Time-frequency analysis of chemosensory event-related potentials to characterise the cortical representation of odors in humans

Introduction and aim: The recording of olfactory and trigeminal chemosensory event-related potentials (ERPs) has been proposed as an objective and non-invasive technique to study the cortical processing of odors in humans. Until now, the responses have been characterized mainly using across-trial averaging in the time domain. Unfortunately, chemosensory ERPs, in particular, olfactory ERPs, exhibit a relatively low signal-to-noise ratio. Hence, the current usefulness of the technique remains limited. We proposed that the relatively low signal-to-noise ratio could at least in part be due to temporal jitter affecting brain responses. Here, we used a time-frequency analysis based on the wavelet transform to reveal EEG responses that are not strictly phase-locked to the chemosensory stimulation. We hypothesized that this approach would significantly enhance the signal-to-noise ratio of the elicited responses because, as compared to conventional time-domain averaging, (1) it is less sensitive to temporal jitter and (2) it can reveal non phase-locked EEG responses such as event-related synchronization and desynchronization. Material and methods: EEG responses to selective trigeminal and olfactory stimulation were recorded in 11 normosmic subjects. Classical across-trial time-domain averaging was used to characterize the responses in the time-domain. A Morlet wavelet was used to characterize the elicited responses in the time-frequency domain. Results: The time-frequency approach markedly improved the signal-to-noise ratio of the obtained responses, in particular, following olfactory stimulation. Furthermore, the approach allowed characterizing non phase-locked components that could not be identified using conventional time-domain averaging. Conclusion: By providing a more robust and complete view of how odors are represented in the human brain, our approach could constitute the basis for a robust tool to study olfaction, both for basic research and clinicians