Analyses for physiological and behavioral rhythmicity

Biological data that contain cycles require specialized statistical and analytical procedures. Techniques for analysis of time series from three types of systems are considered with the intent that the choice of examples is sufficiently broad that the processes described can be generalized to most other types of physiological or behavioral work. Behavioral circadian rhythms, acoustic signals in fly mating, and the Drosophila melanogaster cardiac system have been picked as typical in three broad areas. Worked examples from the fly cardiac system are studied in full detail throughout. The nature of the data streams and how they are acquired is first discussed with attention paid to ensuring satisfactory subsequent statistical treatment. Analysis in the time domain, namely simple and advanced plotting of data, autocorrelation analysis, and cross-correlation, is described. The search for periodicity is conducted through examples of analysis in the frequency domain, primarily spectral analysis. Nonstationary time series pose a particular problem, and wavelet analysis of Drosophila mating song is described in detail as an example. Conditioning of data to improve output with digital filters, Fourier filtering, and trend removal is described. Finally, two tests for noise levels and regularity are considered. All the nonproprietary software used throughout the work is available from the author free of charge and can be specifically tailored to the needs of individual systems.