Abstract
Spike sorting is often required for analyzing neural recordings to isolate the activity of single neurons. Wave shape analysis in the spike sorting procedure provides a means to detect spikes while minimizing the influence of false alarms. As neural recording techniques allow for recording hundreds of electrodes, power is too limited in neural implants for current spike sorting algorithms. Even with spike sorting at the back-end where more power is available, the bandwidth is too limited to transmit enough information for current spike sorting techniques. A low-power pulse-based feature extractor presented in the paper is a solution to the bandwidth bottleneck. It reduces the bandwidth of the neural signal by several orders of magnitude while preserving enough information for spike sorting.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering |
| Pages | 490-493 |
| Number of pages | 4 |
| DOIs | |
| State | Published - Sep 25 2007 |
| Externally published | Yes |
| Event | 3rd International IEEE EMBS Conference on Neural Engineering - Kohala Coast, HI, United States Duration: May 2 2007 → May 5 2007 |
Other
| Other | 3rd International IEEE EMBS Conference on Neural Engineering |
|---|---|
| Country | United States |
| City | Kohala Coast, HI |
| Period | 5/2/07 → 5/5/07 |
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ASJC Scopus subject areas
- Biotechnology
- Bioengineering
- Neuroscience (miscellaneous)
Cite this
A pulse-based feature extractor for spike sorting neural signals. / Rogers, Christy L.; Harris, John G.; Principe, Jose C.; Sanchez, Justin C.
Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering. 2007. p. 490-493 4227321.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A pulse-based feature extractor for spike sorting neural signals
AU - Rogers, Christy L.
AU - Harris, John G.
AU - Principe, Jose C.
AU - Sanchez, Justin C.
PY - 2007/9/25
Y1 - 2007/9/25
N2 - Spike sorting is often required for analyzing neural recordings to isolate the activity of single neurons. Wave shape analysis in the spike sorting procedure provides a means to detect spikes while minimizing the influence of false alarms. As neural recording techniques allow for recording hundreds of electrodes, power is too limited in neural implants for current spike sorting algorithms. Even with spike sorting at the back-end where more power is available, the bandwidth is too limited to transmit enough information for current spike sorting techniques. A low-power pulse-based feature extractor presented in the paper is a solution to the bandwidth bottleneck. It reduces the bandwidth of the neural signal by several orders of magnitude while preserving enough information for spike sorting.
AB - Spike sorting is often required for analyzing neural recordings to isolate the activity of single neurons. Wave shape analysis in the spike sorting procedure provides a means to detect spikes while minimizing the influence of false alarms. As neural recording techniques allow for recording hundreds of electrodes, power is too limited in neural implants for current spike sorting algorithms. Even with spike sorting at the back-end where more power is available, the bandwidth is too limited to transmit enough information for current spike sorting techniques. A low-power pulse-based feature extractor presented in the paper is a solution to the bandwidth bottleneck. It reduces the bandwidth of the neural signal by several orders of magnitude while preserving enough information for spike sorting.
UR - http://www.scopus.com/inward/record.url?scp=34548753937&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34548753937&partnerID=8YFLogxK
U2 - 10.1109/CNE.2007.369716
DO - 10.1109/CNE.2007.369716
M3 - Conference contribution
AN - SCOPUS:34548753937
SN - 1424407923
SN - 9781424407927
SP - 490
EP - 493
BT - Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering
ER -