Biological Psychology 98 (2014) 1–5
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Models and methods of emotional concordance Tom Hollenstein ∗ , Dianna Lanteigne Department of Psychology, Queen’s University, Kingston, Ontario K7L 3N6, Canada
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Article history: Received 5 November 2013 Accepted 17 December 2013 Available online 3 January 2014 Keywords: Emotion Concordance Emotion regulation Psychophysiology Emotional expression Cognitive appraisal
a b s t r a c t Theories of emotion generally posit the synchronized, coordinated, and/or emergent combination of psychophysiological, cognitive, and behavioral components of the emotion system – emotional concordance – as a functional definition of emotion. However, the empirical support for this claim has been weak or inconsistent. As an introduction to this special issue on emotional concordance, we consider three domains of explanations as to why this theory–data gap might exist. First, theory may need to be revised to more accurately reflect past research. Second, there may be moderating factors such as emotion regulation, context, or individual differences that have obscured concordance. Finally, the methods typically used to test theory may be inadequate. In particular, we review a variety of potential issues: intensity of emotions elicited in the laboratory, nonlinearity, between- versus within-subject associations, the relative timing of components, bivariate versus multivariate approaches, and diversity of physiological processes. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Explicitly or implicitly, almost all models of emotion rely on the idea that (a) there are multiple components in the emotion response system, chiefly physiological, cognitive (appraisal), expressive, and behavioral; and (b) emotion is identified by some degree of coordination among these components (Barrett & Campos, 1987; Darwin, 1872; Ekman, 1992; Fogel et al., 1992; Gross, 2007; Lang, 1994; Lazarus, 1991; Levenson, 1994; Mauss, Levenson, McCarter, Wilhelm, & Gross, 2005; Quas, Hong, Alkon, & Boyce, 2000; Rosenberg & Ekman, 1997; Scherer, 2005; Sze, Gyurak, Yuan, & Levenson, 2010; Tomkins, 1962). Indeed, the issue of emotional concordance features prominently in early theories of emotion (Cannon, 1927; Darwin, 1872; James, 1884, 1894) and continues to this day with modern, comprehensive models reflecting the latest research (Damasio, 1998; Frijda, 2007; Gross & Thompson, 2007; Matsumoto & Ekman, 2009; Ortony, Clore, & Collins, 1988; Sander, Grandjean, & Scherer, 2005). The canonical fear response, for example, should be a synchronized combination of a threat appraisal, fearful facial affect, elevated sympathetic arousal, and an urge to flee the threatening situation. In this way, emotion is conceptualized as a dynamic, mutual amplification of components of the emotion system to create an adaptive and coherent response to one’s current circumstances. There is one non-trivial problem that has dogged this conceptualization of emotion for more than a century: poor empirical
∗ Corresponding author. Tel.: +1 6135333288. E-mail address: [email protected] (T. Hollenstein). 0301-0511/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.biopsycho.2013.12.012
support. Concordance has been weakly supported by the data, at best, but often not supported, with some research even showing evidence for the opposite, discordance or negative associations (Adelmann & Zajonc, 1989; Hastings et al., 2009; Lang, 1968; Mauss & Robinson, 2009; Mauss, Wilhelm, & Gross, 2004). Moreover, the file-drawer problem may be particularly relevant to examinations of concordance and the inconsistent results in the literature could be the tip of an iceberg of null findings that never make it to an editor’s desk. The purpose of this special issue is to shed a concentrated light on this perennial problem with a group of papers addressing various aspects of the concordance of physiological responses with each other and other emotion system components. To introduce this issue, we review subtle differences between conceptualizations of concordance and provide a range of explanations as to why concordance may not have the expected empirical support. 2. What do we mean by ‘concordance’? Emotional concordance has gone by various names over the years, including concordance (Nesse et al., 1985; Wilhelm & Roth, 2001), response system coherence (Ekman, 1992; Mauss et al., 2005), organization of response tendencies (Lazarus, 1991; Levenson, 1994) or response components (Scherer, 1984; Witherington, Campos, & Hertenstein, 2001), or response component syndromes (Averill, 1980; Reisenzein, 2000). We prefer the term concordance – and the opposite, discordance – rather than other terms (e.g., coherence, convergence, organization, synchrony) and their respective opposites. Concordance and discordance are clear and precise terms that delineate the two possibilities of combinations of emotional processes. Divergence
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is inappropriate because it incorrectly suggests that that response components are “moving away” from each other. Incoherence lacks precision and has a negative connotation that would not work for this context. Disorganization implies a haphazard coordination among components. Synchrony can be used to describe both temporally positive and negative associations among components and asynchrony is simply a lack of that synchrony. Using the term discordance is also favorable because it can be used effectively in combination with these other terms to describe more fine-grained aspects of emotional processes. For example, certain discordant emotional responses can be evaluated as coherent (e.g., suppressing expression) or incoherent (e.g., disorganized). Thus, although the use of a single term may occlude these important distinctions, we argue that concordance–discordance is the best over-arching framework. However, in the future it may be optimal for the field to create a more multi-dimensional conceptualization that combines these important features. For example, Bulteel et al. (2014) distinguish two types of concordance: pattern and synchrony. Regardless of the terminology, the lack of empirical support has inspired more nuanced conceptualizations of the coordination among emotion system elements. One approach has been to identify the relations among components to be a loose coupling (Lang, 1988) or probabilistically weak (Bradley & Lang, 2000). Other caveats involve associating concordance with only relatively strong emotional responses (Russell, 2003; Scherer, 1984). Still others argue that discordance may be the norm rather than the exception due to regulatory efforts to disrupt emotional processes (Butler, Gross, & Barnard, 2014; Dan-Glauser & Gross, 2013; Lanteigne, Flynn, Eastabrook, & Hollenstein, 2012). Here, we explore a range of possible explanations for the limited support for emotional concordance grouped into three broad categories: (1) theories should reflect the data and be revised; (2) moderating factors have not been sufficiently considered; and (3) methods have been inappropriate.
3. Why is there limited support for concordance? Theory. The first and most obvious explanation would be that the theoretical premise behind concordance is wrong (Barrett, 2006; Bradley & Lang, 2000; Fridlund, 1997; Reisenzein, 2000). Barrett (2006) most recently and forcefully makes the argument that progress in understanding emotions is impeded by the pervasive assumption that there are “natural kinds” of emotions comprised of a set of “characteristic property clusters”. The search for emotion-specific concordance – a unique combination of physiological, behavioral, and cognitive components for each “natural kind” of emotion – has been a fool’s errand. Instead, “[r]ather than beginning with an abstract, theoretical construct (e.g., anger) that we try to identify in human behavior, perhaps we could concentrate our empirical efforts on identifying which observables (e.g., cardiovascular changes, facial expressions, startle responses, electroencephalographic recordings, subjective experience, conscious thoughts) are implicated across instances of emoting and observe, rather than prescribe, their relationships in varying circumstances and time frames.” (Barrett, 2006, p. 48). Thus, from this perspective concordance is still seen as important, yet only as a bottom-up process through which we can discover functional combinations via inductive rather than deductive inquiry. This bottom-up approach has also been advocated by emergent accounts of emotion (e.g., Lewis, 2005). Coan (2010), for example, makes a compelling argument that there has been a problematic reliance on latent variable approaches for the examination of what is generally agreed is an emergent process. With a latent approach, indicators of emotions (e.g., physiological, cognitive, behavioral) all reflect an underlying emotion process and are reasonably interchangeable. The conceptual underpinning of such an approach is
that there is a latent process, emotion, which is manifest in various ways in body, behavior, and felt experience. In contrast, and more consistent with theoretical claims, emergent approaches model these components as interacting elements in a dynamic system from which emotion arises (Coan, 2010; Lewis, 2005). Thus, one reason why evidence for concordance has been inconsistent could be the traditional application of latent models for a putatively emergent process. It also makes a difference which components of the emotion system are selected for tests of concordance. For the vast majority of investigations, this is done with estimates of paired associations (e.g., correlations). With these pairings, associations between self-reported experience and behavioral expression have been the strongest, while pairings that include physiological variables have been the most inconsistent (e.g., Fischer & Roseman, 2007; Mauss et al., 2005; also see Evers et al., 2014). A second kind of pairing is across various physiological measures (Bulteel et al., 2014; Gentsch et al., 2014), which has yielded the full spectrum of results: negative, positive, and null (Kreibig, Wilhelm, Roth, & Gross, 2007; Mauss et al., 2005). At least two issues stem from this component pairing approach. First, the reliance on paired associations for what is, at minimum, a three-component process (e.g., physiology, appraisals, behavior) reflects methodological limitations rather than a strong theoretical prediction that concordance should be bivariate (Bulteel et al., 2014; Lanteigne et al., 2012). Second, it could be argued that associations within a particular domain of emotion components, such as physiology, do not really capture the spirit of the concordance question by excluding the experiential, cognitive, or behavioral aspects of emotional response. Another question is whether concordance should occur in the same way for all situations. First, as argued by Evers et al. (2014), there may be at least two levels of processing which would reflect different possibilities for concordance. Rapid, automatic concordance may not be functionally comparable to reflective processes that occur at longer time scales. Second, the means by which emotions are elicited may be important. Receptive or passive experience of emotional content (e.g., films) is often asocial and can be contrasted to active, social or generative experiences that induce emotional arousal. Finally, there are diverse ways to operationalize concordance. For example, the overall pattern of responsivity across domains captures a different aspect of concordance than the relative synchrony of dynamic processes (Bulteel et al., 2014). Moderators. Another set of reasons for why concordance has been elusive is the relative neglect of important moderators of emotion processes. For example, because emotions are situationspecific adaptations, context may be a focal rather than peripheral aspect of concordance. The Ortony, Clore, and Collings (OCC) model (Clore & Ortony, 2013; Ortony, Clore, & Collins, 1988), for example, asserts that emotions cohere around situations rather than just being constrained by context. Thus, the missing ingredient in the list of emotion components is the situation itself and the relative neglect of this ingredient is partly responsible for limited evidence in support of concordance. As argued by Butler et al. (2014), the concordance problem may stem from the relative neglect of regulatory processes in emotion theory and research. With the inclusion of neural processes into modern accounts of emotions, the separation of emotional processes from cognition or regulation has become untenable (Lewis, 2005; Thompson, Lewis, & Calkins, 2008). That is, at no point during an emotional process is regulation not occurring. Emotion regulation covers a wide array of processes and most of these target specific emotion components over others (e.g., suppression of expression, re-appraisal, relaxation to modulate physiological arousal). More generally, the down-regulation of emotion is the top-down, negative feedback counterpart to the
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bottom-up, positive feedback (i.e., emergent) processes that give rise to a concordant emotional response. This could explain why concordance would be more evident at greater intensities when regulatory processes are temporarily overwhelmed. Furthermore, when emotion regulation processes are compromised, such as in dysregulated clinical populations or through experimental manipulation, greater concordance among emotion system components would be expected. Thus, a question that emerges in this special issue is whether regulatory dynamics (e.g., the ebb and flow of RSA) are part of the concordance process postulated by theory (Crowell et al., 2014) or, as Butler et al. (2014) argue, whether regulation interferes with concordance. Theoretically, the concordance postulate is that some form of coordination across components of the emotion system universally defines emotion. However, individual differences certainly have an impact on the degree to which concordance can be observed. Cultural norms and socialization direct the which, where, when, how, and with whom of emotional expressivity (Ekman, 1973; Cole & Tamang, 1998; Matsumoto, Yoo, & Fontaine, 2008). Physiological responsivity, especially in the autonomic and cardiac systems, varies as a function of physical fitness and health (Salmon, 2001; Schlicht, 1994). Self-reports and appraisals also vary as a function of temperament, life-history, and culture (Kuppens & Tong, 2010; Scherer, 1997). These factors complicate the assessment of concordance. Despite the poor evidentiary record, concordance has not fallen out of theoretical favor. Why? Perhaps the intuitive appeal of concordance motivates resistance to revising models of emotion based on a dubious collection of findings. While theoretical parsimony and potential moderators are no doubt part of the problem, most researchers seem to be holding off on radical revisions to theory in lieu of more concentrated and sophisticated efforts to adequately model concordance. This jury-is-still-out perspective reflects the gap between theoretically rich models and an uncertain and limited set of methodological techniques to test these claims (Richters, 1997). Indeed, most recent considerations of concordance place criticism on inadequate methods, which is why we discuss methods in more detail below and have assembled a variety of methodological approaches for this special issue. Methods. The remaining reasons for limited support for concordance are methodological. First, the failure to detect concordance may come from failures to adequately elicit specific emotions in the lab. A recent special issue in this journal explored this possibility by demonstrating emotion-specific physiological response patterns (Friedman & Kreibig, 2010; Stephens, Christie, & Friedman, 2010). Moreover, as Friedman, Stephens, & Thayer (2014) suggest, basic, core emotions may evoke greater concordance than less canonical or universal emotional states. The large variety of emotional elicitation paradigms, even for one emotional state, and diversity of analytical techniques has so far made assessments of emotionspecific concordance inconclusive. Second, the common conceptualization of concordance is that of a positive feedback process in which physiological, cognitive, and expressive components mutually amplify each other to form emotional states. Because emotional states reach a finite zenith before eventually resolving into less intense or neutral states, there must also be negative feedback processes (e.g., regulation) that counteract the positive feedback processes. These positive-negative feedback loops are the bedrock of biological functioning and are by their very nature not linear. These non-linearities manifest as threshold effects, for example, such as those captured by catastrophe models (Guastello, 2013). Thus, linear statistics and models might not be the best approach for capturing the non-linearity of emotional concordance. Another problem that has been frequently identified is the issue with using between-subjects approaches to a within-subject
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problem (Reisenzein, 2000). At the simplest level this would entail favoring within-subject correlations and eschewing betweensubject approaches (see Butler et al., 2014 for an extensive discussion). Fourth, the general prediction is that concordance should increase with intensity (Davidson, 1992; Mauss et al., 2005; Rosenberg & Ekman, 1997). By extension, full concordance may only be possible in extreme circumstances (e.g., fear in a violent, life-threatening moment). Modern challenges are typically less dire than the environmental pressures for which emotions evolved, thus concordance may be the exception rather than rule (Friedman et al., 2014). Hence, ethical constraints and experimental reductionism may also be a factor in limiting assessment of concordance. Fifth, in emotion research, it is most common to use a stimulus onset as a synchronizing point for psychophysiological, expressive, and appraisal components. However, the time course of emotion components may vary greatly and therefore synchronized changes in two or more time series may not be simultaneous. For example, to address 2014, some recent studies have used windows of 6-10 second lags within which to find the maximum correlation between components (Butler et al., 2014; Dan-Glauser & Gross, 2013). Whatever the solution, it is probable that analyses based on simultaneous changes across components will produce attenuated indices of concordance. Finally, the diverse nature of physiological measures and their putative psychological meaning make it difficult to generalize about what would constitute evidence of concordance. As can be seen in the wide range of measures used in the studies in this special issue, there are important functional differences in neural, autonomic, muscular, and endocrine processes that must be factored in. For example, as shown by Crowell et al. (2014), concordance with RSA is complex due to the nature of parasympathetic withdrawal. This withdrawal indicates regulatory effort but also enables greater sympathetic arousal, which in combination could obscure clear interpretation of concordance among system components. Thus, temporally linked divergence of emotion processes may need to be added to conceptualizations of emotion concordance.
4. This special issue For this special issue, we have assembled contributions that reflect diverse approaches to the issue of emotional concordance. Table 1 summarizes the experimental context, emotions, measures, analytical techniques, and support for concordance for each of the novel empirical contributions. Each one addresses at least one of the issues mentioned above. Bulteel et al., propose a new methodology that is particularly well-suited to the detection of both pattern and synchrony across multiple measures. Butler et al., test how efforts to regulate emotions might interfere with concordant processes. Crowell et al. investigate how physiological regulation (RSA) and behavior may be concordant within and between individuals. Evers et al. test a dual process model that distinguishes between automatic and reflective processes. Friedman et al. use redundancy analysis to estimate the degree of shared variance across various measures of emotional responses to evocative films. Gentsch et al. explore the concordance across two physiological systems, facial muscles and event-related potentials, as a test of the component process model. Schaefer et al. provide some evidence that the intensity of emotional reactivity may be a factor related to concordance. Finally, the theoretical contribution of Quigley and Barrett (2014) caps off this special issue to complete the set of attempts to take the problem of concordance seriously and tackle it head on. Concordance is an intuitively appealing concept but one that is fraught with theoretical and methodological issues. We hope that this collection inspires and focuses future research, ultimately
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Table 1 Summary of empirical contributions to the special issue. Experimental design
Emotion(s) elicited
Measures
Analysis
Support for concordance?
Bulteel et al.
Pleasant IAPS pictures
Unspecified positive
IBI; SCL; EMG
De-Con (new technique for assessing concordance)
Butler et al.
Discussion of upsetting film; suppression, reappraisal and control conditions
Unspecified negative-positive
IBI; SCL; BP; video self-report; observed verbal/non-verbal expression
Crowell et al.
Depressed and self-injuring adolescents & controls; mother-adolescent conflict discussion Interrupted counting task; lexical-decision task; anger self-report
Observed aversiveness
RSA and observed aversiveness of both dyad members
Multivariate multilevel model of auto-/crosscorrelations (max within ± 6 second window) Two-level actor-partner interaction model
General support for patterning and synchronization concordance; notable individual differences Max cross-correlation = |.3| in control condition; evidence that regulation disrupts concordance
Anger
Friedman et al.
Music and film clips
Content, amused, fearful, angry, sad & neutral
Gentsch et al.
Feedback during monetary gambling task
Schaefer et al.
Video clips of snakes (threatening and non-threatening) and fish; fMRI; snake phobics & controls
Unspecified (appraisals of goal conduciveness and power) Fear
Automatic: anger accessibility in lexical task; Reflective: self-reported anger; MAP IBI; RSA; PEP; RR; MAP; SCL; SBP; DBP; LVET; SV; CO; TPR;TI; TE; self-report of 6 emotions ERP and EMG
Evers et al.
Pupil diameter; SCL; self-reported valence and arousal; voxel activation
Within-individual concordance for clinical group; between-individual concordance for controls
Multiple regression
Within-system (automatic or reflective) but not between-system concordance
Redundancy analysis
Up to 28% shared variance (canonical r = .53)
Principal components analysis
ERPs (appraisals) loaded with EMG in expected directions
ANOVAs and chi-square
Phobics had greater concordance in threatening snake condition compared to controls
Note: IBI = interbeat interval; SCL = skin conductance level; EMG = electromyography; BP = blood pressure; RSA = respiratory sinus arrhythmia; MAP = mean arterial pressure; PEP = pre-ejection period; RR = R-to-R interval; SBP = systolic blood pressure; DBP = diastolic blood pressure; LVET = left ventricular ejection time; SV = stroke volume; CO = cardiac output; TPR = total peripheral resistance; TI = inspiration time; TE = expiration time.
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Biological Psychology journal homepage: www.elsevier.com/locate/biopsycho
Models and methods of emotional concordance Tom Hollenstein ∗ , Dianna Lanteigne Department of Psychology, Queen’s University, Kingston, Ontario K7L 3N6, Canada
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Article history: Received 5 November 2013 Accepted 17 December 2013 Available online 3 January 2014 Keywords: Emotion Concordance Emotion regulation Psychophysiology Emotional expression Cognitive appraisal
a b s t r a c t Theories of emotion generally posit the synchronized, coordinated, and/or emergent combination of psychophysiological, cognitive, and behavioral components of the emotion system – emotional concordance – as a functional definition of emotion. However, the empirical support for this claim has been weak or inconsistent. As an introduction to this special issue on emotional concordance, we consider three domains of explanations as to why this theory–data gap might exist. First, theory may need to be revised to more accurately reflect past research. Second, there may be moderating factors such as emotion regulation, context, or individual differences that have obscured concordance. Finally, the methods typically used to test theory may be inadequate. In particular, we review a variety of potential issues: intensity of emotions elicited in the laboratory, nonlinearity, between- versus within-subject associations, the relative timing of components, bivariate versus multivariate approaches, and diversity of physiological processes. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Explicitly or implicitly, almost all models of emotion rely on the idea that (a) there are multiple components in the emotion response system, chiefly physiological, cognitive (appraisal), expressive, and behavioral; and (b) emotion is identified by some degree of coordination among these components (Barrett & Campos, 1987; Darwin, 1872; Ekman, 1992; Fogel et al., 1992; Gross, 2007; Lang, 1994; Lazarus, 1991; Levenson, 1994; Mauss, Levenson, McCarter, Wilhelm, & Gross, 2005; Quas, Hong, Alkon, & Boyce, 2000; Rosenberg & Ekman, 1997; Scherer, 2005; Sze, Gyurak, Yuan, & Levenson, 2010; Tomkins, 1962). Indeed, the issue of emotional concordance features prominently in early theories of emotion (Cannon, 1927; Darwin, 1872; James, 1884, 1894) and continues to this day with modern, comprehensive models reflecting the latest research (Damasio, 1998; Frijda, 2007; Gross & Thompson, 2007; Matsumoto & Ekman, 2009; Ortony, Clore, & Collins, 1988; Sander, Grandjean, & Scherer, 2005). The canonical fear response, for example, should be a synchronized combination of a threat appraisal, fearful facial affect, elevated sympathetic arousal, and an urge to flee the threatening situation. In this way, emotion is conceptualized as a dynamic, mutual amplification of components of the emotion system to create an adaptive and coherent response to one’s current circumstances. There is one non-trivial problem that has dogged this conceptualization of emotion for more than a century: poor empirical
∗ Corresponding author. Tel.: +1 6135333288. E-mail address: [email protected] (T. Hollenstein). 0301-0511/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.biopsycho.2013.12.012
support. Concordance has been weakly supported by the data, at best, but often not supported, with some research even showing evidence for the opposite, discordance or negative associations (Adelmann & Zajonc, 1989; Hastings et al., 2009; Lang, 1968; Mauss & Robinson, 2009; Mauss, Wilhelm, & Gross, 2004). Moreover, the file-drawer problem may be particularly relevant to examinations of concordance and the inconsistent results in the literature could be the tip of an iceberg of null findings that never make it to an editor’s desk. The purpose of this special issue is to shed a concentrated light on this perennial problem with a group of papers addressing various aspects of the concordance of physiological responses with each other and other emotion system components. To introduce this issue, we review subtle differences between conceptualizations of concordance and provide a range of explanations as to why concordance may not have the expected empirical support. 2. What do we mean by ‘concordance’? Emotional concordance has gone by various names over the years, including concordance (Nesse et al., 1985; Wilhelm & Roth, 2001), response system coherence (Ekman, 1992; Mauss et al., 2005), organization of response tendencies (Lazarus, 1991; Levenson, 1994) or response components (Scherer, 1984; Witherington, Campos, & Hertenstein, 2001), or response component syndromes (Averill, 1980; Reisenzein, 2000). We prefer the term concordance – and the opposite, discordance – rather than other terms (e.g., coherence, convergence, organization, synchrony) and their respective opposites. Concordance and discordance are clear and precise terms that delineate the two possibilities of combinations of emotional processes. Divergence
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is inappropriate because it incorrectly suggests that that response components are “moving away” from each other. Incoherence lacks precision and has a negative connotation that would not work for this context. Disorganization implies a haphazard coordination among components. Synchrony can be used to describe both temporally positive and negative associations among components and asynchrony is simply a lack of that synchrony. Using the term discordance is also favorable because it can be used effectively in combination with these other terms to describe more fine-grained aspects of emotional processes. For example, certain discordant emotional responses can be evaluated as coherent (e.g., suppressing expression) or incoherent (e.g., disorganized). Thus, although the use of a single term may occlude these important distinctions, we argue that concordance–discordance is the best over-arching framework. However, in the future it may be optimal for the field to create a more multi-dimensional conceptualization that combines these important features. For example, Bulteel et al. (2014) distinguish two types of concordance: pattern and synchrony. Regardless of the terminology, the lack of empirical support has inspired more nuanced conceptualizations of the coordination among emotion system elements. One approach has been to identify the relations among components to be a loose coupling (Lang, 1988) or probabilistically weak (Bradley & Lang, 2000). Other caveats involve associating concordance with only relatively strong emotional responses (Russell, 2003; Scherer, 1984). Still others argue that discordance may be the norm rather than the exception due to regulatory efforts to disrupt emotional processes (Butler, Gross, & Barnard, 2014; Dan-Glauser & Gross, 2013; Lanteigne, Flynn, Eastabrook, & Hollenstein, 2012). Here, we explore a range of possible explanations for the limited support for emotional concordance grouped into three broad categories: (1) theories should reflect the data and be revised; (2) moderating factors have not been sufficiently considered; and (3) methods have been inappropriate.
3. Why is there limited support for concordance? Theory. The first and most obvious explanation would be that the theoretical premise behind concordance is wrong (Barrett, 2006; Bradley & Lang, 2000; Fridlund, 1997; Reisenzein, 2000). Barrett (2006) most recently and forcefully makes the argument that progress in understanding emotions is impeded by the pervasive assumption that there are “natural kinds” of emotions comprised of a set of “characteristic property clusters”. The search for emotion-specific concordance – a unique combination of physiological, behavioral, and cognitive components for each “natural kind” of emotion – has been a fool’s errand. Instead, “[r]ather than beginning with an abstract, theoretical construct (e.g., anger) that we try to identify in human behavior, perhaps we could concentrate our empirical efforts on identifying which observables (e.g., cardiovascular changes, facial expressions, startle responses, electroencephalographic recordings, subjective experience, conscious thoughts) are implicated across instances of emoting and observe, rather than prescribe, their relationships in varying circumstances and time frames.” (Barrett, 2006, p. 48). Thus, from this perspective concordance is still seen as important, yet only as a bottom-up process through which we can discover functional combinations via inductive rather than deductive inquiry. This bottom-up approach has also been advocated by emergent accounts of emotion (e.g., Lewis, 2005). Coan (2010), for example, makes a compelling argument that there has been a problematic reliance on latent variable approaches for the examination of what is generally agreed is an emergent process. With a latent approach, indicators of emotions (e.g., physiological, cognitive, behavioral) all reflect an underlying emotion process and are reasonably interchangeable. The conceptual underpinning of such an approach is
that there is a latent process, emotion, which is manifest in various ways in body, behavior, and felt experience. In contrast, and more consistent with theoretical claims, emergent approaches model these components as interacting elements in a dynamic system from which emotion arises (Coan, 2010; Lewis, 2005). Thus, one reason why evidence for concordance has been inconsistent could be the traditional application of latent models for a putatively emergent process. It also makes a difference which components of the emotion system are selected for tests of concordance. For the vast majority of investigations, this is done with estimates of paired associations (e.g., correlations). With these pairings, associations between self-reported experience and behavioral expression have been the strongest, while pairings that include physiological variables have been the most inconsistent (e.g., Fischer & Roseman, 2007; Mauss et al., 2005; also see Evers et al., 2014). A second kind of pairing is across various physiological measures (Bulteel et al., 2014; Gentsch et al., 2014), which has yielded the full spectrum of results: negative, positive, and null (Kreibig, Wilhelm, Roth, & Gross, 2007; Mauss et al., 2005). At least two issues stem from this component pairing approach. First, the reliance on paired associations for what is, at minimum, a three-component process (e.g., physiology, appraisals, behavior) reflects methodological limitations rather than a strong theoretical prediction that concordance should be bivariate (Bulteel et al., 2014; Lanteigne et al., 2012). Second, it could be argued that associations within a particular domain of emotion components, such as physiology, do not really capture the spirit of the concordance question by excluding the experiential, cognitive, or behavioral aspects of emotional response. Another question is whether concordance should occur in the same way for all situations. First, as argued by Evers et al. (2014), there may be at least two levels of processing which would reflect different possibilities for concordance. Rapid, automatic concordance may not be functionally comparable to reflective processes that occur at longer time scales. Second, the means by which emotions are elicited may be important. Receptive or passive experience of emotional content (e.g., films) is often asocial and can be contrasted to active, social or generative experiences that induce emotional arousal. Finally, there are diverse ways to operationalize concordance. For example, the overall pattern of responsivity across domains captures a different aspect of concordance than the relative synchrony of dynamic processes (Bulteel et al., 2014). Moderators. Another set of reasons for why concordance has been elusive is the relative neglect of important moderators of emotion processes. For example, because emotions are situationspecific adaptations, context may be a focal rather than peripheral aspect of concordance. The Ortony, Clore, and Collings (OCC) model (Clore & Ortony, 2013; Ortony, Clore, & Collins, 1988), for example, asserts that emotions cohere around situations rather than just being constrained by context. Thus, the missing ingredient in the list of emotion components is the situation itself and the relative neglect of this ingredient is partly responsible for limited evidence in support of concordance. As argued by Butler et al. (2014), the concordance problem may stem from the relative neglect of regulatory processes in emotion theory and research. With the inclusion of neural processes into modern accounts of emotions, the separation of emotional processes from cognition or regulation has become untenable (Lewis, 2005; Thompson, Lewis, & Calkins, 2008). That is, at no point during an emotional process is regulation not occurring. Emotion regulation covers a wide array of processes and most of these target specific emotion components over others (e.g., suppression of expression, re-appraisal, relaxation to modulate physiological arousal). More generally, the down-regulation of emotion is the top-down, negative feedback counterpart to the
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bottom-up, positive feedback (i.e., emergent) processes that give rise to a concordant emotional response. This could explain why concordance would be more evident at greater intensities when regulatory processes are temporarily overwhelmed. Furthermore, when emotion regulation processes are compromised, such as in dysregulated clinical populations or through experimental manipulation, greater concordance among emotion system components would be expected. Thus, a question that emerges in this special issue is whether regulatory dynamics (e.g., the ebb and flow of RSA) are part of the concordance process postulated by theory (Crowell et al., 2014) or, as Butler et al. (2014) argue, whether regulation interferes with concordance. Theoretically, the concordance postulate is that some form of coordination across components of the emotion system universally defines emotion. However, individual differences certainly have an impact on the degree to which concordance can be observed. Cultural norms and socialization direct the which, where, when, how, and with whom of emotional expressivity (Ekman, 1973; Cole & Tamang, 1998; Matsumoto, Yoo, & Fontaine, 2008). Physiological responsivity, especially in the autonomic and cardiac systems, varies as a function of physical fitness and health (Salmon, 2001; Schlicht, 1994). Self-reports and appraisals also vary as a function of temperament, life-history, and culture (Kuppens & Tong, 2010; Scherer, 1997). These factors complicate the assessment of concordance. Despite the poor evidentiary record, concordance has not fallen out of theoretical favor. Why? Perhaps the intuitive appeal of concordance motivates resistance to revising models of emotion based on a dubious collection of findings. While theoretical parsimony and potential moderators are no doubt part of the problem, most researchers seem to be holding off on radical revisions to theory in lieu of more concentrated and sophisticated efforts to adequately model concordance. This jury-is-still-out perspective reflects the gap between theoretically rich models and an uncertain and limited set of methodological techniques to test these claims (Richters, 1997). Indeed, most recent considerations of concordance place criticism on inadequate methods, which is why we discuss methods in more detail below and have assembled a variety of methodological approaches for this special issue. Methods. The remaining reasons for limited support for concordance are methodological. First, the failure to detect concordance may come from failures to adequately elicit specific emotions in the lab. A recent special issue in this journal explored this possibility by demonstrating emotion-specific physiological response patterns (Friedman & Kreibig, 2010; Stephens, Christie, & Friedman, 2010). Moreover, as Friedman, Stephens, & Thayer (2014) suggest, basic, core emotions may evoke greater concordance than less canonical or universal emotional states. The large variety of emotional elicitation paradigms, even for one emotional state, and diversity of analytical techniques has so far made assessments of emotionspecific concordance inconclusive. Second, the common conceptualization of concordance is that of a positive feedback process in which physiological, cognitive, and expressive components mutually amplify each other to form emotional states. Because emotional states reach a finite zenith before eventually resolving into less intense or neutral states, there must also be negative feedback processes (e.g., regulation) that counteract the positive feedback processes. These positive-negative feedback loops are the bedrock of biological functioning and are by their very nature not linear. These non-linearities manifest as threshold effects, for example, such as those captured by catastrophe models (Guastello, 2013). Thus, linear statistics and models might not be the best approach for capturing the non-linearity of emotional concordance. Another problem that has been frequently identified is the issue with using between-subjects approaches to a within-subject
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problem (Reisenzein, 2000). At the simplest level this would entail favoring within-subject correlations and eschewing betweensubject approaches (see Butler et al., 2014 for an extensive discussion). Fourth, the general prediction is that concordance should increase with intensity (Davidson, 1992; Mauss et al., 2005; Rosenberg & Ekman, 1997). By extension, full concordance may only be possible in extreme circumstances (e.g., fear in a violent, life-threatening moment). Modern challenges are typically less dire than the environmental pressures for which emotions evolved, thus concordance may be the exception rather than rule (Friedman et al., 2014). Hence, ethical constraints and experimental reductionism may also be a factor in limiting assessment of concordance. Fifth, in emotion research, it is most common to use a stimulus onset as a synchronizing point for psychophysiological, expressive, and appraisal components. However, the time course of emotion components may vary greatly and therefore synchronized changes in two or more time series may not be simultaneous. For example, to address 2014, some recent studies have used windows of 6-10 second lags within which to find the maximum correlation between components (Butler et al., 2014; Dan-Glauser & Gross, 2013). Whatever the solution, it is probable that analyses based on simultaneous changes across components will produce attenuated indices of concordance. Finally, the diverse nature of physiological measures and their putative psychological meaning make it difficult to generalize about what would constitute evidence of concordance. As can be seen in the wide range of measures used in the studies in this special issue, there are important functional differences in neural, autonomic, muscular, and endocrine processes that must be factored in. For example, as shown by Crowell et al. (2014), concordance with RSA is complex due to the nature of parasympathetic withdrawal. This withdrawal indicates regulatory effort but also enables greater sympathetic arousal, which in combination could obscure clear interpretation of concordance among system components. Thus, temporally linked divergence of emotion processes may need to be added to conceptualizations of emotion concordance.
4. This special issue For this special issue, we have assembled contributions that reflect diverse approaches to the issue of emotional concordance. Table 1 summarizes the experimental context, emotions, measures, analytical techniques, and support for concordance for each of the novel empirical contributions. Each one addresses at least one of the issues mentioned above. Bulteel et al., propose a new methodology that is particularly well-suited to the detection of both pattern and synchrony across multiple measures. Butler et al., test how efforts to regulate emotions might interfere with concordant processes. Crowell et al. investigate how physiological regulation (RSA) and behavior may be concordant within and between individuals. Evers et al. test a dual process model that distinguishes between automatic and reflective processes. Friedman et al. use redundancy analysis to estimate the degree of shared variance across various measures of emotional responses to evocative films. Gentsch et al. explore the concordance across two physiological systems, facial muscles and event-related potentials, as a test of the component process model. Schaefer et al. provide some evidence that the intensity of emotional reactivity may be a factor related to concordance. Finally, the theoretical contribution of Quigley and Barrett (2014) caps off this special issue to complete the set of attempts to take the problem of concordance seriously and tackle it head on. Concordance is an intuitively appealing concept but one that is fraught with theoretical and methodological issues. We hope that this collection inspires and focuses future research, ultimately
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Table 1 Summary of empirical contributions to the special issue. Experimental design
Emotion(s) elicited
Measures
Analysis
Support for concordance?
Bulteel et al.
Pleasant IAPS pictures
Unspecified positive
IBI; SCL; EMG
De-Con (new technique for assessing concordance)
Butler et al.
Discussion of upsetting film; suppression, reappraisal and control conditions
Unspecified negative-positive
IBI; SCL; BP; video self-report; observed verbal/non-verbal expression
Crowell et al.
Depressed and self-injuring adolescents & controls; mother-adolescent conflict discussion Interrupted counting task; lexical-decision task; anger self-report
Observed aversiveness
RSA and observed aversiveness of both dyad members
Multivariate multilevel model of auto-/crosscorrelations (max within ± 6 second window) Two-level actor-partner interaction model
General support for patterning and synchronization concordance; notable individual differences Max cross-correlation = |.3| in control condition; evidence that regulation disrupts concordance
Anger
Friedman et al.
Music and film clips
Content, amused, fearful, angry, sad & neutral
Gentsch et al.
Feedback during monetary gambling task
Schaefer et al.
Video clips of snakes (threatening and non-threatening) and fish; fMRI; snake phobics & controls
Unspecified (appraisals of goal conduciveness and power) Fear
Automatic: anger accessibility in lexical task; Reflective: self-reported anger; MAP IBI; RSA; PEP; RR; MAP; SCL; SBP; DBP; LVET; SV; CO; TPR;TI; TE; self-report of 6 emotions ERP and EMG
Evers et al.
Pupil diameter; SCL; self-reported valence and arousal; voxel activation
Within-individual concordance for clinical group; between-individual concordance for controls
Multiple regression
Within-system (automatic or reflective) but not between-system concordance
Redundancy analysis
Up to 28% shared variance (canonical r = .53)
Principal components analysis
ERPs (appraisals) loaded with EMG in expected directions
ANOVAs and chi-square
Phobics had greater concordance in threatening snake condition compared to controls
Note: IBI = interbeat interval; SCL = skin conductance level; EMG = electromyography; BP = blood pressure; RSA = respiratory sinus arrhythmia; MAP = mean arterial pressure; PEP = pre-ejection period; RR = R-to-R interval; SBP = systolic blood pressure; DBP = diastolic blood pressure; LVET = left ventricular ejection time; SV = stroke volume; CO = cardiac output; TPR = total peripheral resistance; TI = inspiration time; TE = expiration time.
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