Figure 4: Transient episodes of momentary pain can be decoded using neural and facial activity.

A) Manual video reviews by two evaluators were performed to identify periods of momentary pain and periods of neutral affect. B) Consensus AUs (d > 0.2) across participants which were differentially expressed between periods of momentary pain and periods of neutral affect. Majority of these AUs have been implicated in pain expression previously. Colors represent the effect size between momentary pain and neutral periods. C) Classifiers were trained using the full spectro-spatial feature set (optimized model) and using solely features previously selected by the index pain self-report state classifier (pain self-report informed model). D) ROC curves for prediction of momentary pain from neutral affect across participants, stratified by the optimized model, the pain self-report informed model, and the self-reported pain shuffled model (spectro-spatial features selected from pain self-report state classifier trained on shuffled pain labels). The shaded error bar represents the s.e.m across 10 participants. E) Bar plot comparison of the three trained models. There was no significant difference between the optimized and the pain self-report informed model performance (paired t-test; t(9): 2.0, P=0.07). The pain self-report informed model performed better than using features not supervised to the self-report pain states (paired t-test; t(9): 2.7, P=0.03) F) Comparison of momentary pain decoding based on facial dynamics and neural features.