This repository contains code related to an ongoing project where we employ wavelet filtering to try and enhance the signal to noise ratio of EEG measures of Neural Gating in response to both respiratory and somatosensory stimulation.

We employ the wavelet filtering algorithm that is detailed here: Hu, L., Mouraux, A., Hu, Y., & Iannetti, G. D. (2010). A novel approach for enhancing the signal-to-noise ratio and detecting automatically event-related potentials (ERPs) in single trials. Neuroimage, 50(1), 99-111.

To investigate the efficacy of the technique, we perform the analyses on simulated data and compare the performance of the wavelet filtering technique with traditional time domain methods as well as newer frequency domain methods of quantifying neural gating from event related EEG data.

The project will also explore whether pre-stimulus parameters like the aperiodic component (exponent) or the pre-stimulus alpha power are predictive of neural gating magnitude.

This codebase is a work in progress and may be intermittently edited or updated