Analyzing psychophysical and electrophysiological data using mixed-effect models

Analyzing psychophysical and electrophysiological data using mixed-effect models: Quantification of stimulus processing using intra-epidermal electrodes

Mentink, Alexander (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Biomechanical Engineering)

Doll, Robert-Jan (mentor)
van der Helm, F.C.T. (graduation committee)
Buitenweg, Jan (graduation committee)
Söhl, J. (graduation committee)
van de Ruit, Mark (graduation committee)

Delft University of Technology

Biomedical Engineering | BioMechatronics

2017-10-26

Background: One of the biggest challenges of analyzing electroencephalogram (EEG) data in pain processing is the low signal-to-noise ratio (SNR). A common method to increase the SNR is to average time-locked responses over repeated trials. Unfortunately, relevant information is lost due to averaging. In addition, EEG responses are influenced by psychophysical elements, such as stimulus intensity and stimulus detection. Therefore, to reduce the loss of information and to control for psychophysical elements we developed a novel analysis method using linear mixed-effect (LME) models. Furthermore, capsaicin was used to challenge the novel method with the goal to quantify peripheral and central sensitization effects.

New method: LME models were used to include all EEG trials into one model to reduce the loss of information caused by averaging. In addition, phase locked and non-phase locked EEG data were combined with psychophysical data to control for psychophysical elements.

Results: Including all EEG trials into one model made it possible to perform statistical analyses. Moreover, combining EEG data with psychophysical data showed effects of stimulus detection, stimulus amplitude and the number of pulses on EEG responses. Although the LME models were able to test for significant effects after capsaicin application, the analyses did not show sensitization effects.

Comparison with existing methods: The phase locked EEG data was analyzed using conventional time-domain averaging methods and compared with LME models which included all EEG trials into one model.

Conclusion: This study showed that the novel LME method could be used to perform statistical analyses using all EEG trials and detect significant differences over time. In addition, psychophysical elements such as stimulus detection, amplitude and number of pulses could be controlled for both phase locked and non-phase locked EEG analyses. Probably, attention and learning effects played a role in the interpretation of the effects of capsaicin. Although application of this novel method showed no peripheral and central sensitization effects induced by capsaicin, it did show the potential of LME models in phase locked and non-phase locked EEG analyses.

mixed-effect model
intra-epidermal electrical
EEG Analysis
stimulus processing
capsaicin

http://resolver.tudelft.nl/uuid:637a020d-cdb8-4894-b772-05fbdbbbf650

2022-10-26

Student theses

master thesis

© 2017 Alexander Mentink