T-SNE visualization of large-scale neural recordings

It is neuroscience dogma that the brain's computational mechanics are implemented by the complex dynamics of its spiking neural networks. As a consequence, detailed knowledge of the spiking activity for "as-many-neurons-as-possible" during behavior is seen as essential to understand how the brain receives and transforms information. Electrophysiological methods that record spiking activity extracellularly have been one of the most significant tools for exploring the correlations between behavior and neural activity and there has been a constant drive to record from more neurons, for longer times, from a host of neural regions, in diverse physiological conditions, and from many different species. This trend was recently accelerated by new microfabricated recording probes that extend the standard single electrode and tetrode devices (Recce 1989) with integrated electronics to produce devices with thousands of recording sites (Ruther 2015, Alivisatos 2013). The new generation of recording tools brings with it the challenge of extracting meaningful physiological signals from the resulting (big) data sets.