Journal of Psychophysiology 1/2018

Volume 32 / Number 1 / 2018

Volume 32 / Number 1 / 2018

Journal of

Psychophysiology

Journal of Psychophysiology

Editor-in-Chief Michael Falkenstein Editorial Board Markus Breimhorst Tavis Campbell Ritobrato Datta Nicola Ferdinand Patrick Gajewski Edward Golob Sien Hu Julian Koenig Cristina Ottaviani Patrick Papart Daniel S. Quintana Walter Sannita Henrique Sequeira Franck Vidal Lin Wang Juliana Yordanova

An International Journal

Contents Articles

Journal of Psychophysiology (2018), 32(1)

Evaluative and Psychophysiological Responses to Short Film Clips of Different Emotional Content Luis Aguado, Marı́a Fernández-Cahill, Francisco J. Román, Iván Blanco, and Javier de Echegaray

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An ERP Investigation of Object-Scene Incongruity: The Early Meeting of Knowledge and Perception Fabrice Guillaume, Sophie Tinard, Sophia Baier, and Stéphane Dufau

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Burnout of the Mind – Burnout of the Body?

Claudia Traunmüller, Kerstin Gaisbachgrabner, Helmut Karl Lackner, and Andreas R. Schwerdtfeger

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Ó 2018 Hogrefe Publishing

Article

Evaluative and Psychophysiological Responses to Short Film Clips of Different Emotional Content Luis Aguado,1 María Fernández-Cahill,2 Francisco J. Román,3,4 Iván Blanco,1 and Javier de Echegaray1 1

Facultad de Psicología, Universidad Complutense de Madrid, Spain Instituto de Investigación “12 de octubre,” Madrid, Spain

2 3

Facultad de Psicología, Universidad Autónoma de Madrid, Spain

4

Decision Neuscience Laboratory, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign,

Urbana, IL, USA

Abstract: The study presents self-report and psychophysiological data obtained in response to short film clips representing scenes related to different emotions. This was done in order to obtain evidence on the structure of positive and negative affective states following a combined dimensional/categorical approach to emotion and based on responses to stimuli that are more realistic than the static pictures usually employed in the study of emotion. Affective ratings and self-report measures showed a differential structure of the response to positive and negative films (Experiment 1). While all negative films were rated as low in valence and high in arousal, positive films were differentiated into arousing (happy and pleasure contents) and de-arousing (relax contents) categories. A more complex pattern emerged in Experiment 2, using two psychophysiological measures that are differentially sensitive to the main affective dimensions of valence and arousal, skin conductance response (SCR) and facial electromyography (fEMG). First, high arousal positive and negative films produced larger skin conductance responses. Second, fEMG measures showed differentiated response patterns within the positive and negative film categories. Within the positive category, happy and relaxing films had opposed effects, with happy films increasing and relax films decreasing activity over the zygomaticus muscle region. In the case of negative films, only those eliciting disgust produced a differentiated pattern of fEMG activity characterized by large corrugator responses and a modest increase of zygomatic responses. These results are discussed in relation to the adequacy of the dimensional and categorical approaches to emotion, the usefulness of combining subjective and psychophysiological measures, and the advantages of using realistic, dynamic stimuli for the study of emotion.

Keywords: emotional films, arousal, valence, skin conductance, facial EMG

Contemporary studies of emotion have followed one of two different but complementary approaches to the characterization of affective experience and response. Dimensional approaches organize the affective space based on global elements of emotion, such as valence and arousal (e.g., Bradley & Lang, 2000a, 2000b). According to this approach, affective states can be differentiated based on specific values of these elemental dimensions, being defined, for example, as highly positive and arousing or slightly negative and de-arousing. In contrast with this, the discrete emotions approach proposes a differentiation of affective states in terms of their specific contents (e.g., threat-related vs. loss-related, Ekman, 1992; Izard, 1993), leading to different emotion categories such as fear or sadness. Studies using pictures as eliciting stimuli and self-report and psychophysiological measures as dependent measures have provided evidence supporting the dimensional approach. For example, some psychophysiological Ó 2016 Hogrefe Publishing

responses are differentially sensitive to variations in the two basic dimensions of valence and arousal. While the skin conductance response is sensitive to variations in arousal, with larger responses to more arousing stimuli (e.g., Bradley, Codispoti, Cuthbert, & Lang, 2001; Bradley, Codispoti, Sabatinelli, & Lang, 2001), the response of facial muscles measured through facial electromyography (fEMG) is more sensitive to valence, with different patterns of muscle activity for positive and negative stimuli (e.g., Cacioppo, Petty, Losch, & Kim, 1986). Albeit less abundant, research with picture stimuli has also provided results supporting the discrete emotions or categorical approach. For example, differences have been shown between the precise pattern of facial and visceral activity evoked while viewing fear and disgust pictures (Bradley, Codispoti, Sabatinelli, & Lang, 2001; Lang, Greenwald, Bradley, & Hamm, 1993).

Behavioral and neuroscientific research on emotion has used different procedures to induce mood changes and Journal of Psychophysiology (2018), 32(1), 1–19 DOI: 10.1027/0269-8803/a000180

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elicit evaluative and psychophysiological responses in experimental participants (see Coan & Allen, 2007, for a collection of chapters on emotion elicitation techniques).

Among those using visual stimuli, pictures showing affectively positive and negative objects or scenes (Lang, Bradley, & Cuthbert, 2008) have been most popular. Static visual stimuli have the advantage of allowing precise control of timing, which is a crucial requisite in most experimental paradigms. Moreover, briefly presented static stimuli do not change over time in terms of emotional intensity, as would be the case if animated images were used. However, the flip side of these methodological advantages is the reduced realism of static pictures that lack the dynamism and continuous change of real-life events. An alternative to static pictures is the use of films or film extracts that describe emotionally meaningful scenes. Although the use of this tool is not generalized, there are now several published reports describing collections of film clips that can be used in the study of emotion (Carvalho, Leite, Galdo-Álvarez, & Gonçalves, 2012; Gross & Levenson, 1995; Hewig et al., 2005; Philippot, 1993; Schaefer, Nils, Sanchez, & Philippot, 2010; see Rottenberg, Ray, & Gross, 2007, for a review).

Emotional film scenes also have their own advantages.

Firstly, films are especially effective in inducing mood changes and may be superior to other induction procedures (e.g., Palomba, Sarlo, Angrilli, Mini, & Stegagno, 2000; Simons, Detenber, Roedema, & Reiss, 1999; Simons, Detenber, Reiss, & Shults, 2000; Westermann, Spies, Stahl, & Hesse, 1996). Secondly, the dynamic nature of film scenes makes this a more realistic procedure to induce emotional changes, as it is closer to real-life emotions produced by experiences where events unfold over time. In effect, emotional film excerpts have been used successfully to elicit experiential (e.g., Gross & Levenson, 1995; Schaefer et al., 2010) and physiological changes (e.g., Christie & Friedman, 2004; Hubert & de Jong-Meyer, 1990; Kreibig, Wilhelm, Roth, & Gross, 2007). Similarly, characteristic patterns of brain activity have been reported in the presence of emotional film clips, compared to films of neutral content (e.g., Goldberg, Preminger, & Malach, 2014; Karama, Armony, & Beauregard, 2011). Based on this evidence, the use of film clips seems a suitable method to study emotion as their characteristics are closer to the dynamic and evolving nature of real-life emotional events. In this way, the use of this type of stimuli can improve the generalizability of basic research on emotion.

Experts in the use of films to elicit emotion have warned about the low temporal resolution of films in terms of emotional intensity and the danger that long excerpts may create heterogeneous epochs of data with significant variations in intensity (Rottenberg et al., 2007). However, most previous collections of emotion films include stimuli Journal of Psychophysiology (2018), 32(1), 1–19

L. Aguado et al., Responses to Emotional Clips

of different durations and in some cases excerpts lasting several minutes have been used. For example, the larger and more complete database of emotion films published to date (Schaefer et al., 2010) contains 70 clips with durations that range from 1 min to over 6 min. Although in the study by Hewig et al. (2005) shorter clips were included, duration varied from 29 to 236 s. Though long and varying durations may be appropriate to elicit overall mood or emotion changes that can be measured retrospectively via self-report by the participant, they are more problematic when the interest is in online gathering of objective physiological or brain activity data that are subject to continuous variation. In this case, averaging over the entire duration of films that contain segments of different emotional intensity increases the risk of reducing the sensitivity of the measure in question. The use of short films with a fixed duration is clearly more appropriate in this type of study. Moreover, when choosing the appropriate duration of film fragments, consideration must be paid to the temporal dynamics of the target response system.

Some indexes of emotional reactivity are fast, like facial EMG responses, which reach maximum amplitude during the first 500 ms after stimulus onset (e.g., Dimberg, 1990). In contrast with this, other indexes such as heart rate changes and electrodermal activity are slower and take several seconds to reach their maximum peak.

An additional shortcoming of long film fragments is that differences may appear between films in the complexity of the narrative. In fragments lasting several minutes such as those used in some studies (e.g., Schaefer et al., 2010), relatively complex plots can be developed, demanding elaborate processing mechanisms on behalf of the viewer and increasing the difficulty of interpreting associated changes in biological measures. As an alternative to this, much shorter film clips can be used to present peak emotional events that are not embedded in complex narratives or require further contextual information.

The goal of the present study is twofold. First, we describe in Experiment 1 a new set of short film clips with a fixed 10 s duration that can be useful in the study of affect and emotion using psychophysiological measures. This duration is long enough to allow measurement of the most popular and sensitive index of emotional arousal, skin conductance, while at the same time allowing the measurement of changes in responses that are sensitive to affective valence such as facial muscle responses measured through the fEMG technique. The decision to use 10 s clips was also based on our attempt to create a collection of dynamic snapshots describing self-contained, single events that could be easily understood and appraised as affectively meaningful in the absence of further contextual information (e.g., “Someone moving a bloodstained corpse” or “Dolphins jumping over the sea”). This format maintains Ó 2016 Hogrefe Publishing

L. Aguado et al., Responses to Emotional Clips

the characteristic single-event nature of more usual still pictures while adding, at the same time, further emotional power through the more lively and compelling dramatism of dynamic images. Clips of fixed but longer durations have been used in previous studies, such as the study by Carvalho et al. (2012), who used 40 s clips. Moreover, in this last study the clips were rated in terms of the valence, arousal, and dominance dimensions but not in terms of emotion category, unlike our study. The contents of the clips we selected were related to different specific emotions since one of our main goals was to prepare a film collection that could be used to study the reactions associated to different emotional states. The ability of our film collection to elicit differentiated psychophysiological response patterns related to different discrete emotions was tested in Experiment 2 using electrodermal activity and fEMG measures in response to positive (happy and relax), negative (fear and disgust), and neutral film clips.

Experiment 1 Materials and Method Stimulus Selection The first step in the study involved the selection of a set of 50 film excerpts representing a range of contents related to different varieties of positive and negative affect together with a set of control films showing affectively neutral scenes. The set comprised 50 film fragments (20 positive, 20 negative, 10 neutral), all with a fixed duration of 10 s.

Candidate excerpts were identified from a larger set of independent feature films and television documentaries.

These sources were chosen to avoid possible effects of familiarity and prior knowledge that might mediate the emotional impact of excerpts from more popular films already seen by the participants. Initial adscription of the excerpts to the different categories of valence and content was determined a priori by the experimenters.

Several target contents were chosen based on the categories of positive and negative images in the International Affective Picture System (IAPS) collection. Three categories of positive clips were selected: nature (underwater scenes, attractive animals, and landscapes), babies (babies alone or interacting with peers or mother), and couples/families (couples, erotic and family scenes). Studies with the IAPS collection have shown that these positive contents can be discriminated in terms of electrodermal activity and fEMG

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pattern (Bradley, Codispoti, Sabatinelli, & Lang, 2001; Ribeiro, Teixeira-Silva, Pompéia, & Bueno, 2007). As to the negative films, excerpts representing disgust (disgusting scenes involving human beings or animals) and aggression/ threat scenes (human aggression, injuries, or natural disasters) were selected. Studies with IAPS images have shown that these categories of negative content produce differentiated psychophysiological patterns (e.g., Bradley, Codispoti, Cuthbert, & Lang, 2001; Bradley, Codispoti, Sabatinelli, & Lang, 2001). Clips representing neutral scenes (human beings performing daily routines and urban scenes) were also selected as a control condition.

After identifying the excerpts of interest, they were edited to remove soundtrack and mastheads when necessary. We decided to use silent clips, where events are represented visually without the influence of dialogs or background music that might condition the interpretation of the scene and influence its emotional impact.

All excerpts were cut to 10 s duration. Detailed information about the clips is given in Appendix A.1 Participants A total of 38 students (19 males, 19 females, age 18–30 years, M = 22.29, SD = 2.17) from the Universidad Complutense of Madrid voluntarily took part in the study in exchange for course credits. All participants reported having no history of any neurological or psychiatric disorders. Informed consent was obtained before starting the experiment.

Procedure Stimulus presentation was programmed and controlled by software E-Prime 2.0 (Psychology Software Tools, Pittsburgh, PA). The stimuli were presented on a 12000 projector screen and responses were collected through written questionnaires. All participants saw the 50 clips in a single session.

A booklet was prepared containing instructions to perform the task and the valence and arousal SAM (SelfAssessment Manikin) scales (Bradley & Lang, 1994) for each clip. Participants were asked to rate each clip in terms of valence and arousal and to report the emotion they felt while watching each film, selecting from a list of eight word pairs the one that better represented how they felt while watching the clip (“Joy/Happiness,” “Pleasure/ Well-Being,” “Peace/Relaxation,” “Fear/Anxiety,” “Anger/Rage,” “Sadness/Sorrow,” “Disgust/Revulsion,” and “Neutral/No Emotion”). Each trial would start by presenting a film clip during 10 s, followed by a 30 s interval to respond. The order of stimulus presentation was varied randomly.

The complete clip collection can be obtained from the authors in CD-ROM format. Requests should be addressed to the corresponding author: laguadoa@ucm.es.

Ó 2016 Hogrefe Publishing

Journal of Psychophysiology (2018), 32(1), 1–19

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L. Aguado et al., Responses to Emotional Clips

Results As the goal of this study was to obtain initial validation data for our film clip collection, analyses were carried out at the stimulus level. For all repeated-measures ANOVAs reported, the Greenhouse-Geisser correction was applied when the sphericity assumption was violated. Post hoc analyses were performed using the Bonferroni correction (significant when p .05).

Valence and Arousal Ratings as a Function of Film Valence Ratings of valence and arousal correlated negatively (r = .77, p < .001) indicating that clips receiving lower ratings on the valence dimension were also rated as more arousing. Mean valence and arousal ratings for the positive, negative, and neutral film clips are presented in Figure 1.

For the valence ratings, a highly significant effect of valence category was obtained, F(2, 47) = 381.148, p < .001, η2 = .942. Post hoc comparisons showed that all categories were different from each other, with positive clips resulting as the most pleasant, followed by the neutral and negative clips (all ps < .001). A significant effect was also obtained for the arousal ratings, F(2, 47) = 64.428, p < .001, η2 = .733. Post hoc comparisons showed that negative clips were rated as significantly more arousing than neutral and positive clips (both ps < .001). Valence and arousal data for each individual clip are presented in Appendix B. Subjective Experience and Emotion Categories A clip was ascribed to a given emotion category when it reached a cut-off point of 50% choices of the corresponding emotion word (four times higher than the probability of being chosen randomly). Eleven clips had to be excluded for failing this criterion. Moreover, categories where only one clip met this criterion were excluded. This was the case of the anger/rage category. One of the neutral clips was excluded because the selection of positive emotion labels was over 50%. Thus, the final selection for this analysis comprised 37 clips distributed in 7 categories, happy (6), pleasure (2), relax (5), fear (5), sad (5), disgust (5), and no emotion (9). All films categorized in the peace/relaxation category represented pleasant nature scenes without human actors (21A, 21B, 21C, and 21G), except one (clip 21D) in which a woman contemplates the twilight. All clips included in the happiness/joy category (21H, 22A, 22B, 22E, 23A, and 23B) represented scenes describing affiliative situations where babies, children, or young animals appear in play situations or in positive interactions with peers or adults. Finally, the two clips assigned to the pleasure/ well-being category (23C and 23D) represented heterosexual couples in erotic attitude. As for the negative clips, the disgust category included five film fragments representing the shedding of human body fluids Journal of Psychophysiology (2018), 32(1), 1–19

Figure 1. Mean valence and arousal ratings for the positive, negative, and neutral clip categories in Experiment 1.

(11A, 12A, and 12H) or disgusting animals (12G and 12I), two classes of stimuli that are among the most common releasers of disgust reactions (Haidt, McCauley, & Rozin, 1994). Sadness clips represented human actors or animals in different life-threatening situations. Three of these clips (11C, 11F, and 12E) involved bloodshedding, while two additional fragments represented a baby’s medical intubation (12J) or a man showing the stump of his arm (12C).

Finally, the fear category included two clips (11G and 11H) representing destruction caused by natural disasters, threat of human or animal origin (11I and 11J), and a dying woman (12D). Detailed information on the self-report results for each clip is given in Appendix C. The thematic content was fairly consistent within each positive emotion category. In contrast, the sadness/sorrow and fear/anxiety categories included clips of relatively heterogeneous content. Based on the percentage choice of the different emotion labels that the participants used to describe their emotional experience an ambiguity index (AI) was computed for each individual film (FernándezCahill, 2012). This index allowed an estimation of the extent to which a particular clip had induced different emotional states. The AI Index was calculated according to the following formula:

AI ¼

Xi X max

ð1Þ

where Xi is the average percentage choice of all emotion labels except the one most frequently selected and Xmax is the percentage choice of the most frequently selected label. Using this formula, higher AI values indicate higher ambiguity, with 0 indicating no ambiguity and 1 maximum ambiguity. The AI values for each film clip are given in Appendix C. The analysis based on specific emotion categories yielded a significant effect, F(6, 37) = 4, p < .001, η2 = .45. Post hoc comparisons Ó 2016 Hogrefe Publishing

L. Aguado et al., Responses to Emotional Clips

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Figure 2. Mean valence and arousal ratings for clips of different emotion content in Experiment 1.

showed that fear and sad clips were significantly more ambiguous than neutral ones (ps < .05).

Valence and Arousal Ratings According to Emotion Category Figure 2 presents the average valence and arousal ratings according to the emotion categories described above.

Independent one-way ANOVAs yielded a highly significant effect of Emotion, F(6, 37) = 111, p < .001, η2 = .96, and F(6, 37) = 63.32, p < .001, η2 = .93, for the valence and arousal ratings, respectively. Post hoc comparisons showed significant differences between the neutral clips and the rest of categories and between each positive category and each of the negative categories (ps < .001). No significant differences in valence ratings were obtained between clips of similar valence and different emotion content.

Nevertheless, differences between clips of positive valence did appear in the case of arousal ratings. Relaxing films were rated as significantly less arousing than the other two positive categories of positive films (pleasure or happiness) (ps .01). No differences in arousal were observed between negative emotion categories.

Discussion Evaluative ratings of a new set of short film clips with emotional content yielded the expected differences between positive and negative films. However, arousal ratings revealed that negative films were perceived in general as more arousing than both positive and neutral ones. Average arousal of positive clips was relatively low and no different from that of neutral films. Consistent with Ó 2016 Hogrefe Publishing

this, the less populated sections of the affective space defined by the combination of valence and arousal ratings were those corresponding to the negative/low arousal and positive/high arousal quadrants. The particular distribution of negative stimuli over the affective space observed in the present study is not uncommon in research on emotion. In studies with the IAPS collection the negative/low arousal quadrant is usually the less populated section of the affective space (e.g., Lang, Bradley, & Cuthbert, 2008; Ribeiro, Pompéia, & Bueno, 2005) and typical contents include nature pollution, starving children, and cemeteries that were not represented in our clip collection. On the other hand, while pictures of erotica appear frequently in the positive/high arousal quadrant, only 3 of our 20 positive films represented this type of content. The more represented contents in the positive film category were babies and nature scenes that usually tend to receive low arousal ratings. Thus, although not all sections of the affective space were equally represented in our film collection, valence and arousal ratings were consistent with those found for similar contents with still pictures.

The emotion categories selected according to the selfreport measures were not similarly homogeneous in terms of thematic content. Sad and fear films were the most ambiguous, that is, the ones that produced more varied self-reported emotions. Differences in rated arousal appeared between positive films of different emotion content. Relaxing films were evaluated as significantly less arousing than happy and pleasure films. This is consistent with previous studies that have found a differentiation between positive arousing and relaxing pictures (e.g., Bradley, Codispoti, Cuthbert, & Lang, 2001; Bradley, Journal of Psychophysiology (2018), 32(1), 1–19

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Codispoti, Sabatinelli, & Lang, 2001; Ribeiro et al., 2007).

The absence of differences in arousal between negative films is not surprising given that most negative clips contained scenes associated to different varieties of threat, physical harm, or strong disgust.

In summary, the collection of film clips here described provides a set of dynamic emotional stimuli that show consistent differences in terms of basic affective dimensions and emotional content. Moreover, the set includes films that are effective in inducing differentiated emotional states as measured via self-report. These characteristics, together with the short and fixed duration of the films, seem particularly suited to the study of the psychophysiological differentiation of affective states. In Experiment 2, we present psychophysiological data obtained with a subset of clips belonging to different positive and negative emotion categories.

Experiment 2 The goal of the present experiment was to study the different patterns of physiological reactivity in response to positive and negative clips of different emotion content.

To this end, we employed two measures that are routinely used in emotion research, electrodermal activity, and facial EMG. These two measures were chosen because they are differentially sensitive to variations in the valence and arousal dimensions. Increased electrodermal activity is usually observed in the presence of highly arousing stimuli (e.g., Greenwald, Cook, & Lang, 1989; Lang et al., 1993).

On the other hand, affectively positive and negative stimuli increase activity on the Zygomaticus Major (ZM) and Corrugator Supercilii (CS) muscle regions, respectively (Bradley, Codispoti, Cuthbert, & Lang, 2001; Greenwald et al., 1989; Lang et al., 1993).

There is abundant evidence on the ability of emotional pictures to elicit physiological reactions and changes in facial activity (e.g., Bradley et al., 2001; Dimberg, 1990; Greenwald et al., 1989; Lang et al., 1993; for a review see Bradley & Lang, 2007). Although less abundant, there is also evidence on the sensitivity of these measures to the emotional content of films (e.g., Kreibig et al., 2007; Palomba et al., 2000). There are, however, some important methodological and theoretical differences between these two sets of studies. Studies using films usually include a smaller set of stimuli and there are important variations in the contents represented in different studies. Moreover, films of different durations have often been employed in the same study, a characteristic that may be problematic when using physiologically dependent variables.

Based on the traditional assumption that emotional states are accompanied by differentiated patterns of physiological Journal of Psychophysiology (2018), 32(1), 1–19

L. Aguado et al., Responses to Emotional Clips

arousal (for recent reviews see Kreibig, 2010; Mauss & Robinson, 2009; Norman, Bernston, & Cacioppo, 2014), studies with films have sought to reveal the patterns of bodily responses associated to different categories of emotional experience. In the present experiment, electrodermal (skin conductance response, SCR) and facial EMG responses were measured in the presence of positive and negative film clips. These variables were selected because of their sensitivity to affective variables. Skin conductance and fEMG are differentially sensitive to the basic affective dimensions of valence and arousal, with skin conductance responses covarying with subjectively rated arousal and fEMG showing different response patterns in response to positively and negatively valenced stimuli. However, conjoint use of these variables may reveal different patterns that would allow us to differentiate the responses to clips of different emotion content, that is, differences that would go beyond those expected based solely on valence and arousal ratings. In fact, studies reporting differentiated patterns of response associated to different discrete emotions have employed multiple measures of psychophysiological activity (e.g., Stemmler, 2004; Stephens, Christie, & Friedman, 2010).

Two types of contents were selected for each valence category, happiness and relax for the positive category and fear and disgust for the negative one. Given the characteristics of the clips selected for the present experiment, a key question was the relative role of basic affective dimensions (valence and arousal) and emotion category in determining the pattern of responses to films. In Experiment 1, happy and relaxing films received similar high valence ratings but differed in terms of arousal. On the other hand, fear and disgust films received similar low ratings in valence and similar high ratings in arousal. If the psychophysiological response pattern depends only on valence and arousal, then valence-sensitive measures (fEMG activity) should show no differences between films receiving similar valence ratings and differences in arousal-sensitive measures (electrodermal activity) should appear only between films rated as different in arousal, as is the case of happy and relax films. Response patterns at variance with these predictions would instead reveal an influence of emotion content beyond the basic dimensions of valence and arousal.

Materials and Method Participants A new participant’s sample of 38 students (19 males and 19 females, M = 19.55, SD = 1.49, age 18–24 years) from the Universidad Complutense of Madrid voluntarily took part in this study in exchange for course credits. All participants reported having no history of neurological or psychiatric disorders. Informed consent was obtained before starting the experiment. Ó 2016 Hogrefe Publishing

L. Aguado et al., Responses to Emotional Clips

Stimuli and Procedure Thirty film clips were selected from the set described in Experiment 1.2 Assignment of clips to the different emotion categories was based on the self-report data obtained in Experiment 1. The selection contained 11 positive clips, 10 negative clips, and 9 neutral clips. Two positive emotion categories, happiness (6) and relax (5), were selected.

As for the negative categories, films representing fear (5) and disgust (5) were selected. The clips were presented on the screen of a 2300 LCD monitor (Samsung SyncMaster 244T), inside a 512 512 pixels square, and on a 50% gray background. The experimental sessions were carried out individually in a soundproof room. The software E-Prime 2.0 was used for stimulus presentation and response collection. Participants were seated at a distance of 50 cm from the computer screen. Note that clips selected in Experiment 2 were less ambiguous (AI index) than clips of the same category not selected for this experiment (see Table 1).

A block design was employed, with films of similar valence presented on each of three successive blocks.

All participants saw the neutral films first, followed by the positive and negative blocks in a counterbalanced order.

Participants were asked to rate each film in terms of valence and arousal by clicking over the appropriate section of the SAM valence and arousal scales presented on the screen. Intertrial interval was 10 s. After finishing the experimental session, the participants were thanked for their contribution and debriefed.

SCR and fEMG Signal Acquisition and Analysis The experimental environment was carefully prepared so as to ensure that no electronic devices could contaminate the fEMG/SCR signal. Average temperature in the test room was 22 °C, recording of fEMG and SCR was done through a PowerLabÓ 8/30 system. The SCR signal was registered using ML116 GSR Amp and finger electrodes placed on the volar surface of the distant phalange of the index and middle fingers of the nondominant hand (Cacioppo, Tassinary, & Berntson, 2007). The fEMG signal was registered using four active electrodes corresponding to two distinct bipolar montages. Miniature surface electrodes (4 mm, Ag/AgCl) filled with electrode gel were attached on the left side of the face over the ZM and CS muscle regions, following Fridlund and Cacioppo’s (1986) guidelines. An additional ground electrode was placed on the elbow. Simple motor and cognitive tasks (e.g., eyes closing and opening, counting backwards) were used during participant’s preparation in order to ascertain proper electrode functioning and mask the intention of the experiment.

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Table 1. Ambiguity index means (Experiment 1) for clips selected and not selected for Experiment 2, according to different content

Neutral

Selected

Not selected

t

df

p

d

0.020

–

–

–

–

–

Happy

0.057

0.198

5.829

8

< .001

4.12

Relax

0.066

0.245

5.902

5

.002

5.27

Fear

0.104

0.200

2.885

6

.029

2.35

Disgust

0.078

–

–

–

–

–

Electrodermal activity was continuously recorded using the LabChartÓ application (ADInstruments, Dunedin, New Zealand) at a 400 Hz sampling rate. Data were segmented into two different epochs per trial. The first epoch corresponded to the pre-stimulus 1,000 ms period and was used as a baseline. The second epoch corresponded to the 2,000–10,000 ms film period. The dependent variable was the amplitude of the Skin Conductance Response (SCR). Baseline electrodermal activity for each block was calculated by averaging over the 1,000 ms period immediately preceding each stimulus. Data corresponding to the first 2,000 ms of each clip were excluded from analysis to avoid possible contamination by orienting responses produced by stimulus onset. Changes in skin conductance that exceeded 0.05 μS were scored as stimulus evoked responses during each trial. Skin conductance responses were baseline-corrected (using the average baseline for the corresponding block) prior to statistical analyses. The Change Score for each stimulus-presentation period was calculated by subtracting the average baseline from the maximum peak within the 2,000–10,000 ms film period. In order to evaluate possible emotional post-effects, a Change Score was also calculated for the 500 ms period immediately following stimulus offset (Change Score-Post).

In what follows, we will refer to the change score corresponding to the 2,000–10,000 ms period during clip presentation as Change Score 1 and to the score corresponding to the 5 s period following stimulus offset as Change Score 2.

The fEMG was continuously recorded at 1 K/s with an online 50–400 Hz band-pass digital filter. Data were segmented into 11,000 ms epochs, corresponding to clip duration plus a 1,000 ms pre-stimulus period. The signal was full-wave rectified and smoothed over 200 ms periods.

The values corresponding to the average fEMG activity during the pre-stimulus period of each clip were used as a baseline. The procedure used by Moody and McIntosh (2011) was employed to analyze the fEMG data. The stimulus-presentation period was divided into two 5,000 ms time bins (t1 and t2) for statistical analysis.

Film clips presented in Experiment 2: Neutral: 00A, 00C, 00D, 00E, 00F, 00G, 00H, 00I, 00J. Happy: 21H, 22A, 22B, 22E, 23A, 23B. Relax: 21A, 21B, 21C, 21D, 21G. Fear: 11G, 11H, 11I, 11J, 12D. Disgust: 11A, 12A, 12G, 12H, 12I.

Ó 2016 Hogrefe Publishing

Journal of Psychophysiology (2018), 32(1), 1–19

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L. Aguado et al., Responses to Emotional Clips

Table 2. Valence and arousal ratings for the different emotion content in Experiment 2 Emotion category

Mean valence

SEM

Mean arousal

SEM

Happy

7.65

0.11

5.41

0.22

Relax

7.14

0.15

2.90

0.24

Fear

2.89

0.15

6.73

0.19

Disgust

2.33

0.11

6.65

0.20

Neutral

5.28

0.08

4.52

0.16

Note. SEM = Standard Error of the Mean.

Results Analysis of valence and arousal ratings at the participant level is presented first followed by the analysis of electrodermal and fEMG activity.

Valence and Arousal Ratings Average valence and arousal ratings for the five selected film categories are presented in Table 2. Valence and arousal ratings were analyzed in terms of Emotion Content (happy, relax, fear, disgust, and no emotion) and participant Sex. A mixed 5 2 ANOVA of the valence ratings gave a significant main effect of Emotion, F(2.72, 98) = 410, p < .001, η2 = .91, and a significant effect of Emotion Sex interaction, F = 5.09, p < .005, η2 = .12. All post hoc comparisons between emotion categories were significant, indicating that all five clip categories differed in terms of valence. Happy clips were rated as more positive than relax clips (p < .05) and clips of both categories were rated more positively than fear, disgust, and neutral clips (ps < .01).

In the case of negative clips, those representing disgust were rated as more negative than fear clips (p < .05) and both categories were in turn rated more negatively than positive and neutral clips (p < .01). Female participants tended to give disgust and fear clips lower valence ratings than male participants (p < .05). A significant effect of Emotion was also found on the arousal ratings, F(2.56, 92) = 80, p < .001, η2 = .69. Post hoc comparisons showed higher arousal ratings for fear and disgust films than for happy, relax, and neutral films. Moreover, happy clips were rated as significantly more arousing than relax clips (all ps < .05).Note. SEM = Standard Error of the Mean.

Electrodermal Activity Figure 3 presents the average SCR change scores for the five emotion categories. A 5 2 2 ANOVA applied to SCR change scores with Emotion (5) and Time (2) as repeated-measures factors and participant Sex as the between-subjects factor gave a significant effect of Emotion, F(2.6, 95) = 8.6, p < .001, η2 = .19. No other significant effects were obtained. Post hoc comparisons revealed significantly larger SCRs in the presence of fear Journal of Psychophysiology (2018), 32(1), 1–19

Figure 3. Skin conductance responses for the different emotion categories in Experiment 2.

compared to neutral, happy, and relaxing clips (ps < .05).

Disgust did not differ from fear clips but did produce larger SCRs than relaxing films (p < .05). Significant differences were also found between films of positive valence. In this case, larger responses were produced by happy compared to relax films (p = .05).

Finally, significant differences were found in baseline electrodermal activity between clips of different valence, F(2, 27) = 1,734.98, p < .001, η2 = .99, and content, F(4, 25) = 876.52, p < .001, η2 = .99. Bonferroni-corrected comparisons showed that activity at baseline was significantly different between clips of different valence (ps < .001). However, no significant differences appeared in this measure between films of different emotion content but similar valence. Table 3 shows the mean and standard deviation of SCR levels at baseline for each type of clip.

Facial EMG (fEMG) Data from five participants had to be deleted because of excessive movement during the experiment. The final sample consisted of 33 participants (17 females, 16 males).

Separate 5 2 2 ANOVAs (Emotion Time Sex) were performed on EMG zygomatic and corrugator activity data.

Average responses are shown in Figures 4 and 5.

ZM Activity Analysis of ZM activity in the presence of positive (happy and relax clips), neutral and negative clips (fear and disgust) yielded significant effects of Emotion, F(4, 124) = 32.36, p < .001, η2 = .50, Time, F(1, 31) = 6.92, p = .013, η2 = .18, and its interaction, F(4, 124) = 6.69, p < .001, η2 = .18. No significant effects involving Sex were obtained.

Happy films produced larger responses than the other film categories at Time 1 and Time 2 (ps < .001). Happy films produced the largest ZM responses at Time 1 and Time 2, followed by disgust, fear, neutral, and relax films. Except in the case of happy films, significant changes in ZM Ó 2016 Hogrefe Publishing

L. Aguado et al., Responses to Emotional Clips

9

Table 3. Mean baseline SCR amplitude according to clip valence and emotion content M

SD

Neutral

2.378

0.006

Positive

2.839

0.013

Negative

2.639

0.027

Neutral

2.378

0.006

Happy

2.834

0.005

Relax

2.844

0.017

Fear

2.646

0.026

Disgust

2.633

0.029

Clip valence

Clip content

Figure 5. EMG activity (corrugator muscle) for the different emotion categories in Experiment 2. t = Time.

Figure 4. EMG activity (zygomaticus muscle) for the different emotion categories in Experiment 2. t = Time.

response appeared along the film’s duration (ps < .05).

While ZM activity decreased in the presence of relax, neutral, and fear films, it increased in the presence of disgust films.

CS Activity Analysis of the data corresponding to the EMG activity over the CS region gave only a significant main effect of Emotion, F(4, 124) = 8.51, p < .001, η2 = .22. In this case, disgust films produced overall larger responses than happy and relax films (p < .01). More importantly, disgust films produced larger responses than fear (p < .05) films that in turn did not differ from the other categories.

Subjective Ratings and Psychophysiological Measures: Correlational Analysis Analysis of the covariation of subjective ratings and electrodermal activity during the stimulus and poststimulus

Ó 2016 Hogrefe Publishing

periods showed a positive correlation between SCR amplitude and arousal, rs = .28 and .24 for the Change Score 1 (during clip) and Change Score 2 (5 s period following stimulus offset), respectively (ps < .01), showing that the clips that were rated as more arousing tended to produce larger SCR changes at both time periods. Arousal ratings also showed a positive correlation with total EMG zygomatic activity, r = .33 (p < .01). Significant negative correlations were found between valence ratings and electrodermal activity at Change Score 1 and Change Score 2, rs = .28 and .29, respectively (ps < .01), showing that clips that received lower valence ratings also tended to produce larger SCR increases. Significant correlations were also shown between fEMG activity and subjective ratings of valence and arousal. A significant negative correlation was found between valence ratings and total EMG corrugator activity, r = .30. Finally, a positive correlation was obtained between arousal ratings and total ZM activity (ps < .01).

Discussion In the present experiment, we report psychophysiological (skin conductance and fEMG) results in response to a selection of a new collection of emotion film clips described in Experiment 1. Moreover, in order to establish the relationship between self-report and psychophysiological results, ratings in the general dimensions of valence and arousal are also presented. Electrodermal activity covaried with perceived arousal in a predictable way. Fear and disgust films that received the highest ratings in arousal also produced larger SCRs. Moreover, happy films received

Journal of Psychophysiology (2018), 32(1), 1–19

10

higher arousal ratings and produced larger SCRs than relaxing films. The negative correlation obtained between valence and SCR amplitude can be attributed to the specific contents represented in the positive and negative film categories. While the negative category included highly arousing fear and disgust scenes, the positive category included arousing happy scenes and relaxing nature scenes.

This explains why positive film clips as a whole tended to produce smaller SCRs than negative ones.

Facial EMG activity showed a complex relationship with affective valence, especially in the case of zygomatic responses. Although they were rated as similarly positive, happy films produced larger ZM responses than relax films.

In fact, films representing relaxing scenes produced a decrease in ZM activity along clip duration. Somewhat unexpectedly, a significant increase in ZM activity was observed along the duration of disgust films. Disgust films also produced a significant increase in corrugator activity.

In contrast, no significant changes in fEMG activity were observed in the presence of fear films. This difference between disgust and fear stimuli is consistent with previous reports that have also shown that corrugator activity differentiates between these two emotional contents (Yartz & Hawk, 2002). The implications of these results are elaborated in more detail in the General Discussion section.

We should point out that, in comparison with Experiment 1, the use of a block design is a potential limitation of the present experiment. This design may have produced expectancy effects due to the repetition of clips of similar affective valence on the same block. This might produce either sensitization or habituation effects that might, respectively, lead to increased or decreased psychophysiological reactivity. The use of blocked or randomized presentation in psychophysiological studies is a complex decision as randomized presentation has its own problems, for example due to the presentation of stimuli of opposing valence in adjacent trials that might lead to contrast effects or to the confounding of the effects of the current clip with the post-effects of the previous stimulus of opposing valence.

Other differences between Experiments 1 and 2 should be noted. For example, the assessment of valence and arousal was collective in Experiment 1, while it was carried out individually in Experiment 2. Also, the clips were presented in different displays: 12000 projector screen (Experiment 1) versus 2300 LCD monitor (Experiment 2).

Therefore, a direct comparison between the mean rating results obtained in Experiments 1 and 2 was computed to check for potential differences between both experiments.

Tables 4 and 5 summarize the results of this comparison for the valence and arousal ratings. No statistically significant differences between studies were found in the valence ratings, showing that the different administration conditions did not have an effect on affective ratings. However, Journal of Psychophysiology (2018), 32(1), 1â&#x20AC;&#x201C;19

L. Aguado et al., Responses to Emotional Clips

Table 4. Valence assessment for clips presented in Experiment 1 and Experiment 2 according to different content Valence Experiment 1

Neutral

Experiment 2

Differences

M

SD

M

SD

t

df

p

d

5.24

0.19

5.28

0.21

0.43

16

0.671

0.22

Happy

7.40

0.29

7.65

0.22

1.04

8

0.326

0.73

Relax

7.04

0.43

7.14

0.34

0.19

8

0.851

0.13

Fear

3.04

0.47

2.89

0.50

0.77

6

0.467

0.63

Disgust

2.90

0.53

2.33

0.27

2.17

8

0.062

1.53

there were significant differences in the case of the arousal ratings, with the clips in Experiment 2 being rated as more arousing than in Experiment 1. This can be attributed to the presentation procedure used in Experiment 2 that probably increased the emotional impact of the clips. This notwithstanding, it must be said that the rank order of the arousal ratings according to the emotional content of the clips was the same in both experiments, (Relax < Neutral < Happy < Disgust < Fear).

General Discussion The present paper presents evaluative and psychophysiological data on a new collection of emotional film clips.

In Experiment 1, rating and self-report results are presented, allowing a characterization of the film collection in terms of both basic affective dimensions and emotion categories. In Experiment 2, we report psychophysiological (skin conductance and fEMG) results in response to a selection of the film clips described in Experiment 1. In this last study, skin conductance results covaried with subjectively perceived arousal in a predictable way, with larger response amplitudes in the presence of more arousing clips.

The response of facial musculature, measured through the EMG activity over the zygomaticus and corrugator muscle regions, was sensitive to affective valence and to differences in specific emotion content.

The present study is the first to present self-report ratings related to both general affective dimensions (valence and arousal) and emotion category together with psychophysiological measures using short, fixed duration film clips. Apart from the higher realism and emotional impact of dynamic stimuli, the present collection of emotion clips has characteristics that make it appropriate for behavioral and psychophysiological research. Among these, the fixed duration of 10 s for all clips is especially convenient because it reduces the variability introduced by the use of clips of different durations, as has been done in previous research.

Moreover, the categorization of the film clips in terms of Ă&#x201C; 2016 Hogrefe Publishing

L. Aguado et al., Responses to Emotional Clips

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Table 5. Arousal assessment for clips presented in Experiment 1 and Experiment 2 according to different content Arousal Experiment 1 M

Experiment 2 SD

M

Differences SD

t

df

p

d

Neutral

2.71

0.57

4.52

0.38

7.76

16

< .001

3.68

Happy

3.07

0.34

5.41

0.67

6.86

8

< .001

4.85

Relax

1.90

0.16

2.90

0.36

5.59

8

.001

3.95

Fear

5.89

0.31

6.73

0.27

4.4

6

.005

3.59

Disgust

5.32

0.41

6.65

0.14

6.76

8

< .001

4.78

discrete emotions makes the present collection especially appropriate for the study of subjective and psychophysiological reactions associated to different emotional states.

Based on the self-report responses (Experiment 1), we could assign each film clip to one of seven specific emotion categories, happiness, relax, pleasure, anger, fear, disgust, sadness, and neutral. The positive film set included clips that were rated as high (happiness and pleasure) and low (relax) in arousal. This parallels the difference observed between positive arousing and de-arousing pictures in studies with the IAPS collection (e.g., Bradley, Codispoti, Cuthbert, & Lang, 2001; Bradley, Codispoti, Sabatinelli, & Lang, 2001; Ribeiro et al., 2007). In contrast to this, all categories of negative films received high arousal ratings.

The absence of negative films rated as low in arousal is consistent with the failure to find a significant number of negative deactivating stimuli in most prior research with emotional stimuli. The categories with less exemplars meeting a predetermined inclusion criterion were pleasure and anger. For example, only one film reached the criterion to be included in the category “anger.” This result is consistent with those of previous studies showing that emotional pictures are not an effective means to elicit anger in the laboratory (e.g., Mikels et al., 2005; Thibodeau, Jorgensen, & Jonovich, 2008) and indicates that film clips are also not effective as anger elicitors (see also Gross & Levenson, 1995).

The validity of the emotion categories derived from the participant’s self-report measures in Experiment 1 was partially confirmed by the patterning of autonomic and facial responses in Experiment 2. As expected, electrodermal activity reflected between-category differences in rated arousal. Consistent with these differences participants gave larger SCRs to happy than to relax films. On the other hand, consistent with the lack of differences in rated arousal between fear and disgust films, these two categories elicited similar large SCRs. In contrast to this, the analysis of fEMG data revealed differences between thematic contents that could not be predicted solely on the basis of evaluative ratings of valence and arousal. In the case of positive clips, happy and relaxing scenes had opposed effects. Zygomatic activity was larger in the presence of happy compared to Ó 2016 Hogrefe Publishing

relaxing films. The deactivating effect of relaxing films was shown as a decrease of ZM activity along the clip’s duration. Only negative films representing disgust scenes produced a facial pattern that significantly differed from that observed in the presence of neutral films. Disgust films produced larger corrugator responses than positive films and than those representing fear scenes. Moreover, zygomatic activity increased significantly along the duration of these films. A similar finding has been reported in some studies (Bradley, Codispoti, Cuthbert, & Lang, 2001; de Jong, Peters, & Vanderhallen, 2002) but it is not clear if these responses are part of an exaggerated facial grimace produced by disgusting images (e.g., Burton, 2011) or are due to cross talk from other muscles.

The different patterns of psychophysiological response reported in the present study provide a picture of the affective impact of different positive and negative contents that goes beyond what would be expected based only on valence ratings. This confirms the usefulness of film clips to study the patterns of response associated to different emotional states. The differences observed in Experiment 2 between happy and relaxing films partially replicate the results of previous studies with pictures. For example, in Bradley, Codispoti, Cuthbert, and Lang (2001) study, pictures of families with contents similar to those of our “happy” category elicited larger ZM activity than relaxing scenes. However, in that same study, families and nature pictures elicited similar small SCRs. This is in clear contrast with the increase in electrodermal activity observed in our study in the presence of happy clips. On the other hand, smaller SCRs in the presence of both arousing and deactivating positive pictures were observed in a study by Ribeiro et al. (2007). Moreover, in this last study, superior zygomatic activity was observed in response to positive relaxing compared to positive arousing pictures. These differences might be due to the different characteristics of the stimulus materials employed in each study. Of course, one main difference with the present study was the use of static picture stimuli. However, it should be noted that there are important differences in the specific contents included in ours and in each of the previously mentioned studies. For example, in the study by Journal of Psychophysiology (2018), 32(1), 1–19

12

Ribeiro et al. (2007), the positive arousing category included highly varied contents with or without the presence of human actors (erotic couples, fireworks, nature sports. . .). Similarly, varied contents were included in the positive deactivating category (e.g., babies, couples, nature scenes). In contrast to this, each of the arousing and deactivating categories in our study included more homogeneous contents (babies or animal juveniles in the arousing category and nature scenes in the deactivating category).

Thus, it may be that the results obtained by Ribeiro et al.

(2007) partly reflect the greater heterogeneity of the contents included in the different picture categories.

For example, in that study the positive arousing category included couples in an erotic attitude that tend to produce smaller changes in zygomatic activity (Bernat, Patrick, Benning, & Tellegen, 2006) and can even produce increased corrugator activity, especially in women (Bradley, Codispoti, Sabatinelli, & Lang, 2001).

Facial EMG activity differentiated between the two categories of negative clips, fear and disgust, was facial EMG activity. Facial reactivity was, in general, stronger in the presence of disgust films, with increased corrugator activity and a small but significant increase in zygomatic activity.

Previous studies have shown that the main characteristic of the facial response to disgusting stimuli is an increase of activity of the levator labii superioris muscle, followed in strength by corrugator activity and sometimes a small increase in zygomatic activity (Bradley, Codispoti, Cuthbert, & Lang, 2001; de Jong et al., 2002; Vrana, 1993). In correspondence with the similar arousal ratings given to fear and disgust films, both elicited similar large SCRs. The results of Experiment 2 revealed that there was a good correspondence between the subjective ratings of the emotion clips and the psychophysiological reactions they elicited. However, when the pattern of skin conductance and fEMG responses is considered, it is also clear that there are variations that go beyond those predicted solely in terms of basic affective dimensions. This was the case of the two categories of negative clips, that is, fear and disgust.

These results are relevant for the classic controversy over the specificity of the response patterns associated to different discrete emotions (see Kreibig, 2010; Norman et al., 2014, for recent reviews) and provide new evidence for differentiated response patterns corresponding to different negative emotions that are similarly rated in terms of valence and arousal.

A limitation of the study is that a factor of potential relevance, the presence of human interaction in the clips, was not taken into account and controlled for. This might have brought a certain variability both within- and between-categories (e.g., there were more scenes representing human interaction or with human actors in the negative category). We recognize that this is a relevant aspect that Journal of Psychophysiology (2018), 32(1), 1–19

L. Aguado et al., Responses to Emotional Clips

deserves consideration in future research with emotional clips.

The combination of self-report and psychophysiological measures in the present study confirms the categorical structure of a new set of emotional films that includes clearly differentiable emotional categories, together with neutral control clips. The results obtained with the electrodermal and facial EMG measures show that psychophysiological responses to emotional stimuli cannot be predicted solely on the basis of general affective dimensions. These results are consistent with previous evidence that the specific thematic content related to different basic emotions is a strong determinant of psychophysiological responding to visual stimuli (e.g., Bernat et al, 2006; Bradley, Codispoti, Cuthbert, & Lang, 2001; Bradley, Codispoti, Sabatinelli, & Lang, 2001; Mikels et al., 2005; Ribeiro et al., 2007) and extends this conclusion to film clips that represent realistic emotional scenes that are closer to the emotional events we experience in daily life.

Acknowledgments This work was supported by the Spanish Ministerio de Economía y Competividad [grant number PSI201344262-P to Luis Aguado]. The participation of Francisco J. Román has been possible thanks to a FPI Grant (PSI2010-20364) from the Spanish Ministerio de Ciencia y Tecnología.

Ethics and Disclosure Statements Informed consent was obtained from all participants.

All authors disclose no actual or potential conflicts of interest including any financial, personal, or other relationships with other people or organizations that could inappropriately influence (bias) their work.

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Biological Psychology, 59, 55–68. doi: 10.1016/S0301-0511 (01)00121-1 Received June 3, 2015 Accepted April 27, 2016 Published online November 22, 2016

Luis Aguado Facultad de Psicología Campus de Somosaguas Universidad Complutense de Madrid 28223 Madrid Spain laguadoa@ucm.es

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L. Aguado et al., Responses to Emotional Clips

15

Appendix A Information about the clips presented in Experiment 1 Movie data (name – author – producer – year)

Clip start time* (hh:mm:ss)

Description

Negative clips 11A 11B

11C 11D

11E 11F

11G 11H 11I 11J

12A

12B

12C

12D 12E 12F 12G 12H 12I 12J

Benny’s Video – Michael Haneke – Bernard Lang, Wega Films – 1992 À l’intérieur – Alexandre Bustillo, Julien Maury – Canal+, CinéCinéma, Cofinova 3, Soficinéma 3, Uni Etoile 4, La fabrique de Films, BR Films – 2007 The Three Burials of Melquíades Estrada – Tommy Lee Jones – Europa Corp., Javelina Film Company – 2005 À l’intérieur – Alexandre Bustillo, Julien Maury – Canal+, CinéCinéma, Cofinova 3, Soficinéma 3, Uni Etoile 4, La fabrique de Films, BR Films – 2007 The Three Burials of Melquíades Estrada – Tommy Lee Jones– Europa Corp., Javelina Film Company – 2005 À l’intérieur – Alexandre Bustillo, Julien Maury – Canal+, CinéCinéma, Cofinova 3, Soficinéma 3, Uni Etoile 4, La fabrique de Films, BR Films – 2007 Wild Caribbean (Cap. 3) – BBC Series 4 – British Broadcasting Corporation (BBC) – 2007 Wild Caribbean (Cap. 3) – BBC Series 4 – British Broadcasting Corporation (BBC) 2007 Tiburones. Los ataques más terroríficos del mundo – Discovery Channel – Discovery Communications, Inc. – 2003 Il Mio Nome è Nessuno – Sergio Leone, Tonino Velerii – Riato Film Preben-Philipsen, Les Films Jaques Leitienne, Imp.Ex.Ci., Rafran – 1973 À l’intérieur – Alexandre Bustillo, Julien Maury – Canal+, CinéCinéma, Cofinova 3, Soficinéma 3, Uni Etoile 4, La fabrique de Films, BR Films – 2007 À l’intérieur – Alexandre Bustillo, Julien Maury – Canal+, CinéCinéma, Cofinova 3, Soficinéma 3, Uni Etoile 4, La fabrique de Films, BR Films – 2007 Tiburones. Los ataques más terroríficos del mundo – Discovery Channel – Discovery Channel – Discovery Communications, Inc. – 2003 Saibogujiman kwenchana (I’m A Cyborg, But That’s Ok) – Moho Films – Park Chan-wook–2006 Benny’s Video – Michael Haneke – Bernard Lang, Wega Films – 1992 Insect Wars – National Geographic – National Geographic Society Entertainment – 2003 Insect Wars – National Geographic – National Geographic Society Entertainment – 2003 Insect Wars – National Geographic – National Geographic Society Entertainment – 2003 Insect Wars – National Geographic – National Geographic Society Entertainment – 2003 Science of Babies – Peter Yost – National Geographic Society Entertainment –2006

00:33:21

Someone moving a bloodstained corpse

00:32:31

Crying woman with seriously injured face

00:39:00

Injured man spitting blood out

00:41:23

Woman being stabbed

00:10:25

Man punching woman

00:01:12

Wrecked car in an accident scene and bloodstained victims

00:04:59

Destruction caused by natural disasters

00:05:09

Destruction caused by natural disasters

00:01:04

Shark biting a bait

05:34:10

A razor grazing a hand

00:15:56

Woman being sick (vomiting)

00:42:15

Very anxious smoking woman

00:32:35

Man showing his stump

00:06:41

Dying woman with cables in her bloody wrist

00:00:31

Pig slaughtering season

00:08:26

Spider walking and biting a sleeping man

00:21:06

Spider walking around a kitchen

00:25:55

Someone pulling a leech off of his skin

00:05:38

Scorpion eating a cockroach

00:04:28

Baby0 s medical intubation

Neutral clips 00A

Bin-jip (Hierro 3) – Kim Ki-duk – Kim Ki-duk Films – 2004

00:01:33

Man walking on the street

00B

Aliens of the Deep – James Cameron – Walden Media – 2005

00:39:13

Aquatic plant making bubbles

00C

Ken Park –Larry Clark, Edward Lachman – The Kasander Films Company, Busy Bee Productions – 2002 The Terminal – Steven Spielberg – Amblim Entertainment, Dreamworks SKG, Parkes/MacDonald Productions – 2004

01:04:49

Someone arriving at home by car

00:32:09

Airport coffee shop

00D

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L. Aguado et al., Responses to Emotional Clips

(Continued) Movie data (name – author – producer – year)

Clip start time* (hh:mm:ss)

Description

The Terminal – Steven Spielberg – Amblim Entertainment, Dreamworks SKG, Parkes/MacDonald Productions – 2004 Oldeuboi (Oldboy) – Park Chan-wook – Kim Dong-joo – 2003

01:57:53

Someone arriving to a hotel by walking

01:31:02

Someone putting cufflinks on his shirt

00:04:14

Elevator going down

00:28:36

Boy drinking water

00I

Poseidon – Wolfgang Petersen – Warner Bros Pictures, Irwin Allen Productions, Next Entertainment, Radiant Productions, Virtual Studios, Synthesis Entertainment, Eyetronics USA – 2006 Benny’s Video – Michael Haneke – Bernard Lang, Wega Films – 1992 Bin-jip (Hierro 3) – Kim Ki-duk – Kim Ki-duk Films – 2004

00:05:30

Man grabbing something from the fridge

00J

Bin-jip (Hierro 3) – Kim Ki-duk – Kim Ki-duk Films – 2004

00:01:47

Man delivering advertising pamphlets

Wild Caribbean (Cap. 2) – BBC Serie 4 – British Broadcasting Corporation (BBC) – 2007 Wild Caribbean (Cap. 2) – BBC Serie 4 – British Broadcasting Corporation (BBC) – 2007 Wild Caribbean (Cap. 2) – BBC Serie 4 – British Broadcasting Corporation (BBC) – 2007 Natural Disasters: Forces of Nature – Sean Casey – Paul Novros, National Geographic Society Entertainment – 2004 Dolphins: The Wild Side – National Geographic – National Geographic Society Entertainment – 1995 Dolphins: The Wild Side – National Geographic – National Geographic Society Entertainment – 1995 Aliens of the Deep – James Cameron – Walden Media – 2005

00:02:38

Fishes swimming into reef

00:03:04

Fishes swimming into reef

00:00:45

Coral reef with subaquatic plants

00:15:11

Woman seeing twilight

00:00:27

Dolphins jumping over the sea

00:07:30

Dolphins swimming and jumping

00:24:20

Jellyfish swimming in the ocean

00:05:51

Young monkeys with their mothers

00:39:38

Flamingos flying

00:04:19

Young monkey scale tree

00:06:47

Baby playing with a toy

00:10:52

Baby interacting playfully with his mother

00:18:31

Baby trying to crawl

00:20:49

Baby trying to crawl

00:29:41

Some babies laughing

00E 00F 00G

00H

Positive clips 21A 21B 21C 21D 21E 21F 21G 21H 21I 21J 22A 22B 22C 22D 22E 23A 23B 23C 23D 23E

Science of Babies – Peter Yost – National Geographic Society Entertainment – 2006 Wild Caribbean (Cap. 1) – BBC Serie 4 – British Broadcasting Corporation (BBC) – 2007 Wild Caribbean (Cap. 4) – BBC Serie 4 – British Broadcasting Corporation (BBC) – 2007 Baby Human (DVD 2. Episodio 6 “To Relate”) – Documania (Dir. Eileen Thalenberg) – Discovery Home and Health – 2003 Baby Human (DVD 2. Episodio 6 “To Relate”) – Documania (Dir. Eileen Thalenberg) – Discovery Home and Health – 2003 Science of Babies – Peter Yost – National Geographic Society Entertainment – 2006 Science of Babies – Peter Yost – National Geographic Society Entertainment – 2006 Science of Babies – Peter Yost – National Geographic Society Entertainment – 2006 In Search of a Midnight Kiss – Alex Holdridge – IFC Films – 2007

00:43:01

Couple playing in the beach

Flowers in the Attic – Jeffrey Bloom – Fries Entertainment Films – 1987 Barely 18#19: 9 to 5 – Christian Knight – Sin City Studio – 2005

00:02:35

Children giving a surprise to their father

00:23:41

A couple kissing sensually

Rosario Tijeras – Emilio Maillé – Mattias Ehrenberg, Gustavo Angel – 2005 Pariah – Randolph Kret – Poor Boy Productions – 1998

00:12:17

A couple making love explicitly

0:07:25

A couple kissing tenderly

Note. *The duration of all clips was 10 s.

Journal of Psychophysiology (2018), 32(1), 1–19

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L. Aguado et al., Responses to Emotional Clips

17

Appendix B Valence and Arousal Means for Each Clip Presented in Experiment 1 Valence and arousal were assessed with SAM (Self-Assessment Manikin) scales. Valence and arousal range was 0–9. “0” depicts lowest levels of arousal and highest negative values while “9” depicts highest levels of arousal and highest positive values.

Valence Mean

Arousal SD

Mean

SD

Negative 11A

1.32

1.17

4.37

1.81

11B

1.08

0.87

5.26

1.60

11C

1.76

1.09

4.63

1.78

11D

0.61

0.87

6.13

1.76

11E

1.53

1.43

5.29

1.92

11F

0.71

0.86

5.47

1.52

11G

2.32

1.30

4.63

1.68

11H

2.18

1.21

4.89

1.87

11I

2.89

1.68

4.97

1.81

11J

2.32

1.38

4.71

1.97

12A

1.66

1.28

4.08

1.88

12B

1.84

1.14

4.58

1.84

12C

2.21

1.40

3.63

1.65

12D

1.34

1.13

5.32

1.62

12E

0.89

0.97

5.63

1.74

12F

1.79

1.51

4.89

2.11

12G

1.95

1.49

4.29

2.01

12H

1.82

1.71

4.97

1.74

12I

2.76

1.49

3.87

1.76

12J

2.13

1.93

4.84

2.12

00A

4.47

1.09

1.34

1.61

00B

5.39

1.44

0.79

1.10

00C

4.16

0.59

1.66

1.84

00D

4.05

1.07

3.11

2.05

00E

4.37

0.96

1.47

1.57

00F

4.24

9.67

1.50

1.93

00G

4.05

1.17

2.08

1.77

00H

4.45

0.91

1.29

1.41

00I

3.97

0.84

1.55

1.71

00J

4.37

1.01

1.58

1.65

Neutral

Positive 21A

6.05

1.50

0.82

1.07

21B

5.97

1.35

0.79

1.00

21C

5.74

1.22

0.89

1.58

21D

6.82

1.14

0.84

1.41

21E

6.58

1.09

2.13

2.03

21F

6.71

1.02

2.87

2.43

21G

5.79

1.54

1.18

1.45

21H

6.53

1.45

1.74

1.67

21I

5.76

1.14

1.50

1.57 (Continued on next page)

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Journal of Psychophysiology (2018), 32(1), 1–19

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L. Aguado et al., Responses to Emotional Clips

(Continued) Valence

Arousal

Mean

SD

Mean

SD

21J

5.84

1.55

1.74

1.55

22A

6.08

1.88

1.92

1.68

22B

6.76

1.27

1.82

1.65

22C

5.87

1.28

1.79

1.44

22D

5.87

1.59

2.03

1.55

22E

7.08

0.96

2.55

2.27

23A

6.55

1.23

2.50

2.16

23B

6.11

1.52

2.37

2.04

23C

5.92

1.40

4.55

1.94

23D

6.29

1.30

5.42

1.70

23E

5.92

1.16

2.58

1.84

Appendix C Selection percentage for each emotion label and results of “Emotional Ambivalence” and “Emotional Ambiguity” indexes for each clip of Experiment 1 Clip code

Neut. label

Pos. label

Neg. label

No Joy/ Pleasure/ Peace/ Fear/ Anger/ Sadness/ Disgust/ Emotional Emotional emotion Happiness Well-Being Relaxation Anxiety Rage Sorrow Revulsion ambivalence ambiguity

11A

7.90

0.00

92.10

8.00

0.00

0.00

0.00

10.50

9.70

21.70

50.00

0.04

11B

2.60

2.60

94.80

2.60

2.60

0.00

0.00

39.50

7.90

42.10

5.30

0.03

0.20

11C

2.60

0.00

97.30

2.60

0.00

0.00

0.00

28.90

0.00

57.90

10.50

0.01

0.10 0.15

Negative 0.14

11D

5.40

0.00

94.50

5.40

0.00

0.00

0.00

48.60

8.10

5.40

32.40

0.03

11E

2.60

2.60

94.80

2.60

2.60

0.00

0.00

7.90

81.60

0.00

5.30

0.03

0.03

11F

0.00

0.00

100.00

0.00

0.00

0.00

0.00

31.60

2.60

60.50

5.30

0.00

0.09

11G

13.20

0.00

86.70

13.20

0.00

0.00

0.00

52.60

2.60

28.90

2.60

0.08

0.13

11H

10.50

0.00

89.40

10.50

0.00

0.00

0.00

60.50

2.60

26.30

0.00

0.06

0.09

11I

18.40

2.60

78.90

18.40

2.60

0.00

0.00

55.30

10.50

10.50

2.60

0.13

0.12

11J

18.40

0.00

81.50

18.40

0.00

0.00

0.00

78.90

0.00

0.00

2.60

0.11

0.04

12A

7.90

0.00

92.10

7.90

0.00

0.00

0.00

2.60

0.00

13.20

76.30

0.04

0.04

12B

10.80

0.00

89.10

10.80

0.00

0.00

0.00

35.10

5.40

21.60

27.00

0.06

0.26

12C

10.50

0.00

89.50

10.50

0.00

0.00

0.00

0.00

0.00

55.30

34.20

0.06

0.12

12D

5.30

0.00

94.80

5.30

0.00

0.00

0.00

50.00

13.20

10.50

21.10

0.03

0.14

12E

2.70

2.70

94.60

2.70

0.00

2.70

0.00

5.40

24.30

54.10

10.80

0.03

0.12

12F

16.20

0.00

83.70

16.20

0.00

0.00

0.00

43.20

0.00

5.40

35.10

0.10

0.19 0.03

12G

15.80

0.00

84.20

15.80

0.00

0.00

0.00

2.60

0.00

0.00

81.60

0.09

12H

10.50

5.20

84.20

10.50

2.60

2.60

0.00

7.90

0.00

0.00

76.30

0.09

0.04

12I

26.30

2.60

71.00

26.30

0.00

0.00

2.60

18.40

2.60

0.00

50.00

0.20

0.14

12J

5.30

5.30

89.50

5.30

5.30

0.00

0.00

15.80

0.00

71.10

2.60

0.06

0.06

00A

84.20

10.60

5.30

84.20

0.00

5.30

5.30

5.30

0.00

0.00

0.00

0.09

0.03

00B

23.70

73.70

2.60

23.70

0.00

10.50

63.20

0.00

0.00

0.00

2.60

0.18

0.08

00C

100.00

0.00

0.00

100.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

00D

76.30

5.30

18.40

76.30

5.30

0.00

0.00

15.80

0.00

2.60

0.00

0.16

0.04

00E

94.70

5.30

0.00

94.70

5.30

0.00

0.00

0.00

0.00

0.00

0.00

0.03

0.01

00F

97.40

2.60

0.00

97.40

0.00

0.00

2.60

0.00

0.00

0.00

0.00

0.01

0.00

Neutral

(Continued on next page)

Journal of Psychophysiology (2018), 32(1), 1–19

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L. Aguado et al., Responses to Emotional Clips

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(Continued) Clip code

Neut. label

Pos. label

Neg. No Joy/ Pleasure/ Peace/ Fear/ Anger/ Sadness/ Disgust/ Emotional Emotional label emotion Happiness Well-Being Relaxation Anxiety Rage Sorrow Revulsion ambivalence ambiguity

00G

84.20

2.60

13.10

84.20

0.00

2.60

0.00

10.50

0.00

0.00

2.60

0.09

0.03

00H

84.20

15.80

0.00

84.20

2.60

7.90

5.30

0.00

0.00

0.00

0.00

0.09

0.03

00I

89.50

2.60

7.90

89.50

2.60

0.00

0.00

0.00

0.00

0.00

7.90

0.06

0.02

00J

86.80

13.20

0.00

86.80

7.90

5.30

0.00

0.00

0.00

0.00

0.00

0.08

0.02

21A

10.50

89.50

0.00

10.50

5.30

10.50

73.70

0.00

0.00

0.00

0.00

0.06

0.05

21B

10.50

89.40

0.00

10.50

2.60

18.40

68.40

0.00

0.00

0.00

0.00

0.06

0.07

21C

21.10

76.30

2.60

21.10

5.30

2.60

68.40

2.60

0.00

0.00

0.00

0.16

0.07

21D

0.00 100.00

0.00

0.00

5.30

7.90

86.80

0.00

0.00

0.00

0.00

0.00

0.02

21E

5.30

94.70

0.00

5.30

28.90

31.60

34.20

0.00

0.00

0.00

0.00

0.03

0.27

21F

13.20

86.80

0.00

13.20

28.90

36.80

21.10

0.00

0.00

0.00

0.00

0.08

0.25

21G

26.30

68.50

5.30

26.30

5.30

7.90

55.30

5.30

0.00

0.00

0.00

0.23

0.12

21H

10.50

89.60

0.00

10.50

63.20

21.10

5.30

0.00

0.00

0.00

0.00

0.06

0.08

21I

18.40

78.90

2.60

18.40

10.50

28.90

39.50

2.60

0.00

0.00

0.00

0.13

0.22

21J

31.60

68.40

0.00

31.60

36.80

21.10

10.50

0.00

0.00

0.00

0.00

0.23

0.25

22A

7.90

89.40

2.60

7.90

78.90

7.90

2.60

0.00

0.00

0.00

2.60

0.06

0.04

22B

2.60

94.70

2.60

2.60

78.90

13.20

2.60

0.00

0.00

0.00

2.60

0.03

0.04

22C

26.30

68.40

5.20

26.30

44.70

13.20

10.50

2.60

0.00

2.60

0.00

0.23

0.18

22D

21.10

68.40

10.50

21.10

50.00

10.50

7.90

7.90

0.00

0.00

2.60

0.23

0.14

22E

2.60

97.40

0.00

2.60

86.80

5.30

5.30

0.00

0.00

0.00

0.00

0.01

0.02

23A

13.20

86.80

0.00

13.20

57.90

26.30

2.60

0.00

0.00

0.00

0.00

0.08

0.10

23B

18.40

79.00

2.60

18.40

71.10

7.90

0.00

0.00

0.00

0.00

2.60

0.13

0.06

23C

13.20

86.90

0.00

13.20

26.30

55.30

5.30

0.00

0.00

0.00

0.00

0.08

0.12

23D

2.60

97.40

0.00

2.60

15.80

76.30

5.30

0.00

0.00

0.00

0.00

0.01

0.04

23E

26.30

73.70

0.00

26.30

39.50

34.20

0.00

0.00

0.00

0.00

0.00

0.18

0.22

Positive

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Journal of Psychophysiology (2018), 32(1), 1–19

Article

An ERP Investigation of Object-Scene Incongruity The Early Meeting of Knowledge and Perception Fabrice Guillaume,1 Sophie Tinard,1 Sophia Baier,2 and Stéphane Dufau1 1

Laboratoire de Psychologie Cognitive (CNRS UMR 7290), Aix-Marseille Université, Marseille, France

2

Laboratoire d’Anthropologie et de Psychologie Cognitive et Sociale (EA 7278), Université de Nice Sophia Antipolis, Nice, France

Abstract: The present study investigated the temporal dynamics of the object-scene congruity during a categorization task of objects embedded in a scene. Participants (n = 28) categorized objects in scenes as natural or man-made while event-related brain potentials (ERPs) were recorded. The object-scene associations were either congruous (e.g., a tent in a field) or incongruous (e.g., a fridge in a desert). The results confirmed that contextual congruity affects item processing in the 300–500 ms time window with larger N300/N400 complex in the incongruous than in the congruous condition. However, unlike previous work which found an effect of congruity starting at 250 ms poststimulus on fronto-central regions, the earliest sign of a reliable context congruity effect arose at 170 ms at left centro-parietal regions in the present study. The present results are in line with those of previous studies showing that object and context are processed in parallel with continuous interactions from 150 to 500 ms, possibly through feed-forward co-activation of populations of neurons selective to the processing of the object and its context. The present finding provides novel evidence suggesting that online context violations might affect earlier visual processes and routines of matching between possible scene-congruent activated schemas and the upcoming information about the item to process.

Keywords: context, event-related potentials, incongruity, object categorization, N170

As we perceive the environment, the flow of incoming visual information interacts with our previous knowledge about the world. As objects in our environment tend to co-occur in specific but recurring contexts, knowledgebased memory processes generate contextually expected entities. Imagine entering a train station. The interplay of incoming information and contextual information helps us to recognize a large rectangular moving object as a train.

Now imagine that instead of a train, we recognize an elephant. This semantic incongruity (also referred to as a semantic inconsistency) is generated by the violation of norms and expectations built up over our lifetime (knowledge). In the early 1980s, Biederman, Mezzanotte, and Rabinowitz (1982) showed that the violations of the physical relations between objects and background scene were accessed from the results of a single fixation and were available sufficiently early during the time course of the scene perception to affect the perception of the objects in the scene. More recently, the neural correlates of this incongruity effect have been investigated (e.g., Van Kesteren et al., 2013). Medial temporal lobe (MTL) and medial prefrontal cortex (mPFC) have been identified as key brain regions in processing the congruency of incoming information with existing knowledge in neocortex Journal of Psychophysiology (2018), 32(1), 20–29 DOI: 10.1027/0269-8803/a000181

(see Van Kesteren, Ruiter, Fernández, & Henson, 2012, for a review). For example, Van Kesteren et al. (2013) showed that the congruency of new information with prior knowledge enhances memory for that information by facilitating retrieval via a preexisting schema through the interaction between MTL, mPFC, and other neocortical regions.

The earliest sign of reliable scene congruity effects on event-related potentials (ERPs) has been found to occur around 300 ms, a timing reminiscent of the N400 sentence congruity effect typically observed in sentence context paradigms (Ganis & Kutas, 2003; Mudrik, Lamy, & Deouell, 2010; Vo & Wolfe, 2013). The congruity effect has been replicated many times on the N300–N400 complex. Ganis and Kutas (2003) presented real-life visual scenes (e.g., players in a soccer field) with a pre-cue replaced 300 ms later by either a congruous object (e.g., a soccer ball) or an incongruous one (e.g., a toilet paper roll) with the context. They found an N390 congruity effect, with more negative amplitude for incongruous than congruous objects. Because of its similarity to the N400 component, the authors proposed that the N390 congruity effect reflects influences of conceptual information on semantic object processing. However, because the scene was presented before the target object, participants were Ó 2016 Hogrefe Publishing

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able to form expectations about the object. The N390 effect could thus be interpreted as reflecting a mismatch between expectations and the actual object rather than online interaction due to object-scene congruency. Later, Mudrik et al. (2010) used images depicting a person performing an action that involved a congruous or an incongruous object (e.g., a woman putting either food or a chessboard in an oven, respectively). In order to avoid effects of prior expectations, they presented an object simultaneously with a background scene rather than following it. Pictures of a person performing an action that involved a congruous or an incongruous object (e.g., a woman putting either food or a chessboard in an oven, respectively) were presented while participants had to report how many hands the person used to perform the action. The authors found an ERP congruity effect starting around 270 ms in left frontal regions, spreading to the centro-frontal regions before 400 ms. Despite variable topographic distributions, they replicated the ERP congruity effect observed in the 300–500 ms time window by Ganis and Kutas (2003).

These negative deflections for semantic inconsistencies have been replicated recently in the N300–N400 effect while subjects had to compare two successive visual scenes (Vo & Wolfe, 2013). The incongruity N300– N400 effect has been found also on spatially incongruent objects in the 275–500 ms window, with early ERP effects (150–225 ms) when the object appeared 300 ms after the scene at a cue location (Demiral, Malcolm, & Henderson, 2012). This result indicates that spatial information is an early and essential part in scene-object integration.

Previous studies were not planned to test congruity effects on early processes, and their design suffered from various biases such as the fact that incongruous scenes were created by digitally pasting a new object into a scene whereas congruous images were not. It has been suggested that contextual violations affect early processing only when the incongruent object and the scene are presented asynchronously, creating expectation. However, comparing ERP evoked by scenes that depicted a person performing an action using either a congruent or an incongruent object, a fronto-central negativity starting 210 ms poststimulus presentation has been observed recently (Mudrik, Shalgi, Lamy, & Deouell, 2014). The question of whether knowledge about the world per se, without expectations induced by a prior context, likewise affects the early processing steps of the object identification remains open. For example, the larger N170 observed when experts were presented with members of their categories of expertise, such as birds and dogs (Tanaka & Curran, 2001) or fingerprints (Busey & Vanderkolk, 2005), suggests that knowledge and learning may influence the early stages of visual processing.

Following this view, when it comes to semantic incongruity, Ó 2016 Hogrefe Publishing

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norm violation, and expectations built up over our lifetimes (knowledge), we are all experts. A growing body of evidence has shown that higher-level cognitive factors can influence early stages of visual processing (see Rauss, Schwartz, & Pourtois, 2011, for a review). For example, there is evidence that information flow through the visual hierarchy is far more rapid than previously believed (Foxe & Simpson, 2002). For example, knowledge-dependent ERP modulations of visual processing starting at about 100 ms when a prior context has been established have been demonstrated (e.g., Dambacher, Rolfs, Göllner, Kliegl, & Jacobs, 2009). Using a forced-choice saccade-based categorization task, it has been shown that context can interfere with object processing at around 160 ms (Crouzet, Joubert, Thorpe, & Fabre-Thorpe, 2009). This early occurrence of object-scene interactions appears to be consistent with contextual influences on object categorization in a parallel network (Joubert, Rousselet, Fize, & Fabre-Thorpe, 2007). To explain such fast interference, a model proposed by the group of Bar (2004) suggests that rapid, coarse processing of a scene activates the most likely possible object(s) in a given contextual frame. This proposal suggests that object representation built from early coarse magnocellular information might be sufficient to allow some forms of object categorization, such as detecting an animal, a person, or a face in an image. Such global image signatures could be used early to determine the general meaning, or “gist,” of the visual scene. Object and context processing can then interact very early in an ascending wave of visual information processing (see Fabre-Thorpe, 2011 or Oliva & Torralba, 2007 for reviews).

The aim of the present study was to examine the temporal dynamics of the object-scene congruity during a categorization task of objects embedded in a scene.

Ensuring that images used in the congruous and incongruous conditions were matched on low-level visual features, we focus on the early interactions between visual processing and previous knowledge about the world.

We chose to use an object categorization task to ensure the direct conceptual processing of the item. We focused on the sequence of ERP components associated with structural encoding (N170), matching with stored long-term memory representations and semantic access (N300– N400). We expected to replicate the congruity effects previously described in the 300–500 ms time window on fronto-central regions (Ganis & Kutas, 2003; Mudrik et al., 2010). Furthermore, in line with results suggesting that context may interfere with object processing in the same time range as the N170 (e.g., Crouzet et al., 2009), we expected to find an early congruity effect at the level of the structural encoding stage reflected by an N170 on posterior regions. Alternatively, if the early processing stages (prior to object identification) are impervious to Journal of Psychophysiology (2018), 32(1), 20–29

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knowledge, then congruity should only modulate semantic access as indexed by the N300–N400 complex.

Method Participants Twenty-eight healthy volunteers (14 women, mean age = 22.5 years, SD = 2.8, ranging from 18 to 33 years) recruited at Aix-Marseille University participated in the study and were paid (10$) for their participation. All participants were right-handed according to the Edinburgh Handedness Inventory (Oldfield, 1971), native speakers of French, and reported normal or corrected-to-normal visual acuity and no history of psychiatric or neurological disorders. All participants gave written informed consent for their participation and the experiment was approved by the Ethics Committee of the department of psychology at the Aix-Marseille University.

Materials The stimuli consisted of 320 colored pictures (800 600 pixels) of an object appearing in a scene (i.e., an objectscene association). The object-scene associations could be either semantically congruous (e.g., a tent in a field) or incongruous (e.g., a shower cabin in the middle of a field; see Figure 1). Prior to the main experiment, 500 stimuli were presented to 20 native French speakers, who were asked to rate the congruity of object-scene associations on a 7-point Likert-like scale ranging from “congruous” to “incongruous” and to name the objects. The stimuli were selected for use in this experiment if all participants scored them in the first or last two points of the scale (7–6 for congruous associations and 1–2 for incongruous associations). Objects and scenes could either be natural (e.g., natural objects: animals, plants, fruits, etc.; natural scenes: mountain landscapes, forests, beaches, etc.) or man-made (e.g., objects: furniture, tools, instruments, etc.; scenes: streets, building interiors, rooms, etc.). Half each of both objects and scenes were natural and man-made in a 50:50 division. All possible combinations of types of objects and scenes (see Figure 1) were used, and counterbalanced between the two conditions. Two lists were created, each consisting of 160 object-scene associations (80 congruous and 80 incongruous) presented in a random order. Each object and each scene was used only once per list (i.e., an object could not appear in more than one scene, and a scene could not be paired with more than one object in the same list). The objects presented in the congruous condition in one list were presented in the incongruous condition in the other list. The presentation of the two lists Journal of Psychophysiology (2018), 32(1), 20–29

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of 160 object-scene associations was counterbalanced across participants. Half of participants performed the task with the first list and the other half with the second list.

Across all subjects, then, each object and each background scene appeared the same number of times in each condition.

We used exactly the same procedure to create both types of stimuli (i.e., congruous and incongruous). First, highquality copyright-free real-life pictures of objects and scenes were collected from Internet sources. The stimuli were then constructed by digitally inserting a single object into each of the scenes using Adobe Photoshop CSr. Care was given to ensure that the object fit into the scene in terms of size, luminance, and orientation. The average luminance and contrast of the scenes in the congruous and incongruous sets was matched, as were the average size and luminance of the target objects. Low-level differences in saliency, chromaticity, and spatial frequency of the pictures in the congruous and incongruous conditions in each list were tested using perceptual model (Neumann & Gegenfurtner, 2006) with no significant difference between the two conditions in either List 1 or List 2. It was nevertheless possible to detect that the objects had been pasted into the scenes. Although there were other objects in the background, the critical object was the only one presented clearly in the foreground. Additionally, the position of the target object was pre-cued by a fixation cross indicating where the target object appeared on the screen. We divided the screen into six sections of identical size and shape, three in the upper half and three in the bottom half of the screen.

Because the position of a visual stimulus in the visual field can influence early electrophysiological components like C1, P1, and N1 (e.g., Clark, Fan, & Hillyard, 1995), we also ensured that the same numbers of objects appeared in the top and bottom parts of the screen in both conditions.

The distribution of target object locations was roughly uniform across the six screen positions. Stimulus presentation and response recording were controlled by the E-prime 2.0 softwarer (Science Plus, Groningen, The Netherlands).

Procedure After completing informed consent, participants were seated in a comfortable chair in a sound-attenuated and darkened room at a distance of 110 cm from the monitor.

Stimuli were displayed on a 1500 CRT monitor (Dell Inc., Round Rock, TX, USA) with a 60-Hz refresh rate and occupied a visual angle of 6° 5°. They were instructed to refrain from blinking and moving their eyes or bodies during the stimulus presentation. The experiment consisted of 160 trials, and began with a short practice block wherein participants received the task instructions and were acquainted with the procedures. Each trial started with a Ó 2016 Hogrefe Publishing

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Figure 1. Examples of congruous and incongruous object-context associations illustrating the two types of backgrounds (natural/ man-made) and items (natural/ man-made). At the bottom is a schematic diagram of the stimulus sequence used. Time goes from left to right.

fixation cross displayed for 500 ms indicating where the target object would appear. Participants were instructed to direct their gaze to the cued location. The fixation cross then disappeared and the picture was presented for 2,500 ms, with the target object at the pre-cued location.

The stimulus then disappeared. The participants then had to categorize the object as either natural or man-made regardless of the congruity of the object-scene association by pressing either the left or the right button on a response pad. The response delay was used to avoid contamination of the ERP segments by motor-response related artifacts.

The interstimulus interval (ISI) was 2,000 ms. The bottom of Figure 1 resumes the experimental design.

ERP Recordings Electroencephalographic activity (EEG) was recorded continuously through the BioSemi ActiveTwo system (BioSemi Products, Amsterdam, The Netherlands) from 64 active Ag-AgCl electrodes embedded in an elastic cap Ó 2016 Hogrefe Publishing

that was positioned according to the extended International 10–20 system. Two additional electrodes (CMS/DRL, near Pz) were used as an online reference. Four external electrodes were used to monitor horizontal and vertical eye movements and blinks (two placed at the lateral canthi and two below the eyes) and two external electrodes recorded from left and right mastoids. ERP analyses were conducted using BrainVision Analyzer 2.0 (Brain Products GmbH, Gilching, Germany).

The continuous EEG data were digitized at 512 Hz and filtered offline using a phase shift-free Butterworth filter (0.01 Hz high-pass, 30 Hz low-pass, 12 dB/octave) with an additional notch filter at 50 Hz to suppress line activity.

All electrode sites were re-referenced offline to the average of the mastoid signals. Epochs of 1,000 ms, starting 200 ms before stimulus onset, were segmented offline from the continuous record and averaged separately for each channel and condition. Waveforms were corrected relative to the 200-ms pre-stimulus baseline period. Only trials with correct responses were included in the averages.

Offline averaging was done after artifact rejection.

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The following criteria and parameters were first used for artifact rejection: the absolute difference between two adjacent sample points of data could not exceed 75 μV/ ms, 150 μV was the maximum allowed difference between values in 200-ms intervals, and ± 75 μV was the maximum value. After this automatic artifact rejection, visual inspection was done on the remaining trials in order to eliminate the residual artifacts. To maintain an acceptable signal-to-noise ratio, a lower limit of 40 artifact-free trials per condition per participant was set (congruous condition mean = 61.9, SD = 8; incongruous condition mean = 62.7, SD = 8.1). Two participants were excluded from further analysis on this basis.

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an early P1, followed by an N170, P2, N2, and P3 at posterior locations and an N300–N400 complex at frontal sites. As an effect on early ERP components it might be suspected to reflect low-level differences between the stimuli in the different conditions (e.g., Johnson & Olshausen, 2003), we addressed this potential concern by assessing the congruity effect on the occipito-temporal P1 in the 100–150 ms time window. There was no significant condition effect on the amplitude of the P1 component (all p > .05). As shown in Figure 2, the first visible difference arose at 170 ms.

N170 Time Window (150–200 ms) Data Analyses Correct responses and corresponding reaction times (RTs) were evaluated using a t test for repeated measures with condition (congruous/incongruous) as the within-subject factor. Mean ERP peaks were computed for all participants in the time windows corresponding to the N170 (150– 200 ms; mean peak at Pz = 177.8 ms, SD = 24.5 ms) and the N300–N400 complex (300–500 ms; mean peak at Fz = 442.5 ms, SD = 27.4 ms), in keeping with the findings of previous research on visual object recognition and congruity effects. The data were analyzed separately for midline and lateral sites using repeated-measures ANOVAs (α = .05). For the midline sites, the model included condition (congruous/incongruous) and sites (Fz, Cz, Pz) as within-subjects variables. For the lateral sites, the model included condition (congruous/incongruous), region (frontal: AF3/AF4; F3/4; F5/6, central: C3/4; C5/6, parietooccipital: P3/4; P5/6; PO3/PO4), and laterality (left/ right) as within-subjects factors (see Figure 2). For factors with more than two levels, the Greenhouse-Geisser epsilon correction was used to adjust the degrees of freedom.

ANOVA results are reported in terms of uncorrected df values, F-values, epsilon-corrected p-values, and the corresponding epsilon values. Partial eta squared (η2p) was used to determine effect sizes.

Results Participants performed at maximum accuracy in the manmade/natural categorization task, with no significant difference between incongruous (M = .99, SD = .01) and congruous (M = 0.98, SD = .02) conditions, t(25) = 0.17, p = .43.

However, RTs were shorter for congruous (M = 756.34, SD = 281.45) compared to incongruous scenes (M = 804.30, SD = 276.55), t(25) = 3.57, p < .001. Figure 2 displays ERPs in each experimental condition at the selected electrodes. Grand-average waveforms indicated Journal of Psychophysiology (2018), 32(1), 20–29

The ANOVA on midline sites in the N170 time window yielded a Condition Site interaction, F(2, 50) = 10.66, p = .002, ɛ = .71, η2p = .36, showing an N170 congruity effect at central midline (Cz), F(1, 25) = 5.36, p = .03, η2p = .22, and parietal midline (Pz), F(1, 25) = 4.95, p = .035, η2p = .24, but not at frontal midline site (Fz). Separate analysis of ROIs revealed a Condition Laterality interaction on central, F(2, 50) = 4.87, p = .032, ɛ = .81, η2p = .21, and parietooccipital, F(2, 50) = 6.92, p = .012, ɛ = .74, η2p = .28, regions but not on frontal regions. As shown in Figure 2, higher negative amplitudes in the incongruous condition than in the congruous condition were observed at left central, F(1, 25) = 4.71, p = .04, η2p = .20, left parietooccipital, F(1, 25) = 6.23, p = .02, η2p = .25, regions while no significant effect was observed on the right central and parietooccipital regions (see Figures 3 and 4).

N300–N400 Time Window (300–500 ms) The ANOVA on midline electrodes in the N300–N400 time window yielded a Condition Site interaction, F(2, 50) = 15.25, p < .001, ɛ = .78, η2p = .38, with higher negative amplitude in the incongruous condition than in the congruous condition at midfrontal site, F(1, 25) = 9.74, p = .005, η2p = .28. The ANOVA on ROIs confirmed a Condition Region interaction, F(2, 50) = 12.76, p < .001, ɛ = .80, η2p = .38, with higher negative amplitude in the incongruous condition than in the congruous condition on frontal, F(1, 25) = 8.52, p = .007, η2p = .27, but not on central, F(1, 25) = 1.02, or parietooccipital regions, F(1, 25) = 0.52 (see Figure 2).

Discussion The present study used ERPs to examine the time course of the context violations effect in a man-made/natural categorization task with an item embedded in a scene. Ó 2016 Hogrefe Publishing

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Figure 2. Grand-average waveforms in the congruous and incongruous conditions at frontal, central, and parietooccipital regions. Filled rectangles denote the time windows used for statistical analyses of the amplitude of the N170 (150– 200 ms) and N400 (300–500 ms) components.

We replicated previous findings on the N300–N400 complex with larger fronto-central negativity in the incongruous compared to the congruous condition (Demiral et al., 2012; Ganis & Kutas, 2003; Mudrik et al., 2010, 2014; Vo & Wolfe, 2013). This incongruity effect reflects the spatiotemporal overlap between N300-like negativities associated with perceptual object processing and N400-like negativities related to semantic knowledge processing and conceptual matching between the object and the scene.

It might be thought of as in some way not entirely dissimilar from the semantic N400 whose amplitude has been reported to be inversely correlated to the strength of the semantic relationship between the context and the eliciting stimulus. As the N400 is considered to be related to

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semantic processing, the context violations effect observed in the current study could be interpreted as reflecting additional processing required to resolve the mismatch between the present stimulus and preexisting schema or knowledge. Importantly, the simultaneous presentation of the item and the scene kept participants from developing any expectation of the upcoming visual content that could facilitate the object’s processing in a top-down guided manner. The frontal congruity effect reflects the greater resonance with semantic knowledge in congruous compared to incongruous item-scene association without any expectation (see also Mudrik et al., 2014). A similar frontal N400 (FN400 old-new effect) has been described in the recognition literature, with greater FN400 amplitude

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F. Guillaume et al., Early ERP Incongruity Effects

Figure 3. Distribution maps of the incongruency effect (incongruouscongruous) over time.

Figure 4. Grand-average waveforms in the congruous and incongruous conditions focused on left and midline parietooccipital regions where the effect was significant in the N170 time window.

for new compared to old words (Rugg & Curran, 2007) or new compared to old faces (Guillaume & Etienne, 2015).

Moreover, recent studies suggest some links between knowledge and episodic memory retrieval processes.

For example, some links between the ERP correlate of familiarity (FN400) and the meaning-based processing reflected by the N400 modulations have been shown (e.g., Voss & Federmeier, 2011).

Item-scene incongruity modulated the early N170 (150– 200 ms) in the present study, with greater negativity for incongruous compared to congruous conditions. This early Journal of Psychophysiology (2018), 32(1), 20–29

N170 congruity effect is observed on the left parietal region and constitutes direct ERP evidence in support of previous behavioral studies showing that context can interfere with object processing starting at around 160 ms (e.g., Crouzet et al., 2009). This result is also in line with previous studies showing that the timing of object model selection onset may be reported as early as 175–192 ms poststimulus (e.g., McPherson & Holcomb, 1999) or revealing early fast access to semantic representations (e.g., items’ semantic relatedness) in a picture-word interference paradigm, with an onset around 180–200 ms poststimulus (Dell’Acqua, Job, Ó 2016 Hogrefe Publishing

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Peressotti, & Pascali, 2007; Dell’Acqua et al., 2010).

Furthermore, the fact that context violations did not modulate the early P1 component suggests that the effect observed here on the N170 is not due to low-level visual differences between conditions. The N170 congruity effect observed in the present study is in contradiction with models such as the functional isolation model which deny any influence of contextual information on early perceptual processing prior to semantic knowledge activation (e.g., Hollingworth & Henderson, 1998). Present results are, however, compatible with contextual facilitation models which propose that stored knowledge about a scene type influences the early perceptual analysis of objects within the scene (Biederman et al., 1982; Boyce, Pollatsek, & Rayner, 1989). By showing that previous knowledge about the world affects the early stages of item recognition, the N170 congruity effect is also consistent with the subordinate-level expertise account of this early ERP component (Rossion, Curran, & Gauthier, 2002). Bar and colleagues (2006) argued that this early N170 congruity effect might be accounted for at the neuronal level by an early cortical process for triggering top-down facilitation in visual object recognition. According to this framework, low frequencies are extracted quickly and projected from early visual areas to orbitofrontal cortex, possibly via the dorsal magnocellular pathway. The N170 congruity effect observed here is thus consistent with the proposal of rapid preprocessing of magnocellular inputs within the ventral pathway which is able to guide the detailed visual processing of parvocellular information, and the idea that magnocellular information is sufficient to allow some form of object categorization (Fabre-Thorpe, 2011). This blurred representation is sufficient to activate predictions about the identity of the object, which are then integrated downstream into the visual cortex along with the bottom-up stream of analysis to facilitate recognition. In this view, memory effect has already been observed on the N170 also during short-term recognition (e.g., Guillaume & Tiberghien, 2001, 2005).

From an ecological perspective, the early detection of incongruous events could be crucial in order to quickly prepare an appropriate behavioral response to an unexpected and potentially dangerous situation. In addition, prediction errors are a prime source for learning as they signal the need for learning in order to update predictions (e.g., den Ouden, Friston, Daw, McIntosh, & Stephan, 2009). One proposal is that the N170 congruity effect reflects the mismatch between the visual input and the prediction activated through this early mechanism of top-down facilitation. In this view, the congruity effect observed on the N170 could be due to differences in image statistics between scenes containing consistent objects and scenes containing inconsistent objects (Joubert et al., 2007; Ó 2016 Hogrefe Publishing

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Mack & Palmeri, 2010). However, the fact that each item appeared in both congruous and incongruous conditions and on different scene (natural/man-made) minimizes the difference in global scene statistics in the present study.

Different reasons could explain the lack of N170 congruity effect in previous studies. The main reason is probably that previous studies were not designed specifically to explore the early correlates of incongruity. In the study of Mudrik et al. (2010, 2014), the pictures always depicted a person performing an action that involved an object, and the participants were asked to decide how many hands were used by the person in the picture to perform the action.

The hand categorization task likely meant that the objectscene incongruity was difficult to assess directly. The fact that the decision was not directed on the incongruity of the scene but on the number of hands used by the person may account for the delayed ERP effect observed in previous studies (e.g., 210 ms) compared to the current experiment. The use of a semantic categorization task (nature/man-made) in the present study could have led to a “tuning” of the cognitive system toward conceptual processing, rendering it more prone to detecting incongruity, whereas Mudrik et al.’s task may have made it more prone to activate motor processing related to the hand categorization (e.g., motor simulation). In the Vo & Wolfe’s study (2013), semantic and syntactic violations were manipulated and the incongruity was related to the relation between two objects. One possibility is that the between items incongruity was slower and more difficult to access than item-scene incongruity because between items incongruity is visually less salient than item-scene incongruity.

Moreover, participants made a visual matching judgment between two successive scenes and mainly focus on the perceptual details of the picture whereas semantic and syntactic information were processed later. Another possibility is that the congruity effect observed in the present study is inflated by the use of animals as stimuli. Indeed, it has been shown that contextual information biased animal responses as early as 160 ms after the stimulus, which was not the case for man-made objects such as vehicle (Crouzet, Joubert, Thorpe, & Fabre-Thorpe, 2012). But here again, the fact that each item appeared in both congruous and incongruous conditions eliminates this possibility.

It remains that further investigations are required to confirm that incongruity modulates neurophysiological processes as earlier as 170 ms and specify the underlying mechanisms of the early processing of contextual violation.

Taken together, the present findings are in line with previous work showing that neuronal responses are shaped by experience (see Sigala & Logothetis, 2002, for a review). For example, an inhibition of object-selective neurons which respond to shower cabins when viewing a field of flowers, while neurons which respond to tents are Journal of Psychophysiology (2018), 32(1), 20–29

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facilitated in the presence of the same scene. The present study thus confirms that context violations yielded an N300–N400 complex related to semantic activation by recognized items and response conflict. At the same time, present results provide novel evidence suggesting that online context violations might affect earlier routines of matching between possible scene-congruent activated schemas and the upcoming information about the actual item. The early (N170) as well as the later (N300–N400) ERPs are modulated by the shaping of object-selective populations of neurons through the daily experience that human beings have with their visual world. Present findings thus confirm that object and context are processed in parallel with continuous interactions from 150 to 500 ms, possibly through feed-forward co-activation of populations of neurons selective to the processing of the object and its context. Resulting interference (or facilitation) between these neuronal populations depends on whether they are usually co-activated or not.

Acknowledgments This work was supported by a grant awarded to Fabrice Guillaume by the Centre National pour la Recherche Scientifique (CNRS) interdisciplinary program “Longévité et vieillissement” (No. AO2008-1) and a special delegation fund from the CNRS. Ethics and Disclosure Statements All participants of the study provided written informed consent and the study was approved by the Ethics Committee of CPP Sud-Méditerranée II. All authors disclose no actual or potential conflicts of interest including any financial, personal, or other relationships with other people or organizations that could inappropriately influence (bias) their work.

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Van Kesteren, M. T. R., Beul, S. F., Takashima, A., Henson, R. N., Ruiter, D. J., & Fernández, G. (2013). Differential roles for medial prefrontal and medial temporal cortices in schema-dependent encoding: From congruent to incongruent.

Neuropsychologia, 51, 2352–2359. doi: 10.1016/ j.neuropsychologia.2013.05.027 Van Kesteren, M. T. R., Ruiter, D. J., Fernández, G., & Henson, R. N. (2012). How schema and novelty augment memory formation.

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02.001 Võ, M. L.-H., & Wolfe, J. M. (2013). The interplay of episodic and semantic memory in guiding repeated search in scenes.

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09.017 Voss, J. L., & Federmeier, K. D. (2011). FN400 potentials are functionally identical to N400 potentials and reflect semantic processing during recognition testing. Psychophysiology, 48, 532–546. doi: 10.1111/j.1469-8986.2010.01085.x Received November 17, 2015 Accepted June 4, 2016 Published online November 22, 2016 Fabrice Guillaume Laboratoire de Psychologie Cognitive (CNRS, UMR 7290) Université d’Aix-Marseille Fédération de Recherche 3C, Bâtiment 9 Case D 3 place Victor Hugo 13331 Marseille Cedex 3 France Fabrice.Guillaume@univ-amu.fr

Journal of Psychophysiology (2018), 32(1), 20–29

Article

Burnout of the Mind – Burnout of the Body?

Claudia Traunmüller,1 Kerstin Gaisbachgrabner,1 Helmut Karl Lackner,2 and Andreas R. Schwerdtfeger1 1

Department of Psychology, Health Psychology Unit, University of Graz, Austria

2

Institute of Physiology, Medical University of Graz, Austria

Abstract: In the present paper we investigate whether patients with a clinical diagnosis of burnout show physiological signs of burden across multiple physiological systems referred to as allostatic load (AL). Measures of the sympathetic-adrenergic-medullary (SAM) axis and the hypothalamic-pituitary-adrenal (HPA) axis were assessed. We examined patients who had been diagnosed with burnout by their physicians (n = 32) and were also identified as burnout patients based on their score in the Maslach Burnout Inventory-General Survey (MBI-GS) and compared them with a nonclinical control group (n = 19) with regard to indicators of allostatic load (i.e., ambulatory ECG, nocturnal urinary catecholamines, salivary morning cortisol secretion, blood pressure, and waist-to-hip ratio [WHR]). Contrary to expectations, a higher AL index suggesting elevated load in several of the parameters of the HPA and SAM axes was found in the control group but not in the burnout group.

The control group showed higher norepinephrine values, higher blood pressure, higher WHR, higher sympathovagal balance, and lower percentage of cortisol increase within the first hour after awakening as compared to the patient group. Burnout was not associated with AL. Results seem to indicate a discrepancy between self-reported burnout symptoms and psychobiological load.

Keywords: allostatic load, autonomic nervous system, burnout, heart rate variability, HPA axis

Burnout is a well-established academic subject (Schaufeli, Leiter, & Maslach, 2009) which has been widely reported in countless books, articles, congress papers, and workshops (Halbesleben & Buckley, 2004; Maslach, Schaufeli, & Leiter, 2001). According to Maslach et al. (2001), burnout is a stress state characterized by symptoms of mental exhaustion and physical fatigue, detachment from work, and loss of energy. It is viewed as an affective reaction to prolonged exposure to stress at work, that is, to situations in which job demands exceed individuals’ adaptive resources (Schaufeli et al., 2009). Surveys by insurance funds showed that the current damage to the economy must be regarded as huge. Moreover, it is estimated that the economic burden of burnout costs the American government more than $300 billion dollars annually in terms of lost productivity and health costs (Rosch, 2001). Currently, there exist no standardized procedures to identify individuals who suffer from burnout.

The diagnosis “burnout” is based on self-reports and how individuals communicate their symptoms. Hence, research into the physiological underpinnings of this phenomenon seems warranted.

Several burnout measures were developed in the early 1980s. The most widely used and well-validated self-report questionnaire of burnout is the Maslach Burnout Inventory Journal of Psychophysiology (2018), 32(1), 30–42 DOI: 10.1027/0269-8803/a000182

(MBI; Schaufeli, Leitner, Maslach, & Jackson, 1996).

The MBI addresses three general scales: emotional exhaustion which measures feelings of being emotionally overextended and exhausted by one’s work; depersonalization measures an unfeeling and impersonal response toward recipients of one’s service, care treatment, or instruction; and personal accomplishment measures feelings of competence and successful achievement in one’s work (Maslach, Leiter, & Schaufeli, 2008).

Although burnout it is not regarded as a “classical” stress disorder, it is often preceded by periods of acute or prolonged stress (Henry, 1992; McEwen, 1998) and is discussed to be associated with adverse health effects via constant stimulation of stress systems in the body (Danhof-Pont, van Veen, & Zitman, 2011). The cost of chronic exposure to repeated or chronic stress is defined as allostatic load (AL; McEwen, 1993). The original idea of AL assumed that variables quantifying AL can be separated into mediators (such as cortisol, epinephrine, and norepinephrine) causing primary effects, which in turn lead to secondary outcomes (e.g., waist-to-hip ratio, systolic and diastolic blood pressure) that result in tertiary outcomes representing actual disease (McEwen, 1998). Using indicators for the biological dysregulations of physiological systems, the AL index provides a reasonable approach to Ó 2016 Hogrefe Publishing

C. Traunmüller et al., Burnout and Physiological Dysregulation

the assessment of the cumulative load of burnout (Mauss, Li, Schmidt, Angerer, & Jarczok, 2015). It is argued that this composite measure permits a better overview of stressrelated dysregulations than any single factor alone (Karlamangla, Singer, McEwen, Rowe, & Seeman, 2002).

Studies considerably differ with respect to the number and types of physiological variables entering the AL score.

For example, Seeman, McEwen, Rowe, and Singer (2001) selected systolic blood pressure (SBP), diastolic blood pressure (DBP), waist-to-hip ratio (WHR), high-density lipoprotein (HDL), cholesterol, total/HDL cholesterol ratio, glycosylated hemoglobin, urinary cortisol, urinary norepinephrine and epinephrine, and serum dehydroepiandrosterone sulfate (DHEA-S) as primary and secondary mediators of AL. Trying to explain the socioeconomic status differences in mortality, Seeman et al. (2004) added six additional immunological parameters, like interleukin-6 and C-reactive protein. Schulkin (2004) defined glucocorticoids, dehydroepiandrosterone (DHEA-S), catecholamines, and cytokines as the four most common allostasis mediators. Currently, there is no agreement as to which variables should be primarily included in the AL index (Sjörs, Jansson, Eriksson, & Jonsdottir, 2012).

Several studies related burnout and connected concepts with AL. In a study of Schnorpfeil et al. (2003) job demands were found to be significantly related to AL. Juster et al.

(2011) examined the relationship between burnout symptoms and hypocortisolemic profiles. The results demonstrated increased AL in conjunction with increased burnout symptoms. Bellingrath, Weigl, and Kudielka (2009) confirmed significant correlations between chronic stress and higher AL in female teachers. These findings are consistent with the idea that burnout, representing a cumulative measure of the effects of chronic stress on the individual’s well-being, may be linked to AL. Other studies aimed to examine the psychophysiology of burnout without explicit reference to AL (for an overview, e.g., Mommersteeg, 2006). Two physiological systems are commonly distinguished in the literature as concomitants of chronic stress and negative affective well-being: the sympathetic-adrenergic-medullary (SAM) axis and the hypothalamic-pituitary-adrenal (HPA) axis (Frankenhaeuser, 1991).

Prolonged or repeated exposure to stress can lead to sustained activation of the HPA and SAM axes. As a result both stress axes could stay persistently activated, recovery does not occur, and the systems might not return to homeostasis (De Vente, Olff, Van Amsterdam, Kamphuis, Emmelkamp, 2003, Dienstbier, 1989; Peters et al., 1998).

Beside extensively studied signs of dysregulation of the SAM axis like elevated blood pressure (BP; Fredrikson, Tuomisto, Lundberg, & Melin, 1990; Kawakami, Haratani, & Araki, 1998; Steptoe, Cropley, Griffith, & Kirschbaum, 2000; Steptoe, Cropley, & Joekes, 1999), increased heart Ó 2016 Hogrefe Publishing

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rate (HR; Steptoe et al., 1998, 2000), and release of epinephrine and norepinephrine (Kirschbaum & Hellhammer, 1989), analysis of heart rate variability (HRV) has become a popular tool to study the autonomic nervous system (ANS; Zygmunt & Stanczyk, 2010), although it has not yet been integrated in the AL metric.

HRV is generally assessed using time-domain or frequency-domain analyses (Zygmunt & Stanczyk, 2010).

Several studies support the general view that both parasympathetic and sympathetic efferences impact HRV (Lackner, Goswami, Hinghofer-Szalkay, et al., 2010; Lackner, Goswami, Papousek, et al., 2010; Malpas, 2002). The research group of Pagani (Malliani, Pagani, Lombardi, & Cerutti, 1991; Montano et al., 2009) suggested the possibility to evaluate the balance between the two branches of the ANS (i.e., autonomic balance) by separating higher (i.e., respiratory related) and lower frequencies in the HRV power spectrum. Within this model the researchers stated that the high frequency (HF) component can be taken as an index of parasympathetic tone whereas the low frequency (LF) component is more sensitive to sympathetic outflow. Hence, sympathovagal balance could be assessed as the LF/HF ratio. It is generally accepted that heart rate variability (HRV), BP, and hormone levels are used as measures of acute physiological responses to work-related demands or laboratory stressors.

Dysregulations of the HPA axis have frequently been assessed within the AL (Danhof-Pont et al., 2011). Cortisol follows a basal diurnal rhythm which is expressed as part of normal, healthy circadian physiology (Stalder et al., 2016): cortisol level is typically high in the morning upon waking, increases 50–60% in the first 30–45 min after awakening, and rapidly drops over the first few hours after waking and then declines more slowly across the day to reach the low point around midnight (Pruessner et al., 1997; Wüst, Wolf, et al., 2000). Dysregulations could be quantified as either hyper- or hyposecretion of cortisol (Pruessner et al., 1997) and have frequently been associated with burnout (Marchand, Juster, Durand, & Lupien, 2014).

Furthermore, relations were observed between cortisol and workload (Steptoe et al., 1998, 2000). Frankenhaeuser (1989) suggested that burnout patients might show lower basal HPA axis activity resulting, for example, in hyposecretion of cortisol. However, both decreases (Ockenfels et al., 1995; Pruessner, Hellhammer, & Kirschbaum, 1999) and increases (Melamed et al., 1999) of cortisol levels were reported in studies concerning chronic stress.

The objective of the present study was to investigate differences between burnout patients and healthy controls regarding AL and its constituents. We expected a higher AL index within the patient group as compared to the nonclinical group. Additionally, we expected differences in various physiological indicators. Therefore, measures of Journal of Psychophysiology (2018), 32(1), 30–42

32

the SAM axis and the HPA axis were examined separately.

Differences in both axes were expected between burnout patients and nonclinical controls. Specifically, burnout patients should manifest lower morning cortisol levels of salivary cortisol, reduced cortisol awakening response (CAR) and, as a sign of increased sympathetic activity, higher concentration of epinephrine and norepinephrine than non-patients. We also hypothesized that burnout should be related to HRV and expected that participants with high burnout scores should display a higher LF/HF ratio and lower square root of the mean squared differences of successive RR intervals (RMSSD) as compared to the nonclinical group. Contrary to other studies on burnout and AL, which primarily analyzed inflammatory and metabolic variables (Langelaan, Bakker, Schaufeli, van Rhenen, & van Doornen, 2007), this study is among the first to focus on evaluating multiple physiological parameters of the HPA and SAM axes in a thoroughly diagnosed group of burnout patients as compared to nonclinical controls.

C. Traunmüller et al., Burnout and Physiological Dysregulation

Table 1. Demographic variables for patient group and control group Patient group (n = 32)

Age Waist-to-hip ratio Working hours

Control group (n = 19)

M

SD

M

46.00

7.46

49.61

7.27

0.88

0.05

0.97

0.18

11.31

48.67

7.05

40.1*

SD

Absolute frequency Medication

26

0

5

0

21

0

Women

14

4

Men

17

15

Compulsory school

1

–

Gage

16

–

College

6

–

Higher school certificate

6

–

University degree

3

19

SSRI (Selective serotonin reuptake inhibitors) TCA (Tricyclic antidepressants) Sex

Education

Family status

Methods Study Sample and Design This study was based on a between-subject design.

The demographic data are shown in Table 1. We examined 32 burnout patients and 19 nonclinical controls. There were 33 men and 18 women, and 22 were married. The mean age of the control group was 49.6 years (range: 35–60) and the mean age of the patient group was 46.0 years (range: 31–57). A t-test showed that age did not differ significantly between groups (t[49] = 1.77, p = .083, ηp2 = .060).

However, women were marginally significantly underrepresented in the control group (w2 = 2.97, p = .085).

Burnout patients were included in this study if they had a burnout diagnosis by their physicians based on the dual diagnoses (Z73.0) within the International Classification of Diseases (ICD-10) and showed – according to the recommendation of Maslach, Jackson, and Leiter (1996),1 the most characteristic components of burnout such as high values in the subscales emotional exhaustion, depersonalization, and reduced personal accomplishment on MBI (Schaufeli et al., 1996). Moreover, they were under treatment in a rehabilitation center for psychological diseases on a medical prescription and were on sick leave for at least 10 weeks because of the diagnosis burnout before entering the rehabilitation center. Participants of the control group were included by criteria such as good physical health (evaluated by physicians via a sports medical examination), 1

Living alone

5

In a relationship

13

12

Married

14

7

Notes. Differences in sample size: missing data; *working hours of patient group: before sick leave.

still in their working process, able to work for at least 8 hr a day, and had never been on sick leave because of a burnout diagnosis. Exclusion criteria were: having had a traumatic event in the past six months, cardiovascular diseases (e.g., myocardial infarction and stroke), pregnancy, or a current history of psychiatric illness. Participants with missing values > 10% on the MBI as well as on physiological parameters were excluded from the analysis (burnout patients n = 3).

Recruiting Procedure Patient Group Patients were enrolled in a rehabilitation center of psychological illness with a focus on burnout. The first visit to the clinic took place one day after admission to the clinic.

The physicians were asked to allocate burnout patients to the study. In the second step, patients got a short overview of the study by the doctors. Within the first week after admission to the clinic an informal meeting was organized during which participants first received a description of the study with detailed information. Confidentiality,

Emotional exhaustion (< 18 = low, 19–26 = moderate, > 27 = high); Depersonalization (< 5 low, 6–9 = moderate, > 10 = high); Personal accomplishment (< 40 = low, 34–39 = moderate, > 33 = high).

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anonymity, and the opportunity to withdraw from the study without any negative repercussions was assured. Participants read and signed an informed consent form. Together with the participants who met all the inclusion criteria, we built up a precise timetable for collecting the data.

Control Group Healthy participants were enrolled by the hospital staff of an emergency hospital. An informal meeting was organized, where interested persons received a description of the study with detailed information. Further procedure was comparable to that of the patient group. The study was approved by the Institutional Ethics Review Board and was therefore conducted in accordance with the World Medical Association (2013).

Variables and Procedure To enhance reliability of the data, all physiological variables were assessed two times in a week (except for waist-to-hip ratio). To examine reliability of the measurements, intraclass correlation coefficients (ICCs) for absolute agreement were calculated as shown in Table 2. The ICCs ranged between .71 and .98, thus justifying the calculation of an aggregated score for each variable.

Burnout Burnout was assessed by the Maslach Burnout InventoryGeneral Scale (MBI-GS; Schaufeli et al., 1996), which consists of the three dimensions: exhaustion (five items), depersonalization (five items), and personal accomplishment (six items). Items were rated on 7-point Likert scales, indicating the frequency of experiencing each symptom (0/never, 6/daily). Scores for each scale were calculated according to Schaufeli et al. (1996) by summing up responses with higher scores indicating higher emotional exhaustion, depersonalization, and personal efficacy.

In order to remain consonant with the other two subscales and the general tenor of the MBI, the scale personal efficacy was reverse coded to yield a measure of lack of personal accomplishment. In addition to the MBI and because there are no validated cut-off points depending on the test version of the MBI (Bakker, Emmerik, & Euwema, 2006; Schaufeli & van Dierendonck, 2000), all participants of the burnout group got additionally the burnout diagnosis by physicians of the clinic. Cronbach’s α was .95 for emotional exhaustion, .84 for depersonalization, and .84 for lack of personal accomplishment. The psychological tests were handed over to the participants asking them to fill in the forms and return them within one week. Ó 2016 Hogrefe Publishing

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Table 2. Intraclass Correlation Coefficients for the physiological variables Parameter

Patient group

Control group

Overall

HR

.727

.914

.748

lnRMSSD

.759

.961

.774

SDNN

.752

.975

.800

lnLF

.789

.982

.831

lnHF

.895

.967

.907

LF/HF

.811

.904

.853

Adrenaline*

.747

–

–

Noradrenaline*

.705

–

–

Notes. *Only available for the patient group; for control group an aggregated score was calculated directly in the laboratory.

Measurement of Cortisol and Catecholamines Participants got a detailed instruction on how to collect saliva samples and the nocturnal urine. For the saliva samples Salivettes (Sarstedt, Nümbrecht, Germany) were used, which were prepared as follows: each Salivette was labeled with the individual code of the participant, the date and time when they should begin collecting their samples (time of awakening, +15 and +45 min thereafter). The cortisol awakening response (CAR) was calculated as a valid parameter of the neuroendocrine stress axis. The resulting hormone value was interpreted as an index of unstimulated HPA activity (Laudat et al., 1988). Participants were informed about the necessity of strictly following the time schedule for saliva sampling to obtain valuable data.

Participants were asked to start with the saliva sampling immediately upon awakening. They were instructed to complete sampling before breakfast and were asked not to brush their teeth to avoid contamination of saliva with food, drinks, or blood through micro injuries of the gums.

To counteract the problem of sampling inaccuracy within the patient group, participants were woken by nurses who did the nightshift. Specifically, patients received an alarm call in the morning at a planned wake-up time. In the control group, an exact schedule was jointly developed together with the participants. According to the guidelines for assessment of the CAR (Stalder et al., 2016), ECG monitoring was used for verification of awakening time combined with selfreported awakening times. In order to control the compliance especially for the control group, we compared the time which was written on the first salivette with the ECG awakening reaction. On the basis of the documented awakening times we could make sure that the collection of the saliva sample took place nearly at the same time for all participants. In both groups, time of awakening was organized in the way, that there was no disturbance for participants in their daily routines. Collection of the saliva samples took place only on working days. For the control Journal of Psychophysiology (2018), 32(1), 30–42

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group it was ensured that they had no nightshift on the day before samples were taken.

Salivary free cortisol was analyzed by using a commercial chemiluminescence immunoassay (LIA; IBL Hamburg, Germany). To reduce error variance caused by imprecision of the intra-assay, all samples of one participant were analyzed in the same run.

The urine containers for collecting the nocturnal urine sample were labeled in the same way. Twelve-hour urine samples were collected (7:00 p.m. until next day 8:00 a.m.) in bottles containing 10 mL of 25% HCl. It was emphasized that participants should empty their bladders before collecting urine and that it is important to sample also the first morning urine. The following day saliva and urine samples were taken immediately to the laboratory, the amount of urine was recorded and aliquots frozen at 25 °C until biochemical analysis was carried out.

Measurement of the catecholamines, norepinephrine and epinephrine, was performed by High Performance Liquid Chromatography (HPLC) with electrochemical detection, according to the extraction procedure suggested by Chromsystems (Munich, Germany).

ECG Monitoring The day after collecting the cortisol and catecholamine samples, the experimenter met the participants to place the ECG electrodes on them for the 24 hr ECG monitoring.

Both studies were conducted at the same time. Due to the availability of ECG recorders, two different devices were used: an EquivitalTM EQ-01 (EquivitalTM, Hidalgo Cambridge, UK) sensor for the patient group and MedilogrAR12plus recorder (MedilogrAR12plus, Schiller, Switzerland) for participants of the control group. The sampling rate for both devices was 256 Hz. Artifact handling of beat-to-beat HR-values was done semiautomatically with a signal analyzer developed in MATLAB (MATLABr, MathWorks, Natick, MA, USA) which identifies artifacts by the: (1) physiological limits and (2) maximal percentage of change in relationship to standard deviation of the signal, using the time series with equidistant time steps after resampling beat-to-beat values with 4 Hz (Lackner, Goswami, Hinghofer-Szalkay, et al., 2010). Single artifacts were replaced by linear interpolation and their appearance was recorded. To get an average value throughout the day, randomized segments of 15 min per hour were calculated in both groups and aggregated to one day-value for each group. As a result, 4 hr was used for further analysis for day-values. Average values for the night were calculated between 12 p.m. and 4 p.m. Data were subsequently aggregated across day and night in order to get an estimate of circadian cardiac activity. HRV was assessed following the standard criteria of the Task Force of the European Journal of Psychophysiology (2018), 32(1), 30–42

C. Traunmüller et al., Burnout and Physiological Dysregulation

Society of Cardiology and the North American Society of Pacing and Electrophysiology (24). Time-domain (standard deviation of the normal-to-normal interval [SDNN], square root of the mean squared differences of successive RR intervals [RMSSD]) and frequency-domain measures (low frequency [LF] component, 0.04–0.15 Hz, high frequency [HF] component, 0.15–0.40 Hz, and the ratio of LF and HF [LF/HF]) were assessed. Of note, LF has been related to cardiac sympathetic (and presumably parasympathetic) nerve activity; whereas HF is closely related to respiratory rhythm and may be primarily modulated by vagal nerve innervation. LF/HF might thus indicate the relative balance between sympathetic and parasympathetic efference.

Measurement of Blood Pressure and Waist-to-Hip Ratio Resting blood pressure was measured after 5 min of rest in a seated position two times within 10 min by nurses of the clinic. Participants were asked to come to the nurse’s station during the day for the blood pressure measurement.

Participants were invited to sit down and relax for 10 min.

Thereafter, blood pressure was measured with a blood pressure monitor Bluetooth 4.0 (Pearls, Austria), which measures blood pressure on the wrist. In the control group, blood pressure was measured by the investigator with the same device used in the patient group.

Waist-to-hip ratio (WHR) was measured on the first measurement day. According to WHO abdominal obesity is defined as a waist-to-hip ratio above .90 for males and above .85 for females.

Allostatic Load In order to meaningfully integrate the physiological measures, the AL index was additionally calculated as an indicator of cumulative physiological load. Five biomarkers representing the following systems were included into the AL index: neuroendocrine (12 hr overnight urinary epinephrine and norepinephrine), metabolic (WHR), and cardiovascular (systolic and diastolic blood pressure; SBP, DBP). Moreover, cortisol and HRV parameters (SDNN, RMSSD, and LF/HF) were additionally included in an extended version of the AL, which comprised nine biomarkers altogether. Percentiles were calculated whereby values falling within the highest 75th percentile of risk, with respect to the sample’s biomarker distribution, were dichotomized as 1 while those falling below the 75th percentile were scored as 0 (e.g., Seeman, Singer, Rowe, Horwitz, & McEwen, 1997). The exceptions to this approach were cortisol, SDNN, and RMSSD, for which the lowest Ó 2016 Hogrefe Publishing

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Table 3. Overview of the main variables of the study Patient group

Control group

Women

Men

M

SD

M

SD

M

SD

M

SD

Depersonalization*

4.31

0.80

3.04

1.07

4.18

1.00

3.63

1.13

Personal accomplishment*

4.62

0.74

5.16

0.59

4.61

0.87

4.94

0.63

Emotional exhaustion

5.23

0.74

5.36

0.78

5.36

0.82

5.24

0.72

Systolic blood pressure* (mmHg)

122.74

8.91

139.50

10.57

126.83

8.63

130.39

14.24

Diastolic blood pressure* (mmHg)

76.95

6.51

93.88

12.58

80.65

6.87

84.63

14.58

Waist-to-hip ratio*

0.87

0.18

0.97

0.05

0.91

0.07

0.91

0.19

Cortisol t0 (nmol/L)

9.49

3.26

11.10

4.08

11.32

3.78

9.58

3.53

Cortisol t15 (nmol/L)

12.75

4.88

11.87

4.65

12.30

4.91

12.45

4.76

Cortisol t45 (nmol/L)

14.25

5.06

12.75

5.54

15.38

5.23

12.79

5.15

2.57

1.46

2.68

1.48

2.38

0.89

2.75

1.69

Noradrenaline* (μg/L)

18.64

8.91

27.68

8.81

19.50

7.63

23.88

10.71

Heart rate (BPM; averaged over 24 hr)

72.72

11.37

70.47

7.71

72.95

10.27

71.26

10.13

SDNN (ms; averaged over 24 hr)

Adrenaline (μg/L)

53.49

20.76

61.53

14.59

57.65

21.86

55.93

17.38

lnRMSSD (ms; averaged over 24 hr)

3.29

0.60

3.24

0.41

3.29

0.63

3.26

0.48

lnLF (ms2; averaged over 24 hr)

6.08

0.83

6.45

0.57

6.22

0.85

6.22

0.72

lnHF (ms2; averaged over 24 hr)

4.96

1.12

4.85

0.89

5.00

1.19

4.88

0.95

lnLF/HF* (ms2; averaged over 24 hr)

1.14

0.54

1.59

0.56

1.25

0.58

1.35

0.61

Notes. AUCi and AUCg have been conducted but did not show any significant effect. *p < .05.

25th percentile signified highest risk. Importantly, based on the findings of Pruessner et al. (1997) we decided to define a reduced cortisol increase in the morning within the first 30 min after awakening as a risk factor. In sum, the AL index was operationally defined as the total number of dysregulated biomarkers which could theoretically range from 0 to 5 for the “classical” and from 0 to 9 for the “extended” AL index. Higher scores should reflect greater cumulative physiological burden (Bellingrath et al., 2009).

and significance level was set at p < .05, two-sided for all analyses.

Results A complete overview of the descriptive statistics is listed in Table 3.

Self-Rated Burnout Statistical Analyses For testing the hypotheses, analyses of variance (ANOVAs) and analyses for covariance (ANCOVAs) were conducted.

Differences in cortisol response profiles over three measuring times between the two groups (patient/control group) were analyzed using a repeated-measures analysis of variance. Group and sex were included as betweensubject factors throughout. The homogeneity of variance assumption was analyzed with Mauchly’s test of sphericity.

Multivariate tests were used for repeated-measures analyses and Wilk’s Ʌ and effect sizes (partial eta-squared) are reported. Post hoc within-group comparisons were calculated with t-tests. A natural logarithmic transformation was applied to the LF, HF, RMSSD, and sympathovagal balance (LF/HF) data, as their distribution was skewed.

All statistical analysis was performed using the software IBM SPSS Statistics version 21.0 (IBM Corp., NY, USA) Ó 2016 Hogrefe Publishing

To verify if there was a difference between patients and the control group on the three subscales of the MBI a multivariate analysis of variance (MANOVA) was computed. The results showed a significant main effect of group with a comparably large effect size, F(3, 44) = 6.42, p = .001, ηp2 = .305, suggesting higher burnout scores in the patient group. Post hoc analyses were conducted to examine group effects on the three subscales separately. Depersonalization was significantly higher in the patient group (M = 4.31, SD = 0.82) as compared to the control group (M = 3.04, SD = 1.07), F(1, 46) = 10.96, p = .002, ηp2 = .192.

There was also a significant effect for lack of personal accomplishment, indicating that the patient group scored significantly higher (M = 2.39, SD = 0.75) than the control group (M = 1.84, SD = 0.59), F(1, 46) = 4.28, p = .044, ηp2 = .085). No group difference was found for emotional exhaustion, F(1, 46) = 2.22, p = .143, ηp2 = .046.

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Further analysis using the cut-off scores proposed by Maslach et al. (1996) revealed that 56.3% of the patient group showed high, 37.5% moderate, and 6.3% low burnout symptoms compared to the control group with 5.3% reported high, 42.1% moderate, and 52.6% low burnout symptoms. Furthermore, no sex differences could be found in any of the MBI subscales, F(3, 44) = 0.98, p = .413, ηp2 = .062. The interaction between group and sex was also not significant, F(3, 44) = 1.44, p = .244, ηp2 = .089.

Allostatic Load Index Both the “classical” and the “extended” AL indices were strongly interrelated (r = .84, p < .001) and differed significantly between groups. The traditional ALI score was significantly higher in the control group (M = 2.21, SD = 1.72) as compared to the patient group (M = 0.59, SD = 0.95), F(1, 49) = 18.88, p .0001, ηp2 = .278. The extended ALI was also significantly higher in the control group (M = 3.16, SD = 1.89) as compared to the patient group (M = 1.56, SD = 1.41), F(1, 49) = 11.76, p = .001, ηp2 = .194, thus suggesting greater physiological burden in the control group than the patient group. Additional analyses were computed to explore associations between the ALI and the MBI subscales. There were significant correlations between ALI and depersonalization (ALI_classic r = .429, p .002; ALI_extended r = .498, p .0001) and personal accomplishment (ALI_extended r = .36, p .0001). No significant correlations were found between the ALI and emotional exhaustion. Associations were also calculated for each physiological variable separately. Because a total of 19 tests were conducted, we decided on a Bonferroni alpha adjustment to p < .0026 to overcome the problem of alpha inflation. Depersonalization was significantly negatively correlated with SBP (r = .47; p .0001) and DBP (r = .49, p .0001), norepinephrine (r = .41; p .004), LF/HF (r = .49, p < .0001), and RMSSD (r = .33, p .018). For personal accomplishment significant correlations could be found for norepinephrine (r = .37, p .010). Subsequently, each variable entering the ALI scores was analyzed separately in order to get a more detailed understanding of the psychobiological differences between groups.

Waist-to-Hip Ratio (WHR) A significant difference in WHR was found between the two groups as revealed by an ANOVA. The patient group exhibited a marginally significantly lower WHR (M = .88, SD = .18) than the control group (M = .97, SD = .05), Journal of Psychophysiology (2018), 32(1), 30–42

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F(1, 46) = 3.37, p = .073, ηp2 = .068. There were no sex differences, F(1, 46) = 0.06, p = .801, ηp2 = .001, and no significant interaction between group and sex, F(1, 46) = 1.02, p = .319, ηp2 = .022.

Blood Pressure Systolic and diastolic blood pressure was compared between the study groups using a MANOVA. The analysis showed a significant difference between both groups for both variables. Patients showed a significantly lower systolic blood pressure (M = 122.75, SD = 8.91), F(1, 46) = 19.55, p .0001, ηp2 = .298, as well as a significantly lower diastolic blood pressure (M = 76.95, SD = 6.51), F(1, 46) = 24.21, p .0001, ηp2 = .345, as compared to the control group (SBP: M = 139.50, SD = 10.57; DBP: M = 93.88, SD = 12.58). In order to verify if this group effect was influenced by WHR, an analysis of covariance (ANCOVA) was computed, which indicated that although WHR had a significant effect on both, SBP and DPB, group differences remained significant, F(1, 46) = 10.77, p .0001, ηp2 = .329. No sex differences, F(2, 45) = 0.36, p = .702, ηp2 = .016, and no significant interaction between group and sex could be found, F(2, 45) = 3.10, p = .055, ηp2 = .121.

Salivary Cortisol Measurements First, a repeated-measures ANOVA was computed with absolute cortisol values as the dependent variable.

Mauchly’s test indicated that the assumption of sphericity was violated, w2(2) = 10.79, p < .05, therefore multivariate tests are reported (ɛ = .81). The response curves are depicted in Figure 1.

There was a significant main effect of measurement time, F(2, 41) = 5.83, p = .011, ηp2 = .199, and a significant interaction between measurement time and group, F(2, 41) = 6.25, p = .004, ηp2 = .234. From Figure 1 it can be retrieved that there was a general increase in cortisol across time, although groups seemed to differ. Of note, there were no significant differences between groups for t0: t(45) = 1.52, p = .137; t15: t(45) = 0.74, p = .466; and t45: t(45) = 0.86, p = .394. However, within-group analyses revealed that for the patient group cortisol significantly increased from t0 to t15 (t[27] = 4.94, p < .001) and from t0 to t45 (t[27] = 4.40, p < .001), but remained constant between t15 and t45 (t[27] = 1.23, p = .228). Of note, there were no significant changes across time for the control group (t0 to t15: t[18] = 0.84, p = .411; t0 to t45: t[18] = 1.39, p = .180; t15 to t45: t[18] = 0.69, p = .498). In order to verify if medication had an effect on cortisol, an ANCOVA was Ó 2016 Hogrefe Publishing

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a sex difference, F(2, 42) = 0.66, p = .523, ηp2 = .030, nor a significant interaction between group and sex, F(2, 42) = 0.44, p = .646, ηp2 = .021.

Cardiac Activity

Figure 1. Profile of the morning rise in salivary cortisol for the two sample groups. (Whiskers indicate ± 1 SE).

computed, indicating that this effect remained significant, F(2, 43) = 0.213, p = .808, ηp2 = .005). Thus, medication may not have biased findings.

The interaction between measurement time and sex was also significant, F(2, 41) = 4.66, p = .015, ηp2 = .185.

Although there were no significant differences between men and women for each time point (t0: t[44] = 1.53, p = .134; t15: t[44] = 0.10, p = .920; t45: t[44] = 1.59, p = .120), there were differences in the cortisol profile within sexes. Women showed a significant increase in cortisol level between t15 and t45 (t[14] = 2.44, p = .029) and t0 and t45 (t[14] = 2.55, p = .023), but not between t0 and t15 (t[14] = 0.70, p = .498). Of note, men showed a significant increase in cortisol between t0 and t15 (t[30] = 5.45, p .0001), and t0 and t45 (t[30] = 3.33, p = .002), but not between t15 and t45 (t[30] = 0.37, p = .714).

There were no significant main effects for study group, F(1, 42) = 0.23, p = .879, ηp2 = .001, and sex, F(1, 42) = 1.47, p = .231, ηp2 = .034, and no significant interaction between sex and group, F(1, 42) = 0.11, p = .748, ηp2 = .002.

Catecholamines To examine if there was a difference between the patient and control group in catecholamines a further MANOVA was conducted. There was no significant difference for epinephrine between groups, F(1, 43) = 0.07, p = .792, ηp2 = .002, but there was a significant effect for norepinephrine, F(1, 43) = 5.87, p = .020, ηp2 = .120.

The patient group showed a significantly lower norepinephrine level (M = 18.64, SD = 8.91) compared to the control group (M = 27.68, SD = 8.81). There was neither Ó 2016 Hogrefe Publishing

A MANOVA was conducted in order to compare HR and the different parameters of HRV between the two sample groups. There were no significant group differences for HR, F(1, 46) = 0.04, p = 840, ηp2 = .001; SDNN, F(1, 46) = 1.33, p = .255, ηp2 = .028; lnRMSSD, F(1, 46) = 0.04, p = .843, ηp2 = .001; lnLF, F(1, 46) = 1.56, p = .206, ηp2 = .035; and lnHF, F(1, 46) = .01, p = .937, ηp2 = .000. However, there was a significant main effect for lnLF/HF, indicating that the patient group had significantly lower values (M = 1.15, SD = .54) than the control group (M = 1.59, SD = 0.56), F(1, 46) = 4.11, p = .048, ηp2 = .082. Again, medication was entered as a covariate in the analysis. Effects of HRV parameters were unaltered, thus suggesting that medication did not bias the results, F(1, 47) = 0.616, p = .716, ηp2 = .079.

There were no significant sex differences in any HRV parameter, F(6, 44) = 0.30, p = .933, ηp2 = .042. The interaction between sex and group was also not significant, F(6, 41) = 1.19, p = .330, ηp2 = .149).

Discussion The objective of the present study was to investigate whether physiological underpinnings of a burnout diagnosis can be secured by comparing a clinically diagnosed burnout sample and a nonclinical control group. On account of the fact that the diagnosis “burnout” is currently based exclusively on self-reports and how individuals communicate their symptoms we aimed to explore whether the measurement of biopsychological variables could help to objectify the symptoms described by patients. Therefore, a range of measures of the SAM axis (catecholamines, HR, HRV, and blood pressure) and the HPA axis (cortisol) were analyzed and integrated into two alternative ALIs. Contrary to expectation, both, the traditional ALI and the extended ALI scores were significantly higher in the control group as compared to the patient group. Aberrant physiological activation in SAM and HPA axes could not be found in the patient group but was rather prevalent in the control group. The control group showed significantly higher values for blood pressure (SBP and DBP), WHR, norepinephrine, and HRV (LF/HF) and lower cortisol (percentage of increase) than the patient group, which suggests that the physiological state of the control group might indicate higher physiological burden than the patient group.

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Additional analyses demonstrating associations between the ALI and MBI subscales showed significant inverse correlations between both AL indices and their constituents and depersonalization and personal accomplishment.

However, there were no associations with emotional exhaustion. In sum, these findings largely support the above-mentioned evidence that the burnout group showed lower physiological burden as compared to the control group. Importantly, it should be emphasized that the higher physiological activity in the control group may not be attributed to the rather high level of emotional exhaustion in this group, because there were no correlations with this subdimension.

Maslach Burnout Inventory (MBI) Assessment of burnout was performed with the German version of the MBI (Schaufeli et al., 1996) because this inventory is the most widely used self-report instrument to measure burnout. Significant differences could be observed for two subscales of the MBI. The patient group showed significantly higher scores in depersonalization and lack of personal accomplishment as compared to the control group. No significant differences could be found for emotional exhaustion, which was elevated in both groups. Hence, it might be assumed that between-group differences in physiological activity were probably underestimated, because of a restricted between-group variance in this core dimension of burnout. Nonetheless, it should be noted that according to the authors of the MBI, a burnout manifestation is indicated by elevated scores for both subtests (emotional exhaustion and depersonalization); contrary to the subscale personal accomplishment where a reverse scoring is used. With regard to this definition, burnout patients showed significantly higher burnout symptoms as compared to the control group. Because of the fact that emotional exhaustion is regarded as the most valid burnout dimension in the literature, this subscale is often isolated mentioned without including the other two subscales. It is the most widely reported and most often analyzed component of this syndrome (Shirom, Melamed, & Toker, 2005), although the authors of the MBI emphasized that burnout is multidimensional and not a unitary construct. Hence, it is difficult to compare the results across studies.

Cortisol CAR was analyzed as a reliable indicator of the HPA axis activity, which is not severely influenced by smoking, alcohol, or sleep duration (Clow, Thorn, Evans, & Hucklebridge, 2004; Pruessner et al., 1999; Wüst, Wolf, et al., 2000; Wüst, Federenko, Hellhammer, Journal of Psychophysiology (2018), 32(1), 30–42

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& Kirschbaum, 2000). Cortisol shows large individual variations with normal values for free cortisol ranging between 5 and 23 nmol/L (Pruessner et al., 1997). Because of this large variability the diagnostic value of this measurement could be limited insofar as there could be a significant overlap of morning cortisol between healthy individuals and patients with adrenal insufficiency (Laudat et al., 1988).

However, in the patient group the initial increase of cortisol within the first hour after awakening seemed to correspond with a normal circadian HPA axis profile (50–60% increase after awakening; Pruessner et al., 1997; Wüst, Wolf, et al., 2000). Contrary to that, the percentage of cortisol increase ranged below 20% in the control group.

These findings suggest that individuals with burnout showed a rather normal HPA axis functionality, whereas the control group showed some evidence of a compromised HPA axis function. Contrary to this finding, Marchand et al.

(2014) reported correlations between severe burnout and lowest cortisol concentration 30 min upon awakening.

It should be noted that a meta-analysis of 62 studies found that the magnitude of the CAR seems to be positively associated with job stress and general life stress, but negatively associated with fatigue, burnout, and exhaustion (Chida & Steptoe, 2009). The finding of the present study is not in line with this evidence, but rather suggests that the control group showed a blunted CAR. One possible explanation could be that patients were on sick leave before entering the rehabilitation center for an average of 12 weeks.

Under such circumstances, group differences in CAR profiles could lead to biased results (Stalder et al., 2016). It is conceivable that this period of time and the absence of job stress could enable a regeneration of the HPA axis. In order to verify if medication of the patient group could be explaining the results, we controlled for medication in additional analyses which, however, did not alter findings.

Of note, there were significant differences in the CAR between men and women, with women showing a delayed peak response at 45 min after awakening and a less steep increase immediately after awakening. Although hormonal status could severely influence cortisol secretion and this study did not control for menstrual status, the findings seem to corroborate previous work suggesting that premenopausal women as compared to men exhibit a stronger cortisol increase with a delayed peak after awakening (Pruessner et al., 1997). Future studies should thoroughly control for menstrual cycle effects in order to ensure the robustness of this finding.

Heart Rate Variability (HRV) HRV has been discussed as a sensitive indicator of stress, high load, and recovery (Lanfranchi & Somers, 2002; Ó 2016 Hogrefe Publishing

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van Amelsvoort, 2001). The aim of the study was to examine whether various time-domain (SDNN, RMSSD) and frequency-domain measures of HRV (LF, HF, LF/ HF) are related to burnout. Because frequency-domain measures of HRV are often used as a tool to quantify “autonomic balance” (Grote, 2009), we expected that burnout patients would display lower HF and higher values in LF/HF as well as lower SDNN and RMSSD as compared to their nonclinical counterparts. The findings could not confirm the hypothesis. There was no evidence of autonomic dysbalance as indexed by SDNN, RMSSD, HF, and LF/HF ratio in the patient group. Again, controlling for medication did not alter the cardiac findings.

However, contrary to expectation, participants of the control group showed a significantly higher LF/HF ratio than the patient group. This variable has been discussed to reflect the relative balance between sympathetic and parasympathetic cardiac efference. Hence, the findings are suggestive of a sympathetic predominance in the control group, but not in the patient group. One possible explanation of this finding could be that participants of the control group were still in their working process compared to the patients being on sick leave for at least 12 weeks. It should also be noted that HRV could have been influenced by bodily movement during the monitoring phase within the two groups. Because individuals of the control group were undergoing their daily working routines it is conceivable that they were also more physically active than the stationary patients. Unfortunately, bodily movement was not recorded in this study; hence, we are not able to rule out this explanation. However, it should be emphasized that HR – which should be most sensitive to differences in metabolic demand – was not significantly different between groups. Nonetheless, future studies should examine burnout-related differences in cardiac activity in more detail, thereby controlling for bodily movement.

Blood Pressure There were significant between-group differences in resting blood pressure, documenting that burnout patients showed significantly lower values than the control group. This result is not in line with those of previous research, which found elevated blood pressure levels in a patient group (Steptoe et al., 1999; Steptoe, Roy, & Evans, 1996) or no significant differences relative to controls (De Vente et al., 2003; Langelaan et al., 2007). We want to emphasize that the recording procedure was comparable between groups, namely there was a 5 min rest before the first measurement followed by another measurement within the next 10 min.

Hence, it seems unlikely that differences in bodily movement contributed to this effect. However, it could well be Ó 2016 Hogrefe Publishing

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that individuals in the control group, who were working in a challenging environment, were much more stressed as compared to the nonworking patients.

Catecholamines Epinephrine and norepinephrine were assessed as direct indicators of general sympathetic activity (Reyes del Paso et al., 2013) and have been discussed to reflect the acute mental and physical workload of an individual (Sluiter, 2000). Nocturnal urinary catecholamines were assessed as indicators of recovery. Of note, norepinephrine values were significantly higher in the control group as compared to the patient group, but there was no significant difference in epinephrine. It is interesting to note that reactivity of epinephrine, but not norepinephrine, has been more strongly related to psychosomatic complaints, whereas norepinephrine has been related to physical exertion (Meijman, Mulders, & van Kompier, 1990). Hence, it might be speculated that individuals in the control group showed greater physical exertion because they were working full time, indicating an impaired regeneration process.

The results are concordant with the findings on HRV, which suggest a predominance of sympathetic relative to parasympathetic innervation in the control group. It could be speculated that this elevated activity of the ANS could have extended into the nighttime, thus impairing nocturnal recovery. In order to examine the recovery process in more detail, it would certainly be worthwhile to assess the day-to-night differences in these variables thoroughly.

Unfortunately, we did not collect urine samples across the day, thus precluding further analyses.

Limitations The present study has several limitations that should be emphasized: First, the number of participants in each group was unbalanced, which might have affected the robustness of the findings. Furthermore, the comparably moderate sample size in each group – especially in the control group – limits the statistical power of the analyses and makes it difficult to secure reliable effects. Second, data on consumption of coffee, tea, and alcohol, which could all have an impact on the catecholamines (increase) as well as on the HRV data (decrease), were not collected. Third, in order to get an average HRV value throughout the day a restricted assessment approach was applied by calculating randomized segments of 15 min per hour in both groups during the day. Thus, the generalizability of the cardiac findings might be questioned. However, research suggests that even ultrashort recordings of HRV are enough to obtain robust values (e.g., Munoz, van Roon, Riesel, Thio, & Oostenbroek, 2015). Fourth, in order to reduce Journal of Psychophysiology (2018), 32(1), 30–42

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the demands posed on the participants, cortisol morning rise was assessed at awaking, 15 and 45 min later. Hence, we did not assess cortisol 30 min after awaking, which might have affected the robustness of the CAR and limits comparability with previous research. Fifth, the multiple comparisons of the diverse psychobiological variables could have increased Type-I error, thus increasing the chance of spurious findings. However, to overcome this limitation two integrative ALI scores were calculated that substantiated the results. Hence, we are quite confident that the main finding of increased physiological load in the control group relative to the patient group was robust. Finally, with regard to the catecholamines, no data were collected during the day, which limits interpretation of nocturnal recovery.

Conclusions In conclusion, the hypotheses of this study could not be confirmed. We expected allostatic load symptoms in different variables of the HPA and SAM axes in burnout patients. Contrary to that, signs of higher physiological burden seemed to be more prevalent in the control group.

These results suggest a divergence between subjectively experienced burnout symptoms and physiological data.

Consequently, it might be questioned whether the subjective experience of burnout is tied to bodily dysregulations or exclusively reflects a psychological phenomenon.

In our view, there are at least three possible explanations for this challenging finding: First, due to the fact that the patient group was on sick leave for at least 12 weeks, physiological recovery might have already taken place, suggesting that bodily symptoms might have abolished. This interpretation would offer a promising perspective on burnout and its treatment because it would suggest that physical exhaustion in burnout individuals might be a reversible state that might take a time frame of a few weeks to recover. Second, it could be argued that burnout may be a less stigmatized diagnosis as compared to other mental diseases (e.g., depression) and offers several individual benefits. In some countries a formal burnout diagnosis could result in financial compensation arrangements, counseling, psychotherapeutic treatment, and rehabilitation (Schaufeli et al., 2009). Moreover, burnout as compared to depression is regarded as a label for extraordinary engagement, ambitiousness, and work commitment. Together with the popularity of burnout in many western countries this could make burnout a rather adoptable diagnosis giving way to sickness behavior without organismic manifestation.

Third, an exhaustive list of symptoms (132 in total; Burisch, 1989) have been associated with burnout, suggesting that the construct seems to be used as an umbrella term with little specificity. Thus, the definition of “burnout” varies Journal of Psychophysiology (2018), 32(1), 30–42

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with its context and the intentions of those using the term (Schaufeli et al., 2009). Hence, physiological concomitants might get blurred by the diversity of symptoms.

To conclude, the findings of this study suggest a discrepancy between self-reported burnout and psychobiological activation. Further studies are needed to analyze a wider range of physiological variables (e.g., parameters of the immune system) using a longitudinal research design in order to substantiate – or falsify – the finding of this study.

Acknowledgments This study received founding by the Austrian Social Insurance for Occupational Risks (AUVA) and the province of Styria, Department of Research and Science.

Ethics and Disclosure Statements Conflicts of Interest. The authors Claudia Traunmüller, Kerstin Gaisbachgrabner, Helmut Lackner, and Andreas Schwerdtfeger declare that they have no conflict of interest.

Ethical Approval. All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional and/or National Research Committee (GZ. 39/43/63 ex 2011/12) and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed Consent. Informed consent was obtained from all individual participants included in the study.

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Received November 27, 2015 Accepted June 7, 2016 Published online November 22, 2016

Claudia Traunmüller Department of Psychology, Health Psychology Unit University of Graz Universitaetsplatz 2/III 8010 Graz Austria claudia.traunmueller@uni-graz.at

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