A novel technique for spike detection in extracellular neurophysiological recordings using Cepstrum of Bispectrum

Signals from extracellular electrodes in neural systems record voltages resulting from activity in many neurons. Detecting action potentials (spikes) in a small number of specific (target) neurons is difficult because of poor SNR due to noise generated by the firing of neighbouring neurons. A new algorithm for spike detection has been developed: it applies a Cepstrum of Bispectrum (CoB) estimated inverse filter to provide blind equalization. This CoB based technique can detect 99% of spike events with less than 1% false positives (insertions) from the extracellular signal at up to -10dB SNR. We compare performance with four established techniques and report that the CoB based algorithm performs best.