Electroencephalographic Studies of Human Pain Perception

Abstract

Pain, if insufficiently controlled or inadequately treated, may interfere with a person¿s normal functioning and impair quality of life. The major barriers to effective pain control/ treatment include lack of accurate pain assessment and lack of understanding on gender differences in pain perception. This thesis is concerned with exploring objective measures of human pain perception and investigating gender differences in pain perception by using electroencephalogram (EEG) methods. It also includes a novel method to tackle the challenging problem of automatic EEG artifact removal.

EEG signals are susceptible to various artifacts, which are usually much stronger than brain activities and greatly interfere with EEG interpretation. It is necessary to remove the various artifacts from EEG before further analysis. In this thesis, a novel independent component analysis based automatic artifact removal method is proposed. The proposed method has two unique features: a) it uses weighted support vector machine to handle the inherent unbalanced nature of component classification, and b) it accommodates the structural information typically found in component classification. Numerical experiments on real-life EEG show that the proposed method outperforms several benchmark methods and is well suited for EEG artifact removal by achieving a better tradeoff between removing artifacts and preserving inherent brain activities.

The second contribution of the thesis is in proposing a promising objective measure of acute pain perception ¿ the electrocardiographic R-peak locked brain evoked potential (BEP), i.e. the heartbeat evoked potential (HEP). The HEP is found to be significantly suppressed by tonic cold pain over the right hemisphere which is contralateral to the cold pain stimulation. There is a significant correlation between the suppression of HEP and the level of pain experience. In comparison to the existing pain-related BEPs triggered by external stimuli, the HEP is obtained by using internal triggers, and thus may reveal patterns of endogenous brain activity associated with pain perception.

The last part of the thesis presents a pioneering study of gender differences in pain perception by EEG source localization method. Source analysis shows that during tonic cold pain perception females have significant stronger activations than males in the anterior cingulate cortex (ACC), which likely encodes the affective component of pain. This suggests that females concentrate more on the affective dimension of pain than males, which is consistent with the existing evidence. This study highlights the necessity of incorporating gender differences in clinical pain management. It also demonstrates the possibility of measuring gender differences in pain perception by EEG source localization, which is more portable and affordable than other functional imaging techniques.