RT Journal Article SR Electronic T1 Unsupervised spike sorting for large scale, high density multielectrode arrays JF bioRxiv FD Cold Spring Harbor Laboratory SP 048645 DO 10.1101/048645 A1 Gerrit Hilgen A1 Martino Sorbaro A1 Sahar Pirmoradian A1 Jens-Oliver Muthmann A1 Ibolya E. Kepiro A1 Simona Ullo A1 Cesar Juarez Ramirez A1 Alessandro Maccione A1 Luca Berdondini A1 Vittorio Murino A1 Diego Sona A1 Francesca Cella Zanacchi A1 Upinder S. Bhalla A1 Evelyne Sernagor A1 Matthias H Hennig YR 2016 UL http://biorxiv.org/content/early/2016/04/13/048645.abstract AB A new method for automated spike sorting for recordings with high density, large scale multielectrode arrays is presented. It is based on an efficient, low-dimensional representation of detected events by their estimated spatial current source locations and dominant spike shape features. Millions of events can be sorted in just minutes, and the full analysis chain scales roughly linearly with recording time. We demonstrate this method using recordings from the mouse retina with a 4,096 channel array, and present validation based on anatomical imaging and model-based quality control. Our analysis shows that it is feasible to reliably isolate the activity of hundreds to thousands of retinal ganglion cells in single recordings.