may reliably record spikes from thousands of neurons. ► Validated and automated spike-sorting methods needed to fulfill potential. ► Realistic ground-truth data required both for algorithm development and validation.