A simulation study assessing the efficiency of deriving evoked responses using high stimulus rate

Abstract

This study investigates the effects of stimulus rate on the recording efficiency of evoked-response scenario using a computer generated data simulating auditory evoked potentials (AEPs). We examine AEPs derived from three paradigms: 1) Conventional stimuli for ensemble averaging; 2) continuous loop averaging deconvolution (CLAD); and 3) maximum length sequence (MLS) stimuli, in which deconvolution techniques are incorporated to retrieve the overlapped responses. The performance is evaluated by correlation coefficients between the ideal and the derived responses. The results show that there is no distinct improvement of SNR for high rate stimulation paradigms, suggesting that the techniques of deconvolution in high rate will not provide more efficient recording approach. Further, responses from the CLAD paradigm tend to deteriorate compared to the other two methods due to the lower jittering arrangement of the sequence.

Least-squares (LS) deconvolution of a series of overlapping cortical auditory evoked potentials: a simulation and experimental study

“…Consequently, our simulations showed the limitation of low-jittered sequences to decrease testing time, especially if we consider that physiological responses adapt and decrease in amplitude for high presentation rates. This observation is in agreement with previous findings of Wang et al (2008b) who showed, using simulations, the limitation of low-jittered sequences, such as the CLAD technique for testing time reduction (Wang et al 2008b). Experimental results obtained for real-life CAEPs discussed in the following section provide further information about the amplitude decrease and response adaptation associated with a presentation rate increase.…”

EMD-based EEG signal enhancement for auditory evoked potential recovery under high stimulus-rate paradigm

“…However, the EMD results are sensitive the high oscillation components in a sense that the next IMF is significantly affected by the outcomes of previous IMFs. Another factor that should be taken into account is that they are prone to abnormal augmentation by deconvolution operations [13].…”

“…And Jewett et al [7] also provided an approach to selecting the appropriate stimulus loop (named q-sequence) making the HSR paradigm more practical. However, the CLAD method, inverse filtering in essence, can amplify such irrelevant components as random noise and artifacts within specific frequency bins determined by the properties of the stimulus sequences in frequency domain [1,11,12], introducing a new issue of low AEP recording efficiency [13].…”