Principles of Neurobiological Signal Analysis deals with the principles of signal analysis as applied to the electrical activity of the nervous system. Topics covered include biological signals, the basics of signal processing, and power spectra and covariance functions. Evoked potentials, spontaneous and driven single unit activity, and multiunit activity are also considered, along with the relations between slow wave and unit activity. This book consists of eight chapters and begins by establishing the theoretical groundwork of signal analysis, with emphasis on the properties of signal and noise; sampling and conversion of biological signals into sequences of digital numbers readily digestible by a computer; and the concepts of power spectrum and covariance analysis. The following chapters explore techniques for extracting evoked responses from background noise; multivariate statistical procedures for treating evoked response waveshapes as variables dependent upon the experimental manipulations performed upon a subject; and spike (action potential) activity generated by neurons. The final chapter describes methods for studying how such spike activity may be related to the concurrently observed slow wave (EEG-like) activity of the nervous system. This monograph will be of interest to physiologists and neurobiologists.