Time-frequency analysis of electrophysiology signals in epilepsy

Many of the most powerful and effective algorithms in signal processing start with the assumption of stationarity. In addition, the deterministic portion of the signal is often assumed to be composed of complex exponentials that are the solutions to linear time-invariant (LTI) differential equations. These assumptions are often valid enough to yield good results when the signals and systems involved result from engineering design which often assures compliance with these conceptualizations. Signals of biological origin often do not comply with these assumptions, however, resulting in disappointment when conventional techniques are used. Newly emerging techniques of time-frequency (t-f) analysis can provide new insights into the nature of biological signals. This article describes some results using reduced interference distributions (RIDs) in the analysis of biosignals recorded in human epilepsy. It is shown that RID analysis of these signals results in insights and research hypotheses which would be difficult or impossible to obtain using conventional techniques. This is not a general t-f review article, and it is beyond the scope of this article (and space limits) to discuss the many new t-f tools that are now appearing in the literature. This article demonstrates one application of RID analysis.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>