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Updated: Jun 4, 2026
Infant Auditory Processing and Event-related Brain Oscillations
Published on: July 1, 2015
Single-trial detection of somatosensory evoked potentials by probabilistic independent component analysis and wavelet
1Department of Orthopaedics and Traumatology, The University of Hong Kong, Hong Kong, China.
Objective:
To develop an effective approach for enhancing the signal-to-noise ratio (SNR) and identifying single-trial short-latency somatosensory evoked potentials (SEPs) from multi-channel electroencephalography (EEG).
Methods:
128-channel SEPs elicited by electrical stimuli of the left posterior tibial nerve were recorded from 11 healthy subjects. Probabilistic independent component analysis (PICA) was used as a spatial filter to isolate SEP-related independent components (ICs), and wavelet filtering was used as a time-frequency filter to further enhance the SNR of single-trial SEPs.
Results:
SEP-related ICs, identified using PICA, showed typical patterns of cortical SEP complex (P39-N50-P60) and scalp topography (centrally distributed with the spatial peak located near vertex). In addition, wavelet filtering significantly enhanced the SNR of single-trial SEPs (p=0.001).
Conclusions:
Combining PICA and wavelet filtering offers a space-time-frequency filter that can be used to enhance the SNR of single-trial SEPs greatly, thus providing a reliable estimation of single-trial SEPs.
Significance:
This method can be used to detect single-trial SEPs and other types of evoked potentials (EPs) in various sensory modalities, thus facilitating the exploration of single-trial dynamics between EPs, behavioural variables (e.g., intensity of perception), as well as abnormalities in intraoperative neurophysiological monitoring.
