Single-sweep analysis of event-related potentials by wavelet networks - Methodological basis and clinical application

Objective: Trial-to-trial variabilities in event-related potentials (ERP's) , which are neglected by investigating averaged ERP's, can be important to establish group-specific effects in clinical studies, Single ERP responses have to be analyzed to quantify these variations. In order to overcome the disadvantages of existing single-sweep estimators, we have developed a new procedure based on wavelet networks ((WN's) and applied this novel approach in a study concerning attention deficit hyperactivity disorder (ADHD) in c hildren. Method: WN's represent Signals as a linear combination of wavelet nodes, i. e., components characterized by time-frequency features related to the wave let transformation. In single-sweep analysis, each wavelet node is restrict ed to a specific region of the time-frequency plane during the recursive WN training process, This is achieved by means of tapering and bandpass filte ring with Gaussian functions which are automatically adapted and closely re lated to the Morlet basis wavelet, The time course of a single event-related response can be reliably estimate d. Furthermore, the WN method automatically provides well-defined parameter s for single event-related responses, respectively ERP trial-to-trial varia bilities. Results: In a psychophysiological study on ADHD using auditory evoked poten tials (AEP's), latency and amplitude parameters extracted fi om averaged ER P's did not reveal any significant differences between 25 control and 25 AD HD boys. In contrast, interesting group-specific differences could be estab lished by WN single-sweep analysis. Conclusion: WN single-sweep analysis can be recommended as a sensitive tool for clinical ERP studies which should be applied in addition to the invest igation of averaged responses.