Please use this identifier to cite or link to this item: https://doi.org/10.1109/EMBC.2013.6609756
Title: A robust EC-PC spike detection method for extracellular neural recording
Authors: Zhou, Y.
Yang, Z. 
Issue Date: 2013
Source: Zhou, Y.,Yang, Z. (2013). A robust EC-PC spike detection method for extracellular neural recording. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS : 1338-1341. ScholarBank@NUS Repository. https://doi.org/10.1109/EMBC.2013.6609756
Abstract: This paper models signals and noise for extracellular neural recording. Although recorded data approximately follow Gaussian distribution, there are slight deviations that are critical for signal detection: a statistical examination of neural data in Hilbert space shows that noise forms an exponential term while signals form a polynomial term. These two terms can be used to estimate a spiking probability map that indicates spike presence. Both synthesized data and animal data are used for the detection performance evaluation and comparison against other popular detectors. Experimental results suggest that the predicted spiking probability map is consistent with the benchmark and work robustly with different recording preparations. © 2013 IEEE.
Source Title: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
URI: http://scholarbank.nus.edu.sg/handle/10635/69044
ISBN: 9781457702167
ISSN: 1557170X
DOI: 10.1109/EMBC.2013.6609756
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

18
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.