Abstract
Today's implanted neural systems are bound by tight constraints on power and communication bandwidth. Most conventional ADC-based approaches fall into two categories. Either they transmit all of the information at the Nyquist rate but are ultimately limited to only a handful of channels due to communication bandwidth constraints. Or they perform spike detection on the front-end which allows a scale up to 100 or more channels but prevents the use of spike sorting on the backend. Spike sorting is an important step that provides a labeling to multiple neurons on each channel and further improves the accuracy of spike detection. In this paper we describe the pulse-based approach used in the FWIRE (Florida Wireless Implantable Recording Electrodes) project. A hardware spiking neuron on each channel is configured either to transmit pulses for full reconstruction on the back end, or to transmit dramatically fewer pulses but still allow for spike sorting on the back end. Spike sorting results show that the pulse-based spike sorting accuracy is competitive with conventional methods used in daily practice. ©2008 IEEE.
Recommended Citation
J. G. Harris et al., "Pulse-based Signal Compression For Implanted Neural Recording Systems," Proceedings IEEE International Symposium on Circuits and Systems, pp. 344 - 347, article no. 4541425, Institute of Electrical and Electronics Engineers, Sep 2008.
The definitive version is available at https://doi.org/10.1109/ISCAS.2008.4541425
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-142441684-4
International Standard Serial Number (ISSN)
0271-4310
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
19 Sep 2008
