A slope-based approach to spike discrimination in digitized data

A spike discrimination algorithm based on the analysis of spike up- and down-slopes can advantageously replace those based only on amplitude with a minimal increase of programming complexity and processing time. Such an algorithm was developed to sort muscle depolarizations from nerve spikes in electromyograms in insects. It could also be used to sort spikes according to their direction of travel in bipolar recordings from mixed nerves.

[1]  Clemens Forster,et al.  Automatic classification and analysis of microneurographic spike data using a PC/AT , 1990, Journal of Neuroscience Methods.

[2]  J. Delgado,et al.  CHAPTER 3 – ELECTRODES FOR EXTRACELLULAR RECORDING AND STIMULATION1 , 1964 .

[3]  J. Vibert,et al.  Spike separation in multiunit records: a multivariate analysis of spike descriptive parameters. , 1979, Electroencephalography and clinical neurophysiology.

[4]  Bruce C. Wheeler,et al.  A Comparison of Techniques for Classification of Multiple Neural Signals , 1982, IEEE Transactions on Biomedical Engineering.

[5]  H. D. Patton,et al.  Dipole characteristics of pyramidal cell activity in cat postcruciate cortex. , 1966, Journal of neurophysiology.

[6]  F. Delcomyn An approach to the study of neural activity during behaviour in insects. , 1976, Journal of insect physiology.

[7]  J. Schmitz,et al.  Oil and hook electrodes for en passant recordings from small nerves. , 1991 .

[8]  David H. Friedman,et al.  Detection of signals by template matching , 1969 .

[9]  Edward M. Schmidt,et al.  Computer separation of multi-unit neuroelectric data: a review , 1984, Journal of Neuroscience Methods.

[10]  M. Abeles,et al.  Multispike train analysis , 1977, Proceedings of the IEEE.

[11]  Thomas A. Miller,et al.  Insect Neurophysiological Techniques , 1979, Springer Series in Experimental Entomology.

[12]  M. Salganicoff,et al.  Unsupervised waveform classification for multi-neuron recordings: a real-time, software-based system. I. Algorithms and implementation , 1988, Journal of Neuroscience Methods.

[13]  Daniel S. Ruchkin,et al.  Principles of Neurobiological Signal Analysis , 1976 .