Response Synchrony and Response Patterning of Psychophysiological Parameters in Emotion

An emotional experience is associated with changes in behavior (e.g., facial expression), physiological parameters (e.g., increased heart rate), and subjective experience (e.g., feeling anxious). The different response parameters are said to be changing synchronously during an emotion in order to ensure an optimal reaction to the triggering stimulus (e.g., to flee from a bear; Ekman, 1992; Levenson, 1994). The common simultaneous change over time is referred to as response synchrony (Bulteel et al., 2014). According to the basic emotion approaches, synchrony is regarded as an essential component of emotional experience (Ekman, 1992). In empirical studies, however, the results concerning the synchrony of different response parameters are diverse (Hollenstein & Lanteigne, 2014). The lack of empirical support may be due to the complex multivariate and non-stationary data structure which have a large effect on methods that make over-simplifying assumptions. For instance, previous approaches for quantifying synchrony disregarded the non-stationarity of the data, that is the fluctuation of mean and variance over time, and analyzed data only on an interindividual level (e.g., averaging over several individuals). The possibility to describe synchrony in the course of time or to provide evidence of synchrony in single individuals is thus not given. On the other hand, there are theoretical approaches such as psychological construction approaches that question the necessity of synchrony for an emotional experience (e.g., Barrett, 2006a; Cunningham, Dunfield, & Stillman, 2013). Therefore, one aim of this doctoral thesis was to develop and to apply a new approach to quantify physiological synchrony. Related to the question of the synchronous change of physiological parameters is the question whether individuals or even different emotional states can be correctly classified based on changes in physiological parameters. Here, the focus lies on the change of physiological parameters to a specific pattern depending on the evoked emotion which is described by the term response patterning (Bulteel et al., 2014). The majority of the studies collect data to classify individuals or emotions only on one measurement occasion. Such a procedure neglects the daily variations and intraindividual changes of physiological data at different times and tends to overestimate the accuracy of the classification (R. A. Calvo, Brown, & Scheding, 2009; Picard, Vyzas, & Healey, 2001). For this reason, another aim of this doctoral thesis was the classification of individuals and emotions when data were collected at two different measurement occasions. This cumulus contains three Manuscripts. The aim of Manuscript A (N = 58) was to develop a new time-frequency-based approach to quantify synchrony of physiological parameters on a latent level. Using the new approach, multivariate and non-stationary time series can be analyzed on an intraindividual level. The quantification of synchrony consists of two steps. In a first step, time-varying bivariate coherences of two physiological signals (e.g., electrocardiogram and electrodermal activity) are calculated. Due to the joint time-frequency-based approach, the non-stationarity of the data is taken into account. In a second step, these bivariate coherences are used in a state-space model as manifest indicator variables to form a latent synchrony variable at time t. The synchrony measure can take values between 0 and 1, where 0 means that the manifest coherences variables are completely uncorrelated and 1 means that they change synchronously. The results showed that the overall physiological synchrony variable was close to 1 in some parts of the film clip which was rated as more funny. Further, a high interindividual variability in the synchrony of physiological parameters was found. Compared to the network approach of Hsieh et al. (2011), the new method is capable of mapping the time course of physiological synchrony and revealing inter- and intraindividual differences. The network approach only returned results that counted for the entire sample under the assumption of stationarity and did not allow for individual variability. The aim of Manuscript B (N = 42) was the further application of the newly developed approach for the quantification of physiological synchrony. The research question if the synchrony of physiological parameters during the emotional experience of disgust is higher than during a neutral emotional state was addressed. Further, the interindividual variability and the correlation between the subjective intensity level of disgust and the physiological synchrony were investigated. For this, participants were shown neutral and disgusting pictures. The results showed that synchrony was significantly higher shortly after showing a disgusting picture as compared to shortly after showing a neutral picture. At the same time, there were large interindividual differences in the temporal course of synchrony. Further, physiological synchrony started to increase before the actual picture was shown which raises the question, to what extent an orienting response can be responsible for the changes in physiological synchrony. The subjective intensity rating of disgust was measured continuously with a rating dial. It was at a maximum when physiological synchrony had already decreased back to the baseline level. A possible explanation could be motor and cognitive processes which are necessary for turning the rating dial. The aim of Manuscript C (N = 36) was the classification of individuals and emotions by means of peripheral physiological data. In contrast to many previous studies, data were collected on two measurement occasions with a time interval of six weeks between them. Two well-established methods were applied as classifiers (k-nearest neighbors (KNN) and support vector machines (SVM)) that both take into account the nonlinear separability of the features that were extracted from the data. Pictures and film clips were used to induce fear. Fear could be better differentiated from a neutral state when film clips (77.50% KNN; 81.90% SVM) instead of pictures (64.40% KNN; 66.20% SVM) were used as induction method. Further, initial attempts were made to classify different levels of fear and to compare them with continuous ratings of fear. On a descriptive level, a connection between the classification and the subjective rating could be shown. In addition to the emotion classification task, individuals were classified using features from the electrocardiogram signal. In terms of classifying individuals, the correct classification rate showed a clear decline from 54.53% to 23.16% using the KNN and from 56.70% to 26.93% using the SVM when the training and testing data were from two different measurement occasions. This result demonstrates the high intraindividual variability of physiological data. However, compared to previous results, the classification rates were rather low which could be related to the emotion induction on a rather low intensity level. In summary, in this doctoral thesis the synchrony of physiological parameters during an emotion is examined. Further, this thesis investigates to what extent physiological changes can be used to distinguish a given emotion from a neutral state. In a general discussion, the results are compared with the prevailing emotion theories. In conclusion, the results of this thesis show that physiological synchrony during an emotion exists with great interindividual differences. The results suggest that future studies on physiological parameters should not be evaluated on an interindividual, aggregated level, but rather consider intraindividual processes.