1. What is Mu Desynchronization?
Individual Differences in Empathy and Mu Wave Desynchronization
Durham, J. D., Rooney, C., & Mather, R. D.
Method
Participants
Participants included twelve (eight female and four male) undergraduate introductory psychology students recruited from the University of Central Oklahoma. Participation in this experiment was in exchange for partial fulfillment of a research participation requirement.
Materials & Stimuli
Stimuli included a silent, five-minute compilation film of painful sports injury clips. Compilation clips included self-induced or incidental sport injuries resulting in broken bones and torn ligaments. Video clips were presented subsequently for approximately seven seconds each. Video clips were retrieved from YouTube and edited on a laptop in Movie Maker Project. A blank, black, computer monitor screen was presented as a baseline measure for four-minutes before and after the pain video stimuli.
A computerized acquisition device (BIOPAC MP150 system) recorded EEG data with single gold-cup electrodes administered according to the International Electrode Placement System Manual. A measuring tape, washable marker, an abrasion scrub pad, electrode adhesive gel, rubbing alcohol, and cotton-balls were used to embed each electrode.
Procedure
All participants had two active electrodes to the F3 and F4 region, two reference electrodes to the F1 and F2 region, and a ground electrode clipped to the right ear of each participant to observe a computer monitor for three conditions: 1) a blank, black screen baseline condition for four-minutes prior to viewing stimuli 2) a five-minute compilation video of painful sport injuries, 3) another blank, black screen baseline condition for four-minutes. Participants were randomly assigned to complete the questionnaires before or after electrode administration.
Empathy for Pain
The psychological construct of empathy is the natural, effortless ability to understand a person’s cognitive perspective and experience the other person’s emotional state[3]. Deciphering context and emotional states is conducive for interpreting vicarious pain. Observing others' physical pain activates neural networks related to the actual experience of pain itself. The neural overlap of social and physical pain to effectively experience empathy for vicarious pain through internal simulations may permute a nonlinear dynamic process of social automaticity. Experiencing empathy from vicarious physical pain depends on complex neural networks, including the mirror neuron systems[1].
Mirror Neuron Systems
Mirror systems are visuosensorimotor neurons that discharge while observing motor action, performing an action, and thinking about acting. Mirror systems may constitute an organic observation/execution coding system fundamental for motor learning, imitation, language acquisition, and understanding social context such as others’ intentions and beliefs. However, the temporal dynamics of neurophysiological activities underlying empathic processes remain poorly understood. Previous research has measured mu wave frequencies to investigate mirror system activation while watching a acting agent using Electroencephalography (EEG)[2,4].
What is Mu Desynchronization?
Mu waves are neural oscillations with dominant frequencies of 8-13 Hz related to social cognitive processes and voluntary movement. Mu waves synchronize when the sensorimotor system is in idle, the body is relaxed but alert with eyes open. Mu frequencies become suppressed or desynchronize when mirror systems discharge. The greater mirror system activation, the greater mu wave desynchronization[7].
Research Question
It was hypothesized that participants would exhibit greater mu wave desynchronization watching video clips of sport injuries than while watching a blank, black computer monitor. The authors expected participants who had higher empathy ratings would exhibit greater sensorimotor activity while observing painful stimuli. A1 A2 B
Data Preparation
EEG data were sampled at 200 observations/sec or 200 Hz to produce time series of approximately 60,000 points for each condition. The data were smoothed by a factor of 3 and Fast Fourier Transforms (FFT) were performed for each observation condition. Data were further exported to an EXCEL spreadsheet, then uploaded to MATLAB and SPSS statistical softwares. Each participant’s three conditions also reported permutation entropy values to indicate whether the pain condition exhibited greater unpredictability over time than baseline conditions. Further analyses investigated the relationship between each participant’s FFTs and permutation entropy measures.
Results
BIOPAC’s ACQKnowledge software was used to perform FFTs on epoched EEG data for each participant’s conditions. The FFT is a standard linear and/or nonlinear technique that converts data in a time series domain into a frequency domain. Previous research has used the FFT to substantiate EEG analyses related to mu wave desynchonization. An FFT plot was performed for each condition of each participant to determine if mu desynchronization occurred. Results of FFTs for each participant’s conditions indicated that participants exhibited mu desynchronization either for all conditions or not at all. That is, there were only between-subjects differences in mu desynchronization, but no differences within a participant due to the pain video.
Permutation Entropy: Order and Lag Series
Permutation entropy (PE) is a mathematical indicator of complexity and disorder that was computed because it is quick, robust, and previously used on EEG data. Different order (3 and 4) and lag (1, 2, 3) series were used to find which combination best represented the EEG data. PE values of order 3, lag 2 series showed the greatest differences in value between the pain and baseline conditions. Though the PE was higher for every participant in the experimental condition than in the pre or post conditions, the differences were not large.
Discussion
Feeling other people’s pain and experiencing empathy may be related to the MNS. Desynchronization of mu waveforms is an indicator of MNS activity. However, the current project demonstrated that participants mu desynchronization in response to observing painful stimuli either occurred entirely or not at all during the experiment. Results of the present study do not indicate a clear finding of mu desynchronization which may be explained as theoretical threats to studying MNS activity, pain, and empathy (Hickok, 2009; Williams, 2013). The mixed results may be better explained by potential errors in EEG data acquisition setup, design flaws, and other confounds. This research addresses potential replicability issues using neurophysiological techniques, specifically related to EEG experimental design. 1 2
References
[1] Avenanti, A., & Agliotti, S.M. (2006). Psychoanalysis and Neuroscience: The Sensorimotor Side of Empathy for Pain, chapter 9, Springer.
[2] Baird, A.D., Scheffer, I.E., & Wilson, S.J. (2011). Mirror neuron system involvement in empathy: A critical look at the evidence. Social Neuroscience, 6(4),
[3] Guastello, S.J. (2016). Physiological synchronization in a vigilance dual task. Nonlinear Dynamics, Psychology, and Life Sciences, 20(1),
[4] Oberman, L.M., Hubbard, E.M., McCleery, J.P., Altschuler, E.L., Ramachandran, V.S., & Pineda, J.A. (2005). EEG evidence for mirror neuron dysfunction in autism spectrum disorders. Cognitive Brain Research, 24,
[5] Paulhus, D. L., & Jones, D. N. (2011). Introducing a short measure of the Dark Triad. Poster presented at the meeting of the Society for Personality and Social Psychology, San Antonio.
[6] Spreng, R.N., McKinnon, C.M., Mar, R.A., & Levine, B. (2009). The Toronto empathy questionnaire: Scale development and initial validation of a factor-analytic solution to multiple empathy measures. Journal of Personality Assessment, 91(1), doi: /
[7] Pineda, J.A. (2005). The functional significance of mu rhythms: Translating “seeing” and ”hearing” into “doing”. Brain Research Reviews, 50, 3
This project was supported by funds from the University of Central Oklahoma Office of Research & Grants, College of Education & Professional Studies, & Office of Academic Affairs
Please address correspondence regarding this poster to: Justin Durham, B.A., Department of Psychology, Edmond, OK or
Figure 1-3. FFT plots of frequency distribution for participant #3 before (1), during (2), and after (3) observing painful stimuli.