A 100-channel system for real time detection and storage of extracellular spike waveforms

As extracellular electrode arrays with 100 or more active recording sites b ecome more widely used for simultaneous recording of neural ensembles, prac tical data acquisition systems that can efficiently accommodate high electr ode counts are needed. To reduce the high data rates associated with extrac ellular recordings from these arrays, various algorithms and systems have b een designed to provide complete online detection and classification of ext racellular spike waveforms. However, many of these algorithms require signi ficant user supervision to ensure accurate performance. In this paper, we d iscuss the design and validation of a 100-channel PC-based system that can be used with arrays of extracellular electrodes such as the Utah Electrode Array. Instead of comprehensive online spike analysis, the system performs online detection and storage of the spike waveforms for offline classificat ion. This strategy preserves the data of interest, reduces system complexit y, and requires less user supervision during experiments. (C) 1999 Elsevier Science B.V. All rights reserved.