Dataset Information

Emotional mimicry signals pain empathy as evidenced by facial electromyography.

ABSTRACT: Facial mimicry has been suggested to be a behavioral index for emotional empathy. The present study is the first to investigate the link between facial muscle activity and empathy for pain by facial electromyographic (EMG) recording while observers watched videos depicting real-life painful events. Three types of visual stimulus were used: an intact painful scene and arm-only (needle injection) and face only (painful expression) scenes. Enhanced EMG activity of the corrugator supercilii (CS) and zygomaticus major (ZM) muscles was found when observers viewed others in pain, supporting a unique pain expression that is distinct from the expression of basic emotions. In the intact video stimulus condition, CS activity was correlated positively with the empathic concern score and ZM activity, suggesting facial mimicry mediated empathy for pain. Cluster analysis of facial EMG responses revealed markedly different patterns among stimulus types, including response category, ratio, and temporal dynamics, indicating greater ecological validity of the intact scene in eliciting pain empathy as compared with partial scenes. This study is the first to quantitatively describe pain empathy in terms of facial EMG data. It may provide important evidence for facial mimicry as a behavioral indicator of pain empathy.

SUBMITTER: Sun YB

PROVIDER: S-EPMC4673531 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Emotional mimicry signals pain empathy as evidenced by facial electromyography.

Sun Ya-Bin YB Wang Yu-Zheng YZ Wang Jin-Yan JY Luo Fei F

Scientific reports 20151209

Facial mimicry has been suggested to be a behavioral index for emotional empathy. The present study is the first to investigate the link between facial muscle activity and empathy for pain by facial electromyographic (EMG) recording while observers watched videos depicting real-life painful events. Three types of visual stimulus were used: an intact painful scene and arm-only (needle injection) and face only (painful expression) scenes. Enhanced EMG activity of the corrugator supercilii (CS) and ...[more]

PMID: 26647740

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Project description:Eliminating facial electromyographic (EMG) signal from the electroencephalogram (EEG) is crucial for the accuracy of applications such as brain computer interfaces (BCIs) and brain functionality measurement. Facial electromyography typically corrupts the electroencephalogram. Although it is possible to find in the literature a number of multi-channel approaches for filtering corrupted EEG, studies employing single-channel approaches are scarce. In this context, this study proposed a single-channel method for attenuating facial EMG noise from contaminated EEG. The architecture of the method allows for the evaluation and incorporation of multiple decomposition and adaptive filtering techniques. The decomposition method was responsible for generating EEG or EMG reference signals for the adaptive filtering stage. In this study, the decomposition techniques CiSSA, EMD, EEMD, EMD-PCA, SSA, and Wavelet were evaluated. The adaptive filtering methods RLS, Wiener, LMS, and NLMS were investigated. A time and frequency domain set of features were estimated from experimental signals to evaluate the performance of the single channel method. This set of characteristics permitted the characterization of the contamination of distinct facial muscles, namely Masseter, Frontalis, Zygomatic, Orbicularis Oris, and Orbicularis Oculi. Data were collected from ten healthy subjects executing an experimental protocol that introduced the necessary variability to evaluate the filtering performance. The largest level of contamination was produced by the Masseter muscle, as determined by statistical analysis of the set of features and visualization of topological maps. Regarding the decomposition method, the SSA method allowed for the generation of more suitable reference signals, whereas the RLS and NLMS methods were more suitable when the reference signal was derived from the EEG. In addition, the LMS and RLS methods were more appropriate when the reference signal was the EMG. This study has a number of practical implications, including the use of filtering techniques to reduce EEG contamination caused by the activation of facial muscles required by distinct types of studies. All the developed code, including examples, is available to facilitate a more accurate reproduction and improvement of the results of this study.

Dataset Information

Emotional mimicry signals pain empathy as evidenced by facial electromyography.

Publications

Emotional mimicry signals pain empathy as evidenced by facial electromyography.

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