Automatic extracellular spike detection with piecewise optimal morphological filter

Authors:
Xiaofeng Liu;Xianqiang Yang;Nanning Zheng
Affiliations:
Institute of Artificial Intelligence and Robot, Xi'an Jiaotong University, Xi'an 710049, PR China and College of Electrical Engineering and Information, Shandong University of Science and Technolo ...;Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, Heilongjiang 150001, PR China;Institute of Artificial Intelligence and Robot, Xi'an Jiaotong University, Xi'an 710049, PR China
Venue:
Neurocomputing
Year:
2012

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Abstract

Neuronal spike detection is a technical challenge because of large amounts of background noise and contributions of many neurons to recorded signals. In this paper, we propose an automatic spike detection algorithm in which piecewise optimal morphological filters are designed to separate action potentials (spikes) from background noise. The structure elements of morphological filters are constructed with Gaussian function and a concise criterion is introduced to piecewise optimized structure elements. An adaptive amplitude threshold is utilized to detect spike events when the spikes are extracted by the morphological filter, which increases the detection accuracy. We evaluate our algorithm with both synthesized neural recordings and real neural data, and compare it with two established spike detection methods.