A new time-frequency analysis technique for neuroelectric signals

Abstract

In the presence of external stimuli, the functioning brain emits neuroelectrical signals which can be recorded as the Event Related Potential (ERP) signals. To understand the brain cognitive functions, ERP signals have been the subject matter of many applications in the field of cognitive psychophysiology. Due to the non–stationary nature of the ERP signals, commonly used time or frequency analysis techniques fail to capture the time–frequency domain localized nature of the ERP signal components. In this study, the newly developed Time–Frequency Component Analyzer (TFCA) approach is adapted to the ERP signal analysis. The results obtained on the actual ERP signals show that the TFCA does not have a precedent in resolution and extraction of uncontaminated individual ERP signal components. Furthermore, unlike the existing ERP analysis techniques, the TFCA based analysis technique can reliably measures the subject dependent variations in the ERP signals, which iiiopens up new possibilities in the clinical studies. Thus, TFCA serves as an ideal tool for studying the intricate machinery of the human brain.