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Withdrawal Motivation and Empathy: Do Empathic Reactions Reflect the Motivation to
“Reach Out” or the Motivation to “Get Out”?
by
Alexa Mary Tullett
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Department of Psychology University of Toronto
© Copyright by Alexa Mary Tullett, 2012
ii
Withdrawal Motivation and Empathy: Do Empathic Reactions Reflect the Motivation to
“Reach Out” or the Motivation to “Get Out”?
Alexa Mary Tullett
Doctor of Philosophy
Department of Psychology
University of Toronto
2012
Abstract
Evolutionary accounts of empathy often focus on the ways in which empathy-motivated
helping can give rise to indirect fitness benefits. These accounts posit that empathy is
adaptive insofar as it motivates strategic helping behavior, but they neglect a key feature
of the empathic process – it can prepare one to act effectively within a shared
environment. In particular, adopting the affective and motivational states of others
provides a rapid and automatic way to avoid danger and threat, which play a
disproportionately large role in shaping behavior. Based on the idea that empathic
processes facilitate adaptive reactions to threat, I conducted four experiments to test the
hypothesis that empathic reactions reflect withdrawal motivation. In the first experiment I
used electroencephalography (EEG) to measure baseline right-frontal cortical asymmetry,
a reliable neural correlate of withdrawal motivation. I then assessed empathic reactions to
images of children ostensibly taken from a charity campaign. Participants who showed
greater right-frontal cortical asymmetry also showed stronger empathic reactions to the
images. In the second study I used self-report measures fear and anger to assess
dispositional withdrawal- and approach-motivation, respectively. This time, participants
indicated their empathic reactions to targets experiencing happiness and targets
iii
experiencing sadness. Empathy for both types of targets was positively related to fear and
negatively related to physical aggression, again supporting a link between empathy and
withdrawal motivation. In the third study I measured state withdrawal motivation by
using facial electromyography (EMG) to assess disgust expressions towards charity
images. These expressions were positively correlated with empathic reactions,
demonstrating that state withdrawal motivation is also positively related to empathy. In
the final study I manipulated approach and withdrawal emotions by having participants
make emotional facial expressions. Focusing on fear and anger, I found that participants
were more empathic when making fearful faces than when making angry faces, although
these results must be interpreted with caution, as the manipulation may not have had the
intended effects on emotional state. Taken together, these four studies provide
converging evidence of an association between withdrawal motivation and empathy,
supporting the idea that empathy plays a role in the adaptive response to threat.
iv
Acknowledgments
I will forever be grateful to my advisor, Michael Inzlicht, for making me feel like his
confidence in me is unwavering. My most inspiring moments have been moments spent
with him, discussing ideas. I would like to thank Elizabeth Page-Gould for her
unrelenting generosity with both her wisdom and her kindness. I would also like to thank
Jason Plaks for selflessly sharing his insight and enthusiasm. My labmates, Jenny Gutsell,
Rimma Teper, and Shona Tritt have made my life happy on a daily basis, and I still
marvel at how fortunate I have been to share the last five years with them. My family
outside of the lab has been a source of unending encouragement, and I am so lucky to
have their unconditional support. Sonia Kang and Jacob Hirsh have shown me what it
means to be brilliant academics and wonderful people, and I will continue to aspire to the
example they have set. On a daily basis I have turned to my friends Andrea Schofield and
Andrée-Ann Cyr for advice and perspective, and my work and life would be severely
impoverished without them. I am thankful to Lasana Harris and Eddie Harmon-Jones for
teaching me skills I didn’t have, and for being inspiring examples of creative scientific
minds. I will always look to Simine Vazire as a reminder of the kind of person you can be
if you let go of the things that limit your thinking, and use what you have to make other
people happy. I am grateful to Nicholas Rule, Adam Anderson, Wil Cunningham, and
Jan Wacker for generously offering their time and expertise in helping me complete this
dissertation. Finally, I would like to express my gratitude to the SPA area and the
Psychology Department at the University of Toronto for creating an environment that
fosters excitement and curiosity.
v
Table of Contents Chapter 1: General Introduction ......................................................................................... 1
1 Objectives ................................................................................................................ 1
2 What Is Empathy? .................................................................................................... 2
3 Empathy, Emotion, and Motivation ......................................................................... 7
4 Why Does Empathy Exist? .................................................................................... 11
5 Summary ................................................................................................................ 16
Chapter 2: Frontal Cortical Asymmetry and Empathy ..................................................... 17
1 Introduction ............................................................................................................ 17
2 Methods.................................................................................................................. 19
3. Results .................................................................................................................... 21
4. Discussion .............................................................................................................. 22
Chapter 3: Individual Differences in Withdrawal-Related Affect and Empathy .............. 26
1 Introduction ............................................................................................................ 26
2 Method ................................................................................................................... 28
3 Results .................................................................................................................... 30
4 Discussion .............................................................................................................. 32
Chapter 4: Levator Labii and Corrugator Supercilii Activity and Empathy ..................... 35
1 Introduction ............................................................................................................ 35
2 Method ................................................................................................................... 36
3 Results .................................................................................................................... 38
4 Discussion .............................................................................................................. 41
Chapter 5: Approach and Withdrawal Facial Expressions and Empathy ......................... 43
1 Introduction ............................................................................................................ 43
2 Method ................................................................................................................... 44
3 Results .................................................................................................................... 45
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4 Discussion .............................................................................................................. 47
Chapter 6: General Discussion .......................................................................................... 49
1 Summary ................................................................................................................ 49
2 Limitations ............................................................................................................. 51
3 Future Directions ................................................................................................... 53
4 Conclusion ............................................................................................................. 55
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List of Tables
Table 1. Means and standard deviations for emotion intensity ratings of the images
Table 2. Reliabilities and descriptive statistics for key variables
Table 3. Bivariate correlations between key variables
Table 4. Predicting empathic concern and empathic contagion from emotional disposition
Table 5. Means and SDs for levator labii and corrugator supercilli EMG in response to
images
Table 6. Bivariate correlations between key variables for suffering charity images
Table 7. Bivariate correlations between key variables for non-suffering charity images
Table 8. Results of mediated moderation analysis
viii
List of Figures
Figure 1. Head map of asymmetry scores [Log(Right) – Log(Left)]. High and low
empathizers are identified based on a tertiary split of empathic concern scores. Red
values indicate greater activity in the left vs. right hemisphere, while blue values indicate
greater activity in the right vs. left hemisphere.
Figure 2. A mediation model depicting the relationship between frontal EEG asymmetry
and empathic concern with sadness as a mediator; c is the total effect of frontal EEG
asymmetry on empathic concern and c’ is the direct effect of frontal EEG asymmetry on
empathic concern. Negative values for a and c paths indicate a positive relationship
between right-frontal EEG asymmetry and the relevant variables. Unstandardized
regression coefficients from a bootstrap procedure are provided along with their
associated standard errors. ** p < .01, * p < .05.
Figure 3. Scatterplots showing the relationships between: a) frontal EEG symmetry and
empathic concern, b) frontal EEG asymmetry and sadness, and c) sadness and empathic
concern. Negative slopes represent a positive relationship between right-frontal EEG
asymmetry and the relevant variables.
Figure 4. An example of a) a suffering image and b) a non-suffering image.
Figure 5. Empathic concern ratings as a function of facial movement condition.
ix
List of Appendices
Appendix A. Facial movement instructions
1
Chapter 1: General Introduction
1 Objectives Typically, when empathy is examined for its adaptive value or evolutionary significance,
researchers focus on how the consequences for the target of empathy might, in an indirect
way, benefit the empathizer. Reciprocal altruism and kin selection accounts posit that
empathy encourages people to help others when it benefits the self, either through
reciprocity or through the proliferation of shared genes (Batson, Lishner, Cook, &
Sawyer, 2008; de Waal, 2008; Hamilton, 1964; Trivers, 1971). Related accounts suggest
that empathy can contribute to group-level fitness via the evocation of helping behaviors
(Henrich, 2004). Common across these accounts is the hypothesis that empathy is
adaptive for the individual because it motivates helping behaviors that have indirect
fitness benefits. Absent from these accounts, however, is the consideration of the
possibility that empathy may stem from motivational systems completely separate from
prosociality; perhaps empathy is driven, at a basic level, by the motivation to escape
dangerous situations signaled by the emotional reactions of others.
The overall aim of this dissertation is to answer the following question: Do feelings of
empathy reflect the motivation to avoid dangerous or threatening situations? In other
words, is empathy associated with withdrawal motivation? If empathy serves as an
adaptive warning signal in the face of indications of danger or threat, empathy should be
associated with the motivation to escape, and should thus be linked to withdrawal
motivation. This overarching prediction leads to three specific hypotheses that will be the
focus of the studies described herein:
Hypothesis 1. Dispositional withdrawal motivation should be associated with empathy.
Hypothesis 2. Empathy should co-occur with withdrawal-related emotions.
Hypothesis 3. Experimentally increasing withdrawal-related emotions should increase
empathic responding.
2
The first of these hypotheses will be addressed in Studies 1 and 2. Study 1 will explore
the relationship between baseline right-frontal EEG asymmetry, a neural correlate of
dispositional withdrawal motivation (Davidson, Ekman, Saron, Clifford, Senulis, &
Frisen, 1990; Harmon-Jones & Allen, 1998), and empathic responding. Then, in Study 2,
I will examine the relationship between empathic responding and the dispositional
tendency to experience approach- vs. withdrawal-related affect, focusing specifically on
the emotions of anger and fear (Stemmler, Aue, & Wacker, 2007; Wacker, Heldmann, &
Stemmler, 2003). The second hypothesis will be addressed in Study 3, in which I will use
facial EMG to see whether empathic responding is correlated with naturally occurring
withdrawal-related facial expressions. Finally, I will address the third hypothesis in Study
4 by experimentally manipulating approach and withdrawal facial expressions, and
observing the consequences for empathic reactions.
2 What Is Empathy? Because empathy, as a subject of psychological study, is a particularly heterogeneous
construct, it is important to start with a working definition. Here I will adopt the
relatively broad definition of empathy provided by Preston and de Waal (2002) who
stated that empathy is “any process where the attended perception of the object’s state
generates a state in the subject that is more applicable to the object’s state or situation
than to the subject’s own prior state or situation” (p. 4). While there are important sub-
divisions to be made within this umbrella definition (as will be discussed shortly), this
definition has the advantage of acknowledging all (or almost all) of the frameworks that
people have used to conceptualize and to study empathic processes.
Historically, empathy has been divided into dichotomies based on various dimensions, all
of which have utility depending on the particular behaviors or physiological reactions that
are the focus of explanation. Increasingly, however, there is neural evidence to suggest
that there are two critical – and largely distinct – ways in which people gather
information about the thoughts, intentions, and emotions of other people (Decety &
Lamm, 2006; Singer & Lamm, 2009). The first, which I will refer to as “bottom-up,”
involves understanding another person’s affective or mental states by actually
experiencing them (or impoverished versions of them) for oneself. The second, which I
3
will refer to as “top-down,” involves making inferences about another person’s
experiences by applying one’s personally derived ideas about how a given context should
influence a given individual. It should be noted that either of these processes could lead
to an emotional feeling of concern. For instance, after watching someone burn his or her
hand, one might feel concerned as a consequence simulating the pain, or as a
consequence of reasoning that the experience must have been painful. Despite the
possibility of a common outcome, these two processes are clearly distinguishable and can
usefully be conceptualized as separate.
2.1 Bottom-Up Empathic Processes
Wegner (1980) has posited that empathy may “stem in part from a basic confusion
between ourselves and others” (p. 133), while others understand empathy as an
“emotional signal of oneness” (Cialdini, Brown, Lewis, Luce, & Neuberg, 1997, p. 481).
In line with these definitions, simulation theory proposes that empathy is rooted in the
ability to internally simulate the emotional states of other (Carruthers & Smith, 1996;
Davies & Stone, 1995a; 1995b; Goldman, 2006; Preston & de Waal, 2002). This account
is supported by evidence that common neural regions subserve both the expression and
observation of emotional states such as disgust or pain (Jackson, Meltzoff, & Decety,
2005; Singer et al., 2004; Wicker et al., 2003). Generally, simulation is conceptualized as
a bottom-up process in which one “catches” the emotions, or even actions, of another
person through a process of mimicry (Gutsell & Inzlicht, 2010; in press; Preston & De
Waal, 2002). At least in the initial stages, this process results in the empathizer’s
experience matching that of the target – feeling sadness towards someone who is sad, or
adopting an angry facial expression in reaction to someone who is expressing anger –
with cognitive elaboration and self-other distinctions occurring later.
Perception action mechanism
One potential mechanism for achieving a match between our internal representations and
those of others’ is provided by the idea of a perception-action mechanism. It has been
suggested that the human nervous system is characterized by a perception-action
4
organization wherein the same neural representations are used to code perceptions and
their associated actions (Preston & de Waal, 2002; Prinz, 1987). Evidence for this idea
comes from experiments that show that perceiving a given stimulus facilitates the
execution of compatible actions, and inhibits the execution of incompatible actions
(Prinz, 1997). For instance, choice reaction times are faster when response-keys
correspond to the spatial arrangement of the stimuli, compared to when they do not
correspond (Kornblum, Hasbroucq, & Osman, 1990). This type of organization is
particularly useful in that it facilitates rapid pairing between observations and actions. For
instance, if the same neural circuits are used to perceive an oncoming projectile and to
execute a “ducking response,” this could have clear adaptive consequences compared to
the alternative, which would involve the time-consuming transfer of information.
According to the Russian Doll model of empathy (de Waal, 2008), this perception-action
mechanism underlies the most basic form of empathy – emotional contagion, or catching
the emotions of others. Specifically, this model states that emotional contagion is
accomplished by the automatic activation of neural representations consistent with the
feelings of another person. One example of emotional contagion is personal distress, the
self-oriented negative affect people experience when they are exposed to the suffering of
others. This fundamental process of emotional contagion sets the stage for more complex
types of empathy such as empathic concern (also called sympathetic concern) – an
empathic reaction that requires distinguishing between internally and externally
generated emotions.
Mirror neurons
Consistent with the idea of a perception-action organization of the nervous system, it has
recently been discovered that the human nervous system contains mirror neurons –
neurons that are active during both the execution of an action, and the observation of
another person performing the action (Pellegrino, Fadiga, Fogassi, Gallese, & Rizzolatti,
1992; Mukamel, Ekstrom, Kaplan, Iacobini, & Fried, 2010). These neurons, which
comprise part of the premotor cortex, might play a key role in imitation learning
(Jeannerod, 1994; Rizzolatti & Craighero, 2004), and action understanding (Rizzolatti &
5
Craighero, 2004). Moreover, neural regions associated with emotional experiences like
pain and disgust have been found to demonstrate similar mirroring properties, showing
activity during both the observation and experience of these sensations (Jackson et al.,
2004; Singer et al., 2004; Wicker et al., 2003). The discovery of brain areas, and even
specific neurons, that are active both when people observe someone else’s experiences
and when they live those experiences themselves suggest a neural mechanism for the
simulation account of empathy. Furthermore, it suggests that simulation may be partly
contingent on the degree of shared characteristics and experiences between empathizer
and target (Preston & de Waal, 2002; Gutsell & Inzlicht, 2010).
2.2 Top-Down Empathic Processes
Whereas simulation theory suggests that we understand other people by sharing their
experiences in a bottom-up fashion, an alternative possibility is that understanding others
is a top-down process rooted in a cognitive understanding of how other minds work.
According to top-down accounts of empathic processes, humans have ways of inferring
the experiences of other people by deliberately evaluating their likely emotional or
mental state based on lay-psychological theories, personal experience, and context.
Theory-theory
Theory-theory proposes that people use their mental models of the world in order to make
inferences about how other people think, and feel (Carruthers, 1996; Gopnik & Meltzoff,
1997). An example of the mental steps involved in this process might be: people are
generally afraid of snakes, therefore if a person sees a snake, they must be experiencing
fear. This account can be clearly differentiated from simulation accounts, which would
propose that an individual would infer another person’s fear by experiencing the fear
themselves in an automatic, bottom-up fashion. Theory-theory also differs from
simulation theory in allowing for situations in which a person’s emotional reaction is
incongruent with the person they are observing – for instance, when a person defeats a
friend at chess, they can recognize the negative emotions of the friend while experiencing
the positive emotions associated with victory (Carruthers, 1996). In general, theory-
6
theory frames empathic processes as a problem-solving task in which people take into
account personal experience and contextual variables, along with their beliefs about the
world, to help them determine the likely emotional experience of another person.
Theory of mind
In order to be able to accurately infer the contents of other people’s minds, a person must
first have an understanding that others’ minds can be different than their own. The ability
to make this distinction, and to consider the contents of another person’s mind, has been
labeled theory of mind (ToM). Historically, theory of mind abilities are assessed using
false-belief tasks – that is, tasks that require the participant to recognize that another
person can have a belief that is inconsistent with what the participant knows about the
situation (Flavell & Miller, 1998; Wellman, Cross, & Watson, 2001). Whereas healthy
adults make this type of inference with ease, children under the age of three and people
with autism show impairments on these tasks (Wellman et al., 2001; Baron-Cohen,
1995). Recent evidence regarding the neural correlates of ToM suggests that inferring the
mental states of others relies on neural regions, particularly the medial pre-frontal cortex
(mPFC), that are involved in thinking about our own mental states (Amodio & Frith,
2006; Gallagher & Frith, 2003; Macrae et al. 2004). Further research demonstrates that
there are other regions that distinguish between thinking about the self and others (Siegal
& Varley, 2002; Vogeley et al., 2001).
Neuroscientific investigations of ToM have also demonstrated that right frontal regions
appear to play a larger role in ToM abilities than do left frontal regions. Stuss, Gallup,
and Alexander (2001) found that patients with right-frontal lesions showed impaired
performance on ToM tasks compared to patients with left-frontal or non-frontal lesions.
Similarly, a PET imaging study revealed that non-verbal ToM tasks produced increases
in activation over right mPFC, but not over left mPFC (Brunet, Sarfati, Hardy-Baylé, &
Decety, 2000). As will be discussed in more detail in Chapter 1, relatively greater activity
in the right vs. left prefrontal cortex is also associated with withdrawal motivation (Coan
& Allen, 2003; Davidson, 1995; Harmon-Jones, 2004; Harmon-Jones, Gable, & Peterson,
2010; van Honk & Schutter, 2006). Thus, the ability to distinguish the mental states of
7
self and other may be reflected in patterns of neural activation that are also neural
correlates of withdrawal motivation.
In a review of imaging and lesion studies, Siegal and Varley (2002) conclude that there is
a core neural network, centered on the amygdala circuitry, which is dedicated to the
computation of mental states. The amygdala has been shown to play a key role in threat
responses to outgroup members (Cunningham, Johnson, et al., 2004; Phelps et al., 2000;
Richeson, Todd, Trawalter, & Baird, 2003; Harris & Fiske, 2006), and also in the
development and expression of conditioned fear (Baron-Cohen et al., 2000; Davis, 1992;
Phillips & LeDoux, 1992). Expanding on conceptualizations of the amygdala as a fear
center, further work has provided convincing evidence that the amygdala may play a
broader role in evaluating emotional intensity, regardless of valence (Adolphs, 1999;
Cunningham, Raye, & Johnson, 2004). Taken together, these findings suggest that
impairments in ToM may, to some extent, reflect impairments in emotional processing.
2.3 When Top-Down Meets Bottom-Up
Simulation and theory-theory are often presented as competing accounts of how people
come to understand others. There is substantial evidence, however, that one of these
theories in isolation would fall short of accounting for the range of human empathic
behavior. These two processes are both well-represented in the repertoire of human
behavior, and, although distinguishable, are to some extent overlapping and reciprocal. In
one experiment, Jenkins, Macrae, and Mitchell (2008) provided convincing evidence that
there are neurons in the ventromedial prefrontal cortex (vmPFC) that are involved in
considering the mental states of both the self and others. This process of mental state
simulation is influenced by top-down processes like perspective-taking (Ames, Jenkins,
Banaji, & Mitchell, 2008). Perspective-taking has also been shown to produce increases
in an even more basic form of simulation – motor resonance (Gutsell & Inzlicht, 2012).
Thus, humans appear to have two distinct but interacting ways of coming to understand
their social world, and a comprehensive account of empathy must acknowledge both.
3 Empathy, Emotion, and Motivation
8
Examining empathy using the frameworks provided by theories of emotion and
motivation can help to shed light on the underlying nature of the empathic response.
Because empathy almost always involves emotion, (except, perhaps, in some cases of
inferring mental states or beliefs that have little emotional content), an understanding of
the empathic process rests on an understanding of emotion. Depending on the theory of
emotion that one adopts, empathic emotions could be considered an important driving
force in human behavior or epiphenomena that are uninformative in isolation.
Furthermore, the taxonomy one uses to describe emotional processes has important
consequences for the way that we interpret both the function of emotion and the
relationships between basic emotions and other phenomena. For reasons outlined below,
we will adopt the view that emotions are functional, and that they are key components of
the basic motivational processes of approach and withdrawal (Frijda, Kuipers, & ter
Schure, 1989).
3.1 Theories of Emotion
One of the oldest debates in the history of emotion research centers around the function,
or lack of function, of emotional experience. Any discussion of the motivational nature of
empathic emotion rests on the assumption that emotion is functional, and at an even more
basic level, that emotion affects behavior. At face value such assumptions may appear
uncontroversial, but a glance at the psychological and philosophical literature shows that
this is not the case.
Emotions are epiphenomenal
Proponents of ‘epiphenomenal’ theories of emotion propose that the experience of pain,
or joy, is a byproduct of processes that guide and shape behavior. According to these
theories, the subjective experience of emotion has no capacity to effect downstream
changes in behavior – motivational processes are thought to occur independently, and
emotion is seen simply as a correlate of these more fundamental forces (LeDoux, 1996).
Evidence in support of this conceptualization comes from studies that have revealed
stimulus-response pathways that bypass neocortical regions – the regions associated with
9
conscious experience (LeDoux 1986; Pickard & Silverman, 1981). These findings
demonstrate that it is possible for an organism to respond in a motivated fashion without
(or before) the conscious experience of emotion. Supporters of this view have also
suggested that motivated behavior in non-human animals provides evidence for the
epiphenomenal nature of emotion (LeDoux, 1996). This reasoning rests on the
assumption that motivated behavior in animals occurs in the absence of emotion, a claim
that has been contested by researchers who suggest that conscious and unconscious
emotional processes are an intrinsic aspect of motivated behavior in non-human animals,
and perhaps other vertebrates (Panksepp, 2009; Winkielman & Berridge, 2004).
Emotions are functional
In contrast to the epiphenomenal accounts discussed above, many researchers have
proposed that emotions have functions, and indeed that these functions may be adaptive
for the organism (Barrett & Campos, 1987; Darwin, 1872; Keltner & Gross, 1999).
Panksepp (1998; 2003) commented on the utility of thinking of emotions as “pressures”
or “drives,” noting that emotional and motivational processes emerged over time from
systems involved in basic action-generation. In general, theories that adopt this
perspective focus on the ways in which emotions may drive survival-relevant behaviors
such as avoiding threats, enforcing attachments, and encouraging cooperation (Ekman,
1992; Lazarus, 1991; Levenson, 1994; Oatley & Jenkins, 1992; Tooby & Cosmides,
1990). Far from epiphenomena, emotions are thought to provide an “intelligent interface
that mediates between input and output” (Scherer, 1994, p. 127). This perspective on
emotion has similar implications for emotion generated via empathic processes; empathic
emotion may drive adaptive behaviors in a sort of “second-hand” response to the
environment.
In order to identify the functions of emotions, including empathic emotions, one must
determine useful ways by which to characterize emotions with respect to their functional
outcomes. One possibility is that there are various discrete emotions, each with its own
physiological fingerprint, as well as its own function (Janig, 2003; Levenson, 2003;
Stemmler, 1992). To date, however, researchers have had mixed success in attempts to
10
characterize these physiological and psychological fingerprints, leading to some
skepticism about this approach (Cacioppo, Berntson, Larsen, Poehlmann, & Ito, 2000).
Alternatively, others have attempted to characterize emotions along a relevant dimension
(or dimensions), and to examine the functional consequences at different points along the
continuum. Taking this approach, a substantial amount of emotion research has focused
on the dimension of valence, suggesting that the distinction between positive and
negative has implications for the cognitive and behavioral outcomes of an emotion (Lang,
1995; Taylor, 1991; Watson, 2000). For instance, it has been proposed that positive affect
indicates a safe and comfortable environment, allowing for an expansion of cognitive and
attentional resources, while negative affect does the opposite (Frederickson, 2001). More
recently, researchers have begun to propose that the dimensions of motivational intensity
and direction may provide a more useful framework for capturing variance in the
functional significance of emotions (Harmon-Jones & Gable, 2008).
A motivational perspective on emotions
In contrast to the valence approach, the motivational direction account suggests that the
most basic function of emotion is to motivate people to do one of two things: to withdraw
from a stimulus or to approach a stimulus (Davidson, 1993). Thus, empathic emotion
should serve this same function. Withdrawal motivation ensures that we evade
punishment and threat, whereas approach motivation is what prompts us to pursue
desired goals and rewards (Gray & McNaughton, 2000; Sutton & Davidson, 1997). In a
performance context, withdrawal motivation stems from fear of failure and low
performance expectancies, while approach motivation stems from striving to succeed and
high performance expectancies (Elliot & Church, 1997). In a broad analysis of
personality and temperament, withdrawal motivation was linked to neuroticism, negative
emotionality, and the behavioral inhibition system (BIS) whereas approach motivation
was associated with extraversion, positive emotionality, and the behavioral activation
system (BAS; Elliot & Thrash, 2002).
By experimentally examining the consequences of motivational intensity and direction,
above and beyond the dimension of emotional valence, researchers have come to a more
11
comprehensive understanding of the functional qualities of emotions. For instance, high
approach positive affect is associated with pursuing reward, whereas low approach
positive affect is associated with obtaining reward (Knutson & Wimmer, 2007).
Furthermore, low approach positive affect is associated with broadened attention as
valence models have previously suggested, but high approach positive affect is associated
with narrowed attention relative to a neutral control conditions (Gable & Harmon-Jones,
2008; 2010). The dimension of motivational direction also appears to effectively
characterize differences in asymmetrical frontal cortical activation, a reliable neural
correlate of affective disposition (Harmon-Jones & Allen, 1997; 1998). Thus, the
dimensions of motivational direction and intensity may provide a useful way of
categorizing emotions according to their functional consequences.
Related to the concepts of approach and withdrawal, Gray and McNaughton have
provided detailed accounts of three fundamental neural systems of motivation (2000).
According to their model, known as reinforcement sensitivity theory, motivated behavior
is guided by the interaction of BAS, the fight/flight/freeze system (FFFS), and BIS. BAS
is associated with impulsivity and appetitive behaviors and is engaged by signals of
reward and non-punishment. FFFS is associated with defensive and escape behaviors and
is engaged by signals of punishment and non-reward. BIS, although originally thought to
be engaged by punishment cues (Gray, 1987), is now viewed as a conflict-detection
system, sensitive to competing signals of reward and punishment, and to reward-reward
and punishment-punishment conflicts. Integrating these systems with the motivational
constructs of approach and withdrawal is not always straightforward, but in the case of
withdrawal associated with escape/flight motivation, the FFFS is an obvious candidate
for the underlying neural substrate.
4 Why Does Empathy Exist? Given that there is a substantial amount of neural architecture devoted to simulating and
theorizing about the mental states of others, it makes sense to ask whether these processes
might have adaptive significance. Indeed, many researchers have suggested that empathy
is adaptive, and have proposed accounts of how empathy might augment evolutionary
fitness. Several of these accounts focus on an important behavioral correlate of empathy
12
– helping behavior. In general, these accounts propose that empathy is adaptive in that it
leads to helping behavior, which is in turn adaptive because it indirectly increases
individual fitness. An alternative possibility, however, is that empathy has direct fitness
benefits because it prepares the empathizer to act effectively within the current
environment – particularly in response to danger or threat.
4.1 Kin Selection and Reciprocal Altruism
Famously stating “I would lay down my life for two brothers or eight cousins,” Hamilton
(1964) formalized the idea that genes will become more common in the gene pool if they
cause people to behave in ways that benefit other carriers of those genes. The theory of
kin selection helped to solve one of the most puzzling problems faced by evolutionary
theorists: If success in the gene pool is determined solely be behaviors that increase one’s
own chances of survival and reproduction, why would anyone ever commit an action that
benefits another person at a cost to the self? According to kin selection, if one’s altruistic
actions benefit a person who is likely to share one’s own genes (for instance, a child, or a
sibling), this can have indirect fitness benefits for the altruist, thereby resolving the
paradox.
Extending this logic to empathy, it should be adaptive to be empathic if this leads one to
help others who are closely related. According to de Waal (2008), “This selection
pressure to evolve rapid emotional connectedness likely started in the context of parental
care long before our species evolved” (p. 282). Similarly, other researchers have
proposed that empathy reflects a “nurturance” tendency that spills over beyond one’s own
children to other vulnerable targets, including animals (Batson et al., 2005). Consistent
with the idea that empathy may promote adaptive helping of relatives, it has been shown
that manipulations of perceived similarity – a potential cue of relatedness – can augment
empathic responding (Batson, Turk, Shaw, & Klein, 1995; Krebs, 1975; Stotland, 1969).
Kin selection helps to solve the puzzle of altruistic behavior by revealing the hidden
selfishness behind seemingly selfless behavior. In a similar fashion, the idea of reciprocal
altruism proposes that some actions that seem altruistic, or selfless, are motivated by
13
expectation that the benefitted party return the favor (Trivers, 1971). Again, the
overarching idea is that empathy can be adaptive when it motivates people to help others
in a manner that will have indirect personal benefits. Thus, both kin selection and
reciprocal altruism accounts propose that empathy evolved as a proximate mechanism to
accomplish an ultimate goal – increasing one’s representation in the gene pool (de Waal,
2008).
4.2 For the Good of the Group
As Henrich (2004) has theorized, prosociality might also be adaptive when considered
through the lens of group selection. Although the term ‘group selection’ has become
taboo in some circles, convincing theoretical demonstrations have shown that natural
selection acting on genes can be partitioned into ‘group-level’ and ‘individual-level’
components (Price, 1970; 1972). At a basic level, this perspective suggests that groups
where high levels of prosociality and cooperation are the norm should have higher fitness
relative to other groups. Through processes of genetic and cultural evolution, these
behaviors can then proliferate within the larger population (Henrich, 2004). If empathy is
seen as the proximate cause of helping behavior (de Waal, 2008), a logical extension of
such accounts of prosociality is that empathy is adaptive because it is good for the group.
4.3 Empathy as a Second-Hand Response to the
Environment
The above accounts focus on the adaptive value of empathy as a motivator of helping
behavior, which is thought to provide fitness benefits both at the individual and group
levels. Absent from these accounts, however, is consideration of empathy’s roots in basic
processes of information gathering. The actions and emotions of others tell us about the
environment around us, and are often good indicators of the way we should react to a
given situation. Fundamental processes of mimicry and emotional contagion, thought to
be the psychological and neural building blocks of the empathic process, play a key role
in helping us to determine important facts about the environment. For instance, a person’s
14
fearful expression directed at something behind us, or their disgust expression directed at
something on our plate, could both provide important cues as to what we should do next.
Given that people’s emotional reactions facilitate adaptive behaviors (Barrett & Campos,
1987; Darwin, 1872; Keltner & Gross, 1999), it follows that simulating the emotional
states of others who share the same environmental context could serve the same function.
In other words, adopting another person’s emotional state should ready the observer for
effective interaction with their shared surroundings (Plutchik, 1980; 1990). If it is the
case that emotional contagion provides information, and not just the impetus to help, it
should occur in instances where another organism’s state is highly relevant, and it should
not always be accompanied by prosocial behaviors.
Perhaps the most important aspect of the environment is the presence of a threat (Rozin
& Royzman, 2001). As such, if emotional contagion provides information, humans and
other animals should show emotional contagion for the withdrawal-related threat
reactions of their conspecifics, without necessarily responding prosocially. Examples in
which one organism’s distress spreads to those around it – without generating prosocial
reactions – are well-documented. For instance, it has been shown that rats and pigeons
display distress in response to the perceived distress of a conspecific (Church, 1959).
Mice show an intensified pain response when they see other mice experiencing pain
(Langford et al., 2006). Human infants are more likely to start to cry if they are in the
same room as another crying infant (Hoffman, 1975; 1976). The basic process of
emotional contagion has clear adaptive implications – adopting the emotional reaction of
others is often a useful heuristic for operating within a shared environment.
It should be noted that, theoretically, it could be adaptive to adopt approach-related, as
well as withdrawal-related affect. If emotional contagion is subject to the same negativity
bias as the rest of human affective processes, however, it is likely that humans are more
efficient at simulating withdrawal-related, compared to approach-related, emotional
experiences (Rozin & Royzman, 2001). Evidence suggests that this is, indeed the case
(for a review see Vaish, Grossman, & Woodward, 2008). For instance, people show a
stronger contagion response to others’ bodily expressions of fear than to those of
15
happiness (de Gelder, Snyder, Greve, Gerard, & Hadjikhani, 2004), and infants have
stronger behavioral and neural reactions to adults’ expressions of fear compared to
happiness (Carver, Vaccaro, 2007; Mumme, Fernald, & Herrera, 1996). These findings
are consistent with the idea that emotional contagion is stronger for withdrawal-related
emotions because its function in signaling threat, compared to reward, is more critical to
survival.
Although empathic concern (usually measured by asking people to report feelings of
“warmth,” “compassion,” etc.) is distinguished from emotional contagion in that it
involves other-oriented emotions, the fact that this process relies, to some extent, on
phylogenetically older processes of emotional contagion suggests that it, too, may reflect
an adaptive distress reaction (de Waal, 2008). Put another way, when a person reports
feelings of compassion for another individual, these reports may reflect a relatively
primitive motivational system involved in reactions to threat, rather than a motivational
systems driving prosociality.
Distress-relief models, such as the negative-state relief model (Cialdini, Darby, &
Vincent, 1973) and the aversive-arousal reduction model (Piliavin, Dovidio, & Gaertner,
1981), embrace a similar conceptualization of empathic processes. These models posit
that feelings of concern towards the suffering of others simply reflect the contagion of
personal distress. Furthermore, helping behavior is thought of as a distress-regulation
strategy, rather than as a behavioral manifestation of prosocial emotions. In support of
these models, research has shown that when the negative emotions elicited by others’
suffering are alleviated by a reward or positive mood-induction, people help less
(Cialdini et al., 1987; Schaller & Cialdini, 1988). In some cases perceived self-other
overlap has been found to account for the connection between empathy and helping,
suggesting that empathy leads to helping when we adopt the distress of the victim
(Cialdini et al., 1997; Maner et al., 2002). Furthermore, recent work has demonstrated
that when people are faced with human suffering they use emotion regulation strategies
to prevent themselves from being overwhelmed with the negative emotions that
accompany compassion (Cameron & Payne, 2011; Shaw, Batson, & Todd, 1994). Thus,
empathic concern and even helping behavior, may reflect a basic “escape” reaction.
16
5 Summary Synthesizing theories and findings from the broad psychological domains of affect,
motivation, and empathy, a question about the nature of empathic responding begins to
emerge: Does empathic concern stem from a basic motivation to escape harm signaled by
the emotional expressions of others? Because empathic concern relies on more basic
processes of emotional contagion, and because emotional contagion can serve an
informational function that facilitates effective responses to threat, I predict that empathic
concern will be best characterized by withdrawal motivation. Specifically, I predict that
empathic concern will be associated with trait-level neural correlates of withdrawal
motivation and state-level facial expressions of withdrawal-related emotions.
Furthermore, I predict that empathic concern will show a positive relationship with fear
and a negative relationship with anger, both when measuring and manipulating these
affective variables. If these predictions are supported, this perspective on the empathic
response has the potential to deepen our understanding of the forces driving empathy, and
to generate new hypotheses about how that empathy is translated into action.
17
Chapter 2: Frontal Cortical Asymmetry and Empathy
1 Introduction If empathic concern stems from withdrawal motivation, it should be associated with
reliable neural correlates of this kind of motivational disposition. With the accumulation
of evidence regarding the emotional and behavioral consequences of frontal alpha EEG
asymmetry, it has become widely accepted that asymmetries in prefrontal cortical activity
reflect motivational direction (Coan & Allen, 2003; Davidson, 1995; Harmon-Jones,
2004; Harmon-Jones, et al., 2010; van Honk & Schutter, 2006). This account posits that
basic motivational direction – whether people are driven to move towards things or to
move away from them – maps on to patterns of asymmetrical cortical activation such that
withdrawal motivation has been associated with relative right-frontal activity, while
approach has been associated with relative left-frontal activity (Harmon-Jones & Allen,
1997; Sutton, & Davidson, 1997; cf. Wacker, Chavanon, & Stemmler, 2010).
Consistent with this formulation, asymmetric frontal cortical activation is also closely
tied with patterns of emotional responding (Jacobs & Snyder, 1996). Emotions like
happiness and anger, which are associated with approach motivation, are linked to left-
frontal activity (Coan, Allen, & Harmon-Jones, 2001; Davidson, Schaffer, & Saron,
1985; Harmon-Jones & Allen, 1998). Meanwhile, emotions like disgust, fear, and
sadness, which are associated with withdrawal, are linked to right-frontal activity (Coan
et al., 2001, Dawson, Panagiotides, Klinger, & Hill, 1992). At a dispositional level,
baseline levels of frontal asymmetry reflect susceptibility to approach and withdrawal-
relevant emotions. For example, people who have dispositionally higher levels of right-
frontal cortical activity show stronger negative emotion to fearful or disgusting stimuli
and weaker positive affect to happy stimuli (Tomarken, Davidson, Wheeler, & Doss,
1992; Wheeler, Davidson, & Tomarken, 1993).
These dispositional differences have also been shown to have clinical implications, with
research showing that right-frontal asymmetry is associated with increased risk for
depression (Henriques & Davidson, 1990; 1991; Nusslock, et al., 2011; Schaffer,
18
Davidson, and Saron, 1983). Because frontal EEG asymmetry has proven to be a stable
and reliable measure of individual differences (Tomarken, Davidson, Wheeler, & Kinney,
1992) trait measures of frontal asymmetry can provide a valuable tool in assessing
susceptibility to sadness and withdrawal-related affect.
1.1 Empathy and Frontal EEG Asymmetry
Because empathy is often viewed as an other-oriented, prosocial reaction to suffering – a
kind of “reaching out” – it has been posited that it should be associated with left-frontal
asymmetry (e.g., Goetz, Keltner, & Simon-Thomas, 2010; Lamm, Batson, & Decety,
2007). On the other hand, conceptualizations of empathy that emphasize vicarious
sharing of pain or sorrow (Ikes, 1997), or that propose a critical role for feelings of
personal distress (Cialdini et al., 1973; Ikes, 1997; Piliavin et al., 1981) raise the
possibility that empathy might, in some cases at least, be linked to right-frontal
asymmetry. If strong withdrawal motivation translates into a heightened responsiveness
to the sadness of others, greater right-frontal EEG asymmetry should be associated with
greater empathic responding to the suffering of others.
Some neuroscientific data has begun to reveal a link between right-frontal asymmetry and
empathic dispositions like affiliation motives (Quirin, Kazén, Hardung, & Kuhl, 2012).
Children who show greater right-frontopolar EEG activity during a task designed to elicit
positive emotion were more likely to show empathic concern in response to pain
expressed by the experimenter (Light et al., 2009). People with lesions to the right
ventromedial frontal cortex showed deficits in affective components of “mind-reading”
(Shamay-Tsoory, Tomer, Berger, Golsher, & Aharon-Peretz, 2005), while cortical
atrophy in the right frontal-temporal neural network has been associated with difficulties
in resolving social dilemmas (Eslinger et al., 2006).
Prosocial behavior also appears to be linked with right-frontal activity, as demonstrated
by findings showing that disrupting the functioning of the right, but not left, dorsolateral
prefrontal cortex using transcranial magnetic stimulation causes people to be less fair
during an economic game (Knoch, Pascual-Leone, Meyer, Treyer, & Fehr, 2006).
19
Integrating work on the neurobiology of psychopaths, Hecht (2011) has suggested that
the affective and empathic deficits displayed by these individuals are associated with
hypoactivity in the right hemisphere. This work, combined with the reasoning that
susceptibility to withdrawal-related emotions could lead people to be better able to feel
for the suffering of other people, leads to the prediction that right-frontal asymmetry may
relate to empathic reactions.
1.2 Objectives
In this study I explored the link between baseline right-frontal asymmetry and empathic
reactions towards others’ suffering. To do this I assessed resting frontal EEG asymmetry
and analyzed self-reported sadness, personal distress, and empathic concern to images of
African children ostensibly associated with a charity campaign. Based on Hypothesis 1,
which states that dispositional withdrawal motivation should be associated with empathy,
I predicted that baseline (i.e. trait) levels of right-frontal asymmetry would be associated
with feelings of personal distress, sadness, and empathic concern towards the images.
Furthermore, because empathic concern is thought to reflect more basic processes of
emotional contagion, right-frontal EEG asymmetry should lead to greater empathic
concern via increased contagion of withdrawal-related affect. If this is the case, I should
also find that sadness and personal distress mediate the relationship between right-frontal
EEG asymmetry and empathic concern.
2 Methods
2.1 Participants
Thirty-two introductory psychology students (23 female, Mage = 19.34, SDage = 2.37)
participated for course credit and $5. One participant was excluded due to an outlying
F4F3 asymmetry value (Z > 3.0), and another was excluded due to technical malfunction
during baseline EEG recording. For all retained participants, Z scores for F4F3
asymmetry values fall within the range of -1.00 to 1.00. For three participants, specific
electrode sites were excluded prior to data analysis due to noisy data in those channels.
As a result, Ns for analyses involving asymmetry values vary from 27 to 30.
20
2.2 Procedure
At the start of the experiment the participant was fitted with an EEG cap. First, baseline
EEG was recorded while participants sat still with their eyes alternately open and closed
for four blocks of 30s each. Participants were then told they would view two sets of 10
images of African children, each associated with a charity. These charity images were
found through a search of publically available online sources (i.e. Google image search).
A separate sample of introductory psychology students (N = 16) provided normative
ratings of physical suffering depicted and of emotions elicited by each of these charity
images (Table 1)1. Participants viewed the images as two counterbalanced blocks, each
consisting of 10 charity images interspersed with 10 scenery images. Images were
presented in random order with the restriction that scenery and charity images alternated.
Each image was displayed for 8s, followed by an 8s inter-trial interval. During this part
of the experiment participants were asked to simply sit still and concentrate on the
images. To ensure that participants were paying attention, they were told that they might
be asked questions about the images later in the experiment. Following this phase of the
experiment, participants viewed the two sets of charity images again and rated their
affective responses to each set of 10 images as a whole.
2.3 Self-Report Measures
In response to the charity images, participants used a 5-point scale (1 = strongly disagree,
5 = strongly agree) to indicate empathic concern (moved, sympathetic, compassionate,
warm, tender, soft-hearted), sadness (sad, feeling low, low-spirited, heavy hearted), and
personal distress (alarmed, grieved, troubled, upset, disturbed, worried, perturbed; see
Table 2 for descriptive statistics). Sadness, personal distress, and empathic concern were
analyzed independently (Batson, 1987; Fultz, Schaller, and Cialdini, 1988). Ratings for
each of these three constructs were averaged across the two sets of charity images (αs >
.75).
2.4 EEG Recording and Processing
21
EEG was recorded throughout the experiment using a stretch Lycra cap containing 32 tin
electrodes. Electrode placement followed the 10-20 system, and a digital average earlobe
reference was used. Electrode impedances were below 10kΩ. Vertical eye movements
were recorded to facilitate artifact identification. Recordings were digitized at 1024 Hz
using ASA acquisition software (Advanced Neuro Technology, Enschede, The
Netherlands). EEG was digitally filtered offline between 1 and 15 Hz, and corrected for
vertical electro-oculogram artifacts (Gratton, Coles, & Donchin, 1983), with signal
exceeding ±75 µV rejected by computer algorithm. Artifact-free 2.0s epochs were
extracted through a Hamming window (75% overlap) and submitted to fast Fourier
transform. Spectral power at each electrode was averaged across the two minutes of eyes-
open and eyes-closed blocks of baseline. Power values were natural-log transformed, and
asymmetry scores were calculated by subtracting left- from right-sided alpha at
homologous sites. Asymmetry scores at F4F3 were taken as indices of frontal asymmetry,
while scores at FC4FC3, CP4CP3, and P4P3 were used as non-frontal control values2.
Because alpha-power (8-12Hz) is inversely related to cortical activity (Lindsley &
Wicke, 1974), higher values on this difference score indicate greater left hemisphere
activity. I have chosen to use this metric because it is the most common in the frontal
asymmetry literature, but I discuss my results in terms of right-frontal asymmetry as that
is the focus of the present study. As such, negative correlations will indicate a positive
relationship between right-frontal asymmetry and other variables.
3. Results As hypothesized, asymmetry scores at the F4F3 site were significantly correlated with
empathic concern, sadness, and personal distress (Table 3; Figure 1). If the relationship
between asymmetry and empathy is specific to frontal regions, as expected, these
correlations should not be present for electrodes in central or parietal areas. At FC4FC3
and CP4CP3, asymmetry scores were not correlated with any of the variables of interest,
with the exception of a marginal relationship between CP4CP3 and empathic concern. At
P4P3 there were no significant relationships between asymmetry and personal distress,
but there were significant correlations with empathic concern and sadness in the opposite
22
direction of those found for frontal regions. Thus, it appears that the relationship between
rightward EEG asymmetry and empathy is specific to frontal regions.
According to the Russian doll model of empathy, sadness and personal distress reflect
phylogenetically older processes of emotional contagion compared to empathic concern,
which involves the additional step of recognizing a distinction between self-and other (de
Waal, 2008). To test whether the relationship between frontal EEG asymmetry and
empathic concern could be accounted for by increased emotional contagion, I ran a
multiple mediation model testing the relationship between baseline frontal asymmetry
and empathic concern with sadness and personal distress as mediators. Parameter
estimates were obtained using bootstrap analysis with 5,000 re-samples (Preacher &
Hayes, 2008). Mediation is said to be significant if the 95% bias-corrected confidence
interval for the parameter estimate does not contain 0. In this model, personal distress did
not emerge as a significant mediator (CI: [-1.62, 3.29]), and as such I re-ran this model
excluding personal distress (Figure 2; Figure 3). For the new model predicting empathic
concern from right-frontal asymmetry with sadness as a mediator, the confidence interval
for sadness did not contain 0, (CI: [-4.18, -.70]), indicating that sadness was a significant
mediator of the relationship between baseline frontal EEG asymmetry and empathic
concern. Mediation tests that assume normality (Sobel, 1982) also indicate significant
mediation, Z = -2.67, p = .008. When sadness was accounted for, the relationship
between right-frontal asymmetry and empathic concern was no longer significant, c’ = -
.03, p = .97. Thus, the relationship between right frontal asymmetry and empathic
concern can be explained by the fact that people with greater levels of right frontal
asymmetry tend to react with greater sadness to the images.
4. Discussion Consistent with my predictions, results indicated that individuals who displayed more
dispositional right-frontal asymmetry were more likely to experience empathic concern
when viewing charity images. In addition, this relationship was fully mediated by
feelings of sadness in response to these images. These findings expand our understanding
of empathy by demonstrating that it is associated with a pattern of dispositional brain
23
activity that reflects withdrawal. Furthermore, these findings are consistent with the
suggestion that empathic concern reflects the motivation to escape.
One implication of these findings is that empathy, although measured with positive-
sounding words like “warmth” and “compassion,” might be an unpleasant emotional
state. People who showed neural activity suggestive of a heightened tendency to
experience withdrawal-related emotions were also the ones who were most likely to
report empathic concern. Consistent with distress-relief models of helping, these results
suggest that people who are more susceptible to “feeling the pain” of others are the ones
who are most likely to empathize. This interpretation raises an important question: is
baseline right-frontal asymmetry associated with empathy only when the target is
displaying withdrawal-related emotions? Theories of empathy that focus on internal
simulation of others’ affective states have led to the hypothesis that empathy may be
augmented when there is overlap between the affective state of the observer and target
(Preston & de Waal, 2002). Thus, people who show a dispositional rightward bias in
frontal asymmetry may empathize with suffering targets because their withdrawal
tendencies are congruent with the withdrawal-related emotions of the targets (c.f.
Harmon-Jones & Allen, 1998). Alternatively, right-frontal asymmetry may be associated
with greater empathy to both positive and negative targets, suggesting that this pattern of
brain activity encourages a generalized increase in empathic concern regardless of the
affective state of the target. This possibility will be addressed in Study 2.
My interpretation of the findings is also informed by emerging research on empathy’s
relationship with the error-related negativity (ERN; Gehring, Goss, Coles, Meyer, &
Donchin, 1993). The ERN is a neural signal that is involved in the aversive affective
reaction to conflict and error (Hajcak & Foti, 2008; Inzlicht & Al-Khindi, in press;
Inzlicht & Tullett, 2010; Luu, Collins, & Tucker, 2000; Yeung, 2004; see Olvet &
Hajcak, 2008, for a review). Consistent with these findings, the ERN is thought to be
generated by the midcingulate cortex, a brain region involved in the integration of
cognitive control, pain, and negative affect (Shackman et al., 2011). Importantly, new
research finds that ERN amplitude is larger for those with greater baseline right-frontal
asymmetry (Nash, McGregor, & Inzlicht, 2011), and for those who report high levels of
24
dispositional empathy (Larson, Fair, Good, & Baldwin, 2010; Santesso & Segalowitz,
2009). Because the amplitude of the ERN is associated with a susceptibility to negative
affect, distress, and anxiety (Hajcak & Foti, 2008; Hajcak, McDonald, & Simons, 2003;
2004), these data are consistent with the idea that this susceptibility is conducive to
increased empathic responding.
In addition to the predicted relationship between asymmetry and empathy at frontal
regions, I also found an unanticipated negative relationship between right-parietal
asymmetry (at sites P4P3) and empathy. Thus, for frontal regions relatively greater right-
than-left activity was associated with empathy, while in parietal regions this relationship
was reversed. Although I am cautious in interpreting these results given inconsistencies
in the literature regarding resting parietal EEG asymmetry (Henriques & Davidson, 1997;
Kentgen et al., 2000), research on depression provides some precedent for a dissociation
between frontal and parietal activation patterns. Whereas depression has frequently been
associated with hypoactivity in left-frontal regions (Henriques & Davidson, 1990; 1991;
Nusslock et al, 2011; Schaffer et al., 1983), several studies have found that depressed
participants show hypoactivity in right-posterior regions (Allen, Iacono, Depue, &
Abrisi, 1993; Henriques & Davidson, 1990; 1997). This pattern appears to best
characterize a subset of depressed patients who do not have comorbid anxiety disorders
(Bruder et al., 1997) or who show a pattern of underarousal (Stewart, Towers, Coan, &
Allen, 2011). This pattern of left-frontal hypoactivity and right-parietal hypoactivity in
depression also characterizes empathic responding in the current study, perhaps
suggesting that some of the same factors that underlie susceptibility to depression also
underlie a propensity to feel empathy. Further research that investigates EEG asymmetry,
depression, and empathy in a single study could shed light on this possibility. Currently,
however, this explanation remains speculative, and indeed research demonstrating the
involvement of the right-temporoparietal junction in empathy could lead to the opposing
prediction that hyper-activity in right-posterior regions should be positively associated
with empathy (Decety & Lamm, 2007).
Overall, these findings implicate right-frontal asymmetry in empathic responding.
Conversely, left-frontal asymmetry may dampen empathy (or even encourage aggression;
25
Harmon-Jones & Sigelman, 2001; Peterson, Shackman, & Harmon-Jones, 2008), as
suggested by its association with decreased empathic reactivity towards others in need.
These findings suggest a link between empathy and withdrawal, and raise questions about
the precise nature of this relationship. First, is the dispositional experience of withdrawal-
related emotion associated with empathy, and if so, is this relationship stronger for some
emotions than for others? Second, is the link between withdrawal and empathy only true
when the target of empathy is experiencing withdrawal-related emotions?
26
Chapter 3: Individual Differences in Withdrawal-Related Affect and Empathy
1 Introduction In Study 1, I showed that empathic concern is associated with right-frontal EEG
asymmetry, an established neural correlate of heightened withdrawal motivation (or,
conversely, dampened approach motivation). If my interpretation of this finding is
correct, measures of empathic concern should also be positively related to measures of
withdrawal-related affect, or negatively related to measures of approach-related affect, or
both. To specifically explore the link between empathy and affect I focused on two basic
emotions – fear and anger – that are reliably associated with withdrawal- and approach-
motivational tendencies, respectively.
1.1 Fear, Anger, Withdrawal, Approach
According to Lazarus (1991), fear and anger are competing reactions to threatening
stimuli; in a dangerous situation, a person can react with fear, and flee, or with anger, and
fight. Deciding between these two reactions is partly dependent on the affordances of the
physical environment. For instance, when participants faced a threatening outgroup
member in an enclosed room they were more likely to react with aggression, whereas if
they were in an open field they were more likely to distance themselves from the other
person (Cesario, Plaks, Hagiwara, Navarette, & Higgins, 2010). In addition, levels of
fear are lower in anger-causing situations than in other negative-affect situations,
suggesting that fear and anger are competing emotional reactions (Izard, 1972).
Behaviorally and physiologically, fear and anger can be differentiated in ways that
further corroborate their distinct motivational roles. Anger is associated with high levels
of directed activity, and increased energy and determination (Izard, 1972, 1992).
Compared to fear, anger is associated with greater increases in diastolic pressure and
heart rate, and slower recovery of systolic pressure (Schwartz, Weinberger, & Singer,
1981). Inductions of anger and fear have also been shown to lead to distinct
somatovisceral response patterns, with anger leading to relatively stronger noradrenergic
27
responses, and fear leading to relatively stronger adrenergic responses (Stemmler et al.,
2007). These findings demonstrate that fear and anger are associated with different
behavioral and physiological changes consistent with their roles in withdrawal/flight and
approach/fight, respectively.
Researchers have noted that fear and anger are uniquely interesting from a theoretical
perspective because they allow researchers to tease apart motivational direction from
affective valence – both fear and anger are negative affective reactions, but fear is
associated with withdrawal while anger is associated with approach (Stemmler et al.,
2007; Wacker et al., 2003). Consistent with the motivational direction model of frontal
EEG asymmetry, fear and anger are correlated with relative right- and left-frontal
activity, respectively (Davidson, Marshall, Tomarken, & Henriques, 2000; Fox &
Davidson, 1988; Harmon-Jones & Sigelman, 2001; Harmon-Jones, Sigelman, Bohlig, &
Harmon-Jones, 2003; Wiedemann et al., 1999). Wacker and colleagues (2003)
demonstrated that inducing feelings of anger led to greater changes toward left-frontal
asymmetry compared to feelings of fear, a result that supports anger’s stronger
association with approach motivation and the BAS. Thus, dispositional susceptibilities to
fear and anger provide an emotional indicator of withdrawal- and approach-motivational
tendencies.
1.2 Objectives
Supporting Hypothesis 1, Study 1 showed that a neural correlate of dispositional
withdrawal motivation – right-frontal asymmetry – was a predictor of empathic concern.
In Study 2 I aimed to conceptually replicate this finding by examining the link between
dispositional susceptibility to withdrawal-related emotions and empathic reactions. I also
attempted to extend the findings from Study 1 by looking at empathic reactions to both
positive and negative events. This allowed me to examine whether withdrawal motivation
is associated with empathic reactions in general, or with empathic reactions to
withdrawal-related emotional states specifically. Because I posit that the processes
underlying emotional contagion and empathic concern reflect a basic drive to escape
threat, I predicted that empathy towards both positive and negative events would be
28
associated with dispositional measures of fear, and negatively associated with
dispositional measures of anger.
These comparisons provide a way to specifically focus on the dimension of approach vs.
withdrawal while keeping valence constant, as fear and aggression are both negative
emotions, but fear is associated with withdrawal and anger is associated with approach.
By taking advantage of this comparison, I can address a possible alternative interpretation
of the findings from Study 1. According to emotional valence models of frontal EEG
asymmetry, the findings could reflect a link between empathy and negative affect, rather
than a link between empathy and withdrawal motivation. If this interpretation is correct,
fear and aggression should both be positively associated with empathy in Study 2. To
further investigate this alternative I included a measure of dispositional positive and
negative affect, reasoning that if findings from Study 1 reflect a link between empathy
and general negative affect, then dispositional measures of general negative affect should
effectively predict empathy reactions.
The study design employed here also has the potential to address the possibility that the
link between empathy and right-frontal asymmetry from Study 1 was due to dampened
anger, rather than increased withdrawal-related affect. If this alternative explanation is
accurate, there should be a negative relationship between anger and empathy, but no
positive relationship between fear and empathy. In other words, this design allows me to
assess approach and withdrawal independently, without pitting them against each other as
in Study 1.
2 Method
2.1 Participants
Participants (N = 90) were recruited online from the United States using Mechanical Turk
and received monetary compensation for their participation. I included an instructional
manipulation check to determine whether participants carefully read and followed
instructions (Oppenheimer, Meyvis, & Davidenko, 2009). For this manipulation check
participants were presented with a set of instructions followed by the question “Which of
29
these activities do you engage in regularly?” and a list of sports activities. Near the end of
the instructions, participants are told to ignore the sports items, and instead to choose
“other” and to specify “psychology.” Twenty-one participants were excluded because
they failed to complete the experiment (N = 2) or because they didn’t follow the
instructions in the instructional manipulation check (N = 19). Thus, we analyzed data for
69 participants (51 female, Mage = 34.30, SDage = 11.47). Missing data were replaced with
the sample mean.
2.2 Procedure
Participants were told they would view eight images of children taken from a child
sponsorship website. Four of the images depicted children expressing happiness, and
participants were told that these photos were taken just after those children had learned
that they had been sponsored. The other four images depicted children expressing
sadness, and participants were told that the photos were taken after the children learned
that they had not been sponsored. Happy and sad targets were presented in counter-
balanced order across participants. Participants were told that these images were being
considered for a new fundraising campaign and that for this reason the charity was
interested in the emotional reactions the images elicit. For the sad targets, participants
used a 5-point scale (1 = Not at all, 5 = Extremely) to indicate the degree to which they
experienced empathic concern (warm, tender, soft-hearted, sympathetic, compassionate,
moved) and emotional contagion (sad, single item). Similarly, for the happy targets
participants indicated the degree to which they experienced empathic concern (excited,
pleased, glad, thrilled, delighted) and emotional contagion (happy, single item).
Subsequently, participants filled out demographic information and completed individual
difference measures assessing aggression, fear, and positive and negative affect.
2.3 Individual Difference Measures
To assess dispositional anger, participants completed the Aggression Questionnaire (AQ;
Buss & Perry, 1992) which assesses four dimensions of aggression: physical aggression
(e.g. Given enough provocation, I may hit another person) α = .89, verbal aggression
30
(e.g. When people annoy me, I may tell them what I think of them) α = .71, anger (e.g. I
have trouble controlling my temper) α = .73, and hostility (e.g. I wonder why sometimes I
feel so bitter about things), α = .84. To assess dispositional fear, participants were asked
to complete the Fear Survey Schedule-II (FSS-II; Geer, 1965). This scale is comprised of
a list of stimuli (e.g. dead bodies, roller coasters, being alone), and participants rate the
degree to which each stimulus causes them to feel fear, α = .96. Finally, participants also
filled out the Positive and Negative Affect Schedule (PANAS; Watson, Clark, &
Tellegen, 1988). This scale assesses the degree to which participants generally experience
positive affect (e.g. strong, enthusiastic, inspired) α = .98, and negative affect (e.g.
nervous, irritable, distressed) α = .93.
3 Results First, I computed the bivariate correlations between the FSS-II, the AQ, empathic
concern, and emotional contagion (Table 4). To test the hypothesis that empathic concern
would be positively associated with fear and negatively associated with aggression,
irrespective of the valence of the target image, I conducted a multi-level model to predict
empathic concern as a function of physical aggression, fear, target valence, and all
interactions. I focused on the physical aggression subscale of the AQ because this
subscale is most clearly associated with approach-motivational tendencies. This, and all
subsequent models, was estimated with a random-intercept model for each participant.
The overall three-way interaction between aggression, fear, and valence was non-
significant b = .01, SE = .07, t(85) = .15, p = .88. The two-way interactions between
aggression and valence, and between fear and valence, were also non-significant, ts < .3.
We retained valence as a covariate in subsequent models, but this analysis demonstrates
that the relationships between aggression and empathic concern, and between fear and
empathic concern, are not moderated by the valence of the target image.
The next step was to test the meditational model in which physical aggression and fear
are predictors of empathic concern, as mediated by emotional contagion. To examine this
effect I first examined the total effect of physical aggression and fear on empathic
concern, controlling for target valence. As predicted, physical aggression was negatively
related to empathic concern, b = -.36, SE = .10, t(87) = -3.52, p < .01, and fear was
31
positively related to empathic concern, b = .22, SE = .09, t(87) = 2.45, p = .02. Next, I
modeled the mediator, emotional contagion, as a function of physical aggression and fear,
controlling for target valence. Physical aggression was negatively related to emotional
contagion, b = -.25, SE = .11, t(87) = -2.26, p = .03, and fear was positively related to
emotional contagion, b = .38, SE = .10, t(87) = 3.75, p < .01. When empathic concern
was regressed simultaneously on physical aggression, fear, and emotional contagion,
emotional contagion significantly predicted empathic concern b = .70, SE = .04, t(87) =
15.99, p < .01. The inclusion of emotional contagion reduced the influence of physical
aggression on empathic concern, b = -.16, SE = .06, t(87) = -2.88, p = .01 (Sobel’s z =
2.24, p = .03). The inclusion of emotional contagion also reduced the influence of fear on
empathic concern such that the relationship became non-significant, b = -.05, SE = .05,
t(87) = -1.00, p = .32 (Sobel’s z = 3.65, p < .01). These results demonstrate that
regardless of target valence, fear positively predicts empathic concern and physical
aggression negatively predicts empathic concern, and these relationships are mediated by
emotional contagion.
To address the possibility that empathy might be related to negative affect in general, I
also examined the correlations between empathic concern, emotional contagion, and
positive and negative affect. Here, there were no significant relationships except for a
positive association between the positive affect subscale of the PANAS, and emotional
contagion towards happy targets, r = .25, p =.04. All other relationships between the
PANAS and the empathy measures were not significant, rs < .2, ps > .1. These results
suggest that general positive and negative affect were largely unrelated to measures of
empathic responding.
To examine the independent contributions of physical aggression, fear, and positive and
negative affect to both empathic concern and emotional contagion, I conducted two
multiple regression analyses. In the first, I regressed overall empathic concern on
physical aggression, fear, positive affect, and negative affect. For this analysis, the
multiple correlation coefficient was significant, R = .45, F(4, 64) = 4.07, p < .01, as was
the regression coefficient for aggression, b = -.40, t(64) = -3.41, p < .01. All other
coefficients were non-significant, bs < .15, ps > .2. I then conducted a regression
32
predicting overall emotional contagion from aggression, fear, positive affect, and
negative affect. This analysis revealed a significant multiple correlation coefficient, R =
.42, F(4, 64) = 3.42, p = .01, a significant regression coefficient for fear, b = .30, t(64) =
2.24, p = .03, and a significant regression coefficient for physical aggression, b = -.26,
t(64) = -2.21, p = .03. Thus, physical aggression and fear predicted emotional contagion
and empathic concern above and beyond measures of positive and negative affect. 4 Discussion Overall, the pattern of correlations found in Study 2 is largely consistent with the
prediction that empathic concern and empathic contagion would be positively associated
with dispositional fear, and negatively associated with dispositional anger. Corroborating
the results of Study 1, these findings support Hypothesis 1, which states that empathy
should be associated with dispositional withdrawal motivation. The observation that
empathy shows opposite relationships with fear and anger provides strong support for the
idea that greater empathic responding is predicted by motivational direction specifically,
and not emotional valence. Both fear and anger reflect negative affective states, but they
differ in terms of their motivational direction, with anger motivating people to approach,
and fear motivating people to withdraw. Thus, our findings suggest that empathy is
associated with withdrawal motivation, rather than negative affect. This interpretation is
further supported by the lack of relationship between empathic responding and
dispositional positive affect and negative affect.
Interestingly, the relationships between measures of dispositional affect and empathy
were very similar, regardless of the valence of the affect displayed by the target. In other
words, positive and negative empathy showed similar relationships with both anger and
fear, suggesting that empathic reactions reflect an empathic tendency, rather than positive
or negative emotional tendencies. This finding expands on the findings from Study 1 by
demonstrating that the link between withdrawal and empathy is not simply a matching
effect; withdrawal motivation is not just associated with empathy for withdrawal-related
emotions, but also with empathy for approach-related emotions. Thus, withdrawal
motivation appears to be associated with general processes of emotional contagion and
empathic concern.
33
A potential alternative explanation for the discrepancy between fear and anger in
predicting empathy is that this distinction is attributable to the anti-social characteristics
of anger in comparison to fear. In other words, angry people may generally have more
negative or distrustful views of others. There are two reasons why this interpretation is
unlikely to account for our findings. First, anger is not always an anti-social emotion, and
can even encourage prosocial action. Particularly in instances where one person’s actions
cause harm to another person, anger can motivate observers to stand up for the
disadvantaged (Vitaglione & Barnett, 2003). Second, if the anti-social qualities of anger
account for the negative association with empathy, a similar type of relationship would be
expected with fear, which could also be seen as having anti-social elements. When people
feel fear in a social context, this typically means that they are in the presence of
threatening or dangerous individuals. Fear can be caused by interpersonal rejection or
outright physical danger, events that are clearly anti-social in their implications
(Eisenberger & Lieberman, 2004). For these reasons, motivational direction, rather than
degree of anti-sociality, provides a better explanation of the results.
In this study I also examined the same mechanistic pathway that I looked at in Study 1;
that is, I tested whether emotional contagion might mediate the relationships between
dispositional measures of affect and empathic concern. These results provided support for
the prediction that withdrawal-related affect should predict greater empathic concern via
increased emotional contagion, and approach-related affect should predict lesser
empathic concern via decreased emotional contagion. Specifically, fear positively
predicted empathic concern through increased emotional contagion, while physical
aggression negatively predicted empathic concern through decreased emotional
contagion. Overall, this analysis is consistent with the idea that negative withdrawal-
related affect is associated with enhanced emotional contagion, whether positive or
negative, whereas negative approach-related affect is associated with diminished
emotional contagion. Furthermore, emotional contagion was a significant predictor of
empathic concern reactions that are, theoretically, more phylogenetically advanced other-
centered reactions.
34
Studies 1 and 2 provide converging evidence that dispositional withdrawal motivation –
measured using frontal EEG asymmetry and self-reported affective tendencies – is
predictive of empathic concern. Study 2 expanded on Study 1, showing that this
relationship is not reducible to a link between empathy and negative affect, and showing
that withdrawal predicts empathic reactions even when the target is displaying approach-
related emotions like happiness. Thus far, however, I have focused on withdrawal
motivation as a trait, and have not established that the occurrence of empathic concern is
characterized by a withdrawal-related motivational state. This is the question that I will
examine in Study 3.
35
Chapter 4: Levator Labii and Corrugator Supercilii Activity and Empathy
1 Introduction So far, Studies 1 and 2 have demonstrated, as predicted, that dispositional correlates of
withdrawal motivation are predictive of empathic responses. If the experience of empathy
is characterized by a withdrawal motivational state, however, it is important to
demonstrate that empathic reactions co-occur with withdrawal-related reactions, and that
the degree of the former increases with the degree of the latter. For this reason I
conducted Study 3, focusing on state measures of both empathic concern and withdrawal-
related affect. In addition to measuring self-reported affective reactions, I also obtained
measures of disgust – a withdrawal emotion – and general negative affect using
electromyography (EMG). In this way, I was able to test whether subtle, and largely
automatic, facial expressions associated with withdrawal, but not general negative affect,
were associated with increased empathic concern (Dimberg, 1982; Ekman, 1992).
1.1 The Facial Expression of Withdrawal
Disgust evolved as a self-protective mechanism to avoid disease and contamination
(Oaten, Stevenson, & Case, 2009, Schaller & Duncan, 2007). Humans even display a
facial expression that is specific to the emotion of disgust – wrinkling the nose and
raising the upper lip using the levator labii muscle – that is thought to prevent us from
ingesting pathogens (Rozin, Lowery, & Ebert, 1994; Stark, Walter, Schienle, Vaitl, 2005;
Vrana, 1993). Because the physical suffering of others often implies a threat of
contamination to the self via signals of disease or infection, it is also expected to invoke
such a disgust reaction. Indeed, neuroimaging research has demonstrated that many of the
same neural regions are recruited when people watch disgusting videos as when they
watch videos of people in pain (Benuzzi, Lui, Duzzi, Nichelli, & Porro, 2008). Disgust
compels us to avoid the unsavory, and it is this function that links the emotion very
closely with withdrawal motivation (Rozin, Haidt, & McCauley, 2000; Woody & Tolin,
2002).
36
Previous research has established that a different facial muscle region – the corrugator
supercilii – is associated with a more generalized negative affective response. Like the
facial expression of disgust, it has been proposed that corrugator supercilii activity may
be part of an adaptive reaction to environmental stimuli (Dimberg, 1997; Ekman, 1992).
Corrugator supercilii activity has been observed consistently during the expression of
sadness, disgust, fear, and anger (Brown & Schwartz, 1980; Dimberg & Thunberg, 1998;
Lang, Greenwald, Bradley, & Hamm, 1993; Larson, Norris, & Cacioppo, 2003; Yartz, &
Hawk, 2002). Thus, the corrugator supercilii region is often viewed as a reliable indicator
of negative affect, but a poor indicator of motivational direction, as it is linked with both
withdrawal- and approach-related varieties of negative affect.
1.2 Objectives
In Studies 1 and 2, I found that empathic responding was associated with dispositional
withdrawal. To extend these findings, in Study 3 I examined whether empathic
responding was associated with state withdrawal. Specifically, I wanted to see whether
empathic responding would be accompanied by withdrawal-related facial expressions, as
assessed using EMG. As stated in Hypothesis 2, I predicted that people who react to
images with stronger withdrawal-related facial expressions would also experience
stronger feelings of empathic concern. While participants viewed images of children
ostensibly associated with a charity I used EMG to assess activity in the levator labii and
corrugator supercilii muscle regions, which are associated with expressions of disgust and
general negative affect respectively. In addition, I assessed participants’ empathic
concern, sadness, and disgust towards these images using self-report. I predicted that
empathic concern would be related to activity in the levator labii region, but not activity
in the corrugator supercilli region, as the former is specifically associated with
withdrawal while the latter is not. Because I suspected that this process might be stronger
for images that elicit more pronounced facial expressions, I compared reactions to images
depicting suffering vs. non-suffering children.
2 Method
2.1 Participants
37
Thirty-seven introductory psychology students (19 female, Mage = 18.73, SDage = .96)
participated for course credit and $5. One participant was excluded from all analyses
involving scenery images because of an error in EMG recording during this portion of the
experiment.
2.2 Procedure
To begin, the experimenter attached five electrodes to the participant’s face (two at the
levator labii, two at the corrugator supercilii, and one at the forehead as a ground).
Participants were then told they would view two sets of images of African children, each
from a different charity (these images were the same as those used in Study 1). Images
and charity descriptions were counterbalanced. The two sets of images differed with
respect to the depiction of physical suffering; one set of images portrayed clear physical
suffering (in the form of emaciation, visible lesions, etc.) while the other set did not
(Figure 4). Ten suffering images were matched to ten non-suffering images with respect
to gender, race, age, body position, and general context, and pilot testing revealed that the
two sets differed with respect to the physical suffering participants perceived, t(12) =
17.17, p < .001, d = 4.11. The sets were presented in counterbalanced order, and were
each interspersed with 10 scenery images. Images were presented in random order with
the restriction that scenery and charity images alternated. Each image was displayed for
8s, followed by a 8s inter-trial interval. Participants then viewed all 20 charity images for
a second time, presented in random order, and rated their feelings of empathy, sadness,
and disgust to each one.
Finally, 16 control images – 8 disgust controls and 8 sadness controls – were presented in
the same manner as the charity images. These controls were taken from the International
Affective Picture System (IAPS; Lang, Bradley, & Cuthbert, 2008) and allowed me to
validate our EMG measures by providing a basis of comparison for the charity images.
During pilot testing, participants rated the disgust controls (M = 4.20, SD = .67) as
significantly more disgusting than sad controls (M = 1.34, SD = .34), t(22) = 18.83, p <
.001, d = 5.38, and rated the sadness controls (M = 3.21, SD = .69) as significantly sadder
than disgust controls (M = 1.54, SD = .35), t(22) = 13.13, p < .001, d = 3.05.
38
2.3 Self-Report Measures
In response to each charity image, participants used a 5-point scale (1 = strongly
disagree, 5 = strongly agree) to indicate the extent to which they felt empathic concern
(moved, sympathetic, compassionate), sadness (sad, single item) and disgust (disgusted,
single item). Sadness and empathic concern were analyzed independently, as
recommended by Fultz, Schaller, and Cialdini (1988). Ratings were averaged across the
set of suffering images and the set of non-suffering images separately (αs > .90).
2.4 EMG Recording and Processing
EMG data were acquired using a MindWare BioLab (Version 2.1) system (MindWare
Technologies LTD, Gahanna, OH). At acquisition, data were amplified (×1000) and
filtered with a bandpass of .05 to 100 Hz. Electrodes were placed over the levator labii
and corrugator supercilii muscle regions on the left side of the face, using the placements
suggested by Tassinary, Cacioppo, and Vanman (2007). EMG data were analyzed using
the MindWare Technologies Ltd. EMG Module (Version 2.6). The signal was rectified
with an absolute value function and smoothed by applying a low-pass filter at 100Hz. We
then applied a 30Hz high-pass filter to eliminate potential ocular artifacts (Tassinary et
al., 2007). The period of interest in each trial was the 8s image presentation period, which
we subdivided into two 4s epochs. Activity from 1s of fixation preceding each image was
used as a baseline and was subtracted from activity obtained during image viewing. A
contour following integrator was then applied to compute a running average of EMG
activity.
3 Results First, in order to determine which epoch was associated with stronger EMG responses, I
conducted a 2 (epoch: 0-4s vs. 4-8s), by 2 (image type: sad control vs. disgust control) by
2 (muscle: corrugators supercilii vs. levator labii) within-subjects ANOVA. This analysis
revealed a significant main effect of image type, such that EMG responses were stronger
for the disgust control images (M = 1.54µV, SE = .45µV), than for the sad control images
(M = .22µV, SE = .13µV), F(1, 36) = 8.85, p = .005. There was also a significant
39
interaction between muscle and epoch, such that corrugator supercilii was stronger during
the 0-4s epoch (M = .84µV, SE = .26µV) than during the 4-8s epoch (M = .62µV, SE =
.21) while this difference was less pronounced for the levator labii muscle (M0-4s =
1.02µV, SE0-4s = .34µV, M4-8s = 1.06µV, SE4-8s = .38µV). Because EMG responses were
stronger in the 0-4s epoch, at least for corrugator supercilii sites, I conducted all
subsequent analyses using this epoch.
If levator labii activity is a valid measure of disgust as expected (Vrana, 1993), I should
find that it correlates with self-report measures of disgust, and that it is higher for
disgusting images compared to non-disgusting images. Consistent with these criteria,
levator labii activity was correlated with self-reported disgust to the suffering images r =
.43, p = .008, and was higher for disgust control images (M = 1.89µV, SD, = 3.71µV)
than for scenery (M = .25µV, SD = 1.21µV), t(35) = 3.22, p = .003, or sad control images
(M = .14µV, SD = 1.45µV), t(36) = 2.73, p = .01. Similarly, if corrugators supercilii
activity is associated with negative affect in general, I should find that it correlates with
self-report measures of disgust and sadness, and that it is higher for disgust and sad
control images than for scenery images. As predicted, for suffering images corrugator
supercilii activity was significantly correlated with self-reported sadness, r = .36, p = .03,
and marginally correlated with self-reported disgust, r = .29, p = .08. Corrugator
supercilii activity was also lower for scenery images (M = -.05µV, SD = .45µV), than for
disgust controls (M = 1.26µV, SD = 2.68µV), t(35) = 2.86, p = .007, or sad controls (M =
.31µV, SD = .69µV), t(35) = 2.80, p = .008.
To explore the effects of physical suffering on self-reported empathic concern, sadness,
and disgust, I compared responses to the two charities. When viewing the suffering
images, participants reported feeling more empathic concern, sadness, and disgust
relative to the non-suffering images, all ts(36) > 9.0, all ps < .001. Levator labii activity
was higher for suffering images (M = .38µV, SD = 1.28µV) than for non-suffering images
(M = .07µV, SD = .80µV), but this difference did not reach significance, t(36) = 1.33, p =
.19 (Table 5). Corrugator supercilii activity was higher for suffering images (M = .96µV,
SD = 2.72µV) than for non-suffering images, (M = .03µV, SD = .70µV) t(36) = 2.50, p =
.017. As predicted, corrugator supercilii activity was not correlated with empathic
40
concern for either type of image (rs < .25, ps > .1) suggesting that empathic reactions
were not associated with generalized negative affect.
In this study, I was also interested in examining whether levator labii was a predictor of
empathic concern, and whether emotional contagion mediated this effect (see Tables 6
and 7 for bivariate correlations). I expected this relationship to emerge for suffering
images but not for neutral images. Thus, I hypothesized that the effect of levator labii
activity on empathic concern would be moderated by image type, and that this effect
would be explained by emotional contagion. This hypothesis can be analyzed using
mediated moderation analysis (Muller, Judd, & Yzerbyt, 2005). First, I regressed
empathic concern on image type, levator labii activity, and their interaction. Consistent
with moderated mediation, there was an overall effect of image type, b = .56, SE = .05,
t(34) = 10.40, p < .01, and an interaction between image type and levator labii activity, b
= .15, SE = .07, t(34) = 2.15, p = .04. This demonstrated that suffering images evoked
more empathic concern than non-suffering images, and that this was especially true for
participants who showed higher levels of levator labii activity.
Next, I modeled the mediator, emotional contagion, as a function of image type, levator
labii activity, and their interaction. Similar to the findings for empathic concern, image
type was related to emotional contagion b =.71, SE = .06, t(34) = 12.53, p < .01. There
was also an interaction between image type and levator labii activity in predicting
contagion, b = .21, SE = .07, t(34) = 3.00, p = .01. This showed that people expressed
more emotional contagion towards suffering compared to non-suffering images, and that
this difference was larger for people who showed high levels of levator labii activity.
Finally, I modeled empathic concern as a function of image type, levator labii activity,
emotional contagion, and the interactions between image type and levator labii activity,
and between image type and emotional contagion. The interaction between image type
and levator labii activity no longer predicted empathic concern, b = .01, SE = .05, t(32) =
.25, p = .81. The main effect of emotional contagion on empathic concern was
significant, b = .71, SE = .07, t(32) = 10.66, p < .01. These results show that emotional
41
contagion emerged as a significant mediator in the model. The full effects of all models
are reported in Table 8. 4 Discussion In line with Hypothesis 2, I predicted that state withdrawal reactions – as assessed using
facial EMG measures of levator labii muscle movements – would be associated with
greater empathic concern. These predictions were supported by the findings, as I found
that levator labii activity and image type interacted to predict empathic concern. This
interaction demonstrated that participants felt greater empathic concern towards suffering
compared to neutral images, and that this effect was stronger for people who showed
greater levator labii activity. This suggests that people who experience a stronger
withdrawal reaction to the suffering of others are also more likely to show greater
empathic concern for suffering, compared to non-suffering targets.
Consistent with the hypothesis that empathic concern would be uniquely associated with
withdrawal-related affect, and not with general negative affect, the corrugator supercilii
muscle region was not significantly correlated with empathic concern. Corroborating the
findings regarding dispositional affect from Study 2, these results suggest that empathic
concern doesn’t stem from general negative affect, but specifically from withdrawal-
related affect. Again, these findings support a conceptualization of empathic concern as
arising from escape motivational systems.
These findings demonstrate an interesting juxtaposition of responses that occurs when
people are exposed to the physical suffering of others. Relative to non-suffering images,
participants were more disgusted by the suffering images, but they also reported feeling
more empathic concern and sadness. This co-occurrence of seemingly opposing reactions
was clarified by our mediated moderation analysis; stronger facial expressions of disgust
were associated with stronger emotional contagion to suffering compared to non-
suffering images, and this emotional contagion was a predictor of empathic concern.
These results mirror the meditational pathways that were observed in Studies 1 and 2,
with a measure of withdrawal motivation predicting empathic concern via stronger
emotional contagion reactions. Again, the picture that emerges is one in which empathic
42
concern is associated with withdrawal motivation, a link that is mediated by
phylogenetically older emotional contagion processes (de Waal, 2002).
The three studies described thus far have provided correlational evidence that empathic
concern is associated with both trait and state measures of withdrawal motivation. This
evidence, however, cannot address the causal direction of these relationships. At this
point, the question still remains: Can withdrawal motivation cause greater empathic
concern?
43
Chapter 5: Approach and Withdrawal Facial Expressions and Empathy
1 Introduction Up to this point, I have demonstrated a link between empathy and withdrawal by
conducting correlational studies examining how empathic concern relates to various
measures of withdrawal motivation. These studies provide converging evidence for this
link, but do not rule out the possibility that a third variable is accounting for this
relationship, or that withdrawal motivation might be caused by an empathic disposition.
In Study 4 I will use facial muscle configurations to experimentally manipulate approach-
and withdrawal-related affect, again focusing on anger and fear, and will then examine
whether this manipulation has a causal influence on empathic responding.
1.1 The Facial Feedback Hypothesis
According to the facial feedback hypothesis, people’s facial muscle movements shape
their affective experience (see McIntosh, 1996). Intriguing evidence for this idea comes
from a study demonstrating that holding a pencil between one’s teeth results in more
positive affect than does holding between one’s lips (Strack, Martin, & Stepper, 1988).
The authors reasoned that this occurs because, in the lips condition, the zygomaticus
major muscle – associated with smiling – was inhibited, while in the teeth condition it
was activated. Thus, muscle feedback from the face was found to influence people’s self-
reported emotional state. Further evidence of the role of facial feedback in the experience
of emotions comes from studies that find impaired emotional processing following the
use of Botulinum Toxin-A (popularly known as Botox), a substance that impairs facial
muscle activity (Havas, Glenberg, Gutowski, Lucarelli, & Davidson, 2010).
If facial muscle movements can cause changes in emotional experience, this could
provide a useful way to manipulate approach- and withdrawal-related affect. Indeed,
previous research has shown that facial muscle configurations can influence self-reported
emotional states, as well as physiological changes (Duclos et al.,1989; Levenson, Ekman,
& Freisen, 1990). Importantly, these studies have demonstrated that facial muscle
44
movements associated with fear and anger have diverging effects, suggesting that these
two configurations produce different affective experiences in the person generating the
movements. Although facial patterns may not generate emotion-specific experience for
all emotion categories (Duclos et al., 1989; Zajonc & McIntosh, 1992), the
distinguishability of fear and anger suggests that it is possible to use muscle movements
to manipulate these emotional experiences.
1.2 Objectives
In Studies 1 through 3 I found correlational evidence showing that empathic responding
is associated with both state and trait withdrawal motivation. In Study 4, I hope to
experimentally manipulate motivational direction and to examine the impact on empathic
responding. Participants were instructed to make facial expressions associated with
approach- and withdrawal-related emotions. According to the facial feedback hypothesis,
making these faces should cause the participant to feel the associated emotion (see
McIntosh, 1996). As in Study 2, I was particularly interested in the distinction between
fear and anger expressions, as these provide a way to manipulate approach- vs.
withdrawal-related affect without simultaneously manipulating affective valence
(Stemmler et al., 2007; Wacker et al., 2003). Based on Hypothesis 3, I predicted that
participants who were instructed to make fear facial expressions would show more
empathic concern than participants instructed to make anger faces.
2 Method
2.1 Participants
Participants (N = 305) were recruited online from the United States using Mechanical
Turk and received monetary compensation for their participation (179 female, Mage =
34.46, SDage = 12.42). Twenty-eight participants were excluded because they failed to
complete the experiment (N = 3) or because they reported that they were unable to hold
the facial expression for more than 40% percent of the time (N = 25).
2.2 Procedure
45
Participants were randomly assigned to one of seven groups. For six of these groups,
participants were instructed to make and hold a specific facial muscle configuration at
various points during the experiment, while in the seventh group participants were not
required to do this (no movement control group, N = 48). The facial muscle
configurations corresponded to one of five emotions (sadness, N = 40; happiness, N = 39;
fear, N = 31; disgust, N = 44; anger, N = 37) or to no specific emotion (movement control
group, N = 38; see Appendix A for movement instructions). No mention of particular
emotions or emotion related words (i.e. smile) was made to the participants.
First, participants were given a chance to practice the facial muscle configuration. Then,
they were told that they would view four images of African children taken from a child
sponsorship website. Before each image, participants were presented with the movement
instructions and were asked to make the facial muscle configuration and hold it while
they responded to the following items. They then used a 5-point scale (1 = strongly
disagree, 5 = strongly agree) to indicate the degree to which they felt empathic concern
towards the child in the image (moved, sympathetic, compassionate, warm, tender, soft-
hearted). Combining these items across the four images yielded a reliable composite
index of empathic concern, α = .98. After each set of ratings participants were told to take
a moment to relax their facial muscles.
To test if the movement instructions were causing participants to experience the
associated emotions, participants were asked to make and hold the facial muscle
configuration one more time, during which they used a 5-point scale to rate the extent to
which they felt happy, surprised, disgusted, sad, fearful, and angry. Subsequently,
participants entered demographic information and indicated the percentage of time they
felt that they were able to hold the facial expression during the experiment (1 = 0-20%, 2
= 20-40%, 3 = 40-60%, 4 = 60-80%, 5 = 80-100%).
3 Results First, I conducted a one-way ANOVA to explore the effects of the facial movement
manipulation on empathic concern towards the images. For this analysis, the overall
ANOVA was not significant, F(6, 270) = 1.53, p = .168 (Figure 5). Based on the a priori
46
prediction that withdrawal-related facial expressions would be associated with greater
empathic concern than approach-related facial expressions, I conducted two linear
contrasts. In the first I compared sadness, fear, and disgust to happiness and anger. This
contrast was not significant, t(1, 270) = 1.47, p = .142. In the second I ran a contrast
comparing just fear and anger as this pair of emotions provides an effective way of
comparing approach and withdrawal emotional states without confounding motivational
direction and emotional valence (Wacker et al., 2003). This analysis revealed a
significant difference between fear (M = 3.67, SD = .92) and anger (M = 3.08, SD =
1.24), t(270) = 2.47, p = .014. Linear contrasts comparing fear to movement control and
anger to movement control revealed no significant differences ts < 1.6, ps > .1.
To see if the fear and anger facial movement instructions caused participants to actually
experience the associated emotions I conducted two contrasts comparing the degree to
which these facial muscle configurations evoked fear and anger when participants were
not viewing images. This analysis showed that the fear configuration (M = 1.87, SD =
1.26) evoked more fear than the anger configuration (M = 1.49, SD = .77), but this
difference did not reach significance t(270) = 1.65, p = .101. Unexpectedly, the fear
condition (M = 2.55, SD = 1.43) also evoked marginally more anger than the anger
condition (M = 2.03, SD = 1.12), t(270) = 1.78, p = .076.
I then attempted to determine if the relationship between fear and anger still held when I
only included participants for whom the manipulation worked as intended. As such, I did
a second analysis including only participants who showed equal or greater fear than anger
for the fear condition, and equal or greater anger than fear for the anger condition. I also
excluded participants in the neutral movement condition if they reported ratings of 4 or
higher on any of the five emotions. This resulted in the exclusion of an additional 15
participants from the fear group, 2 participants from the anger group, and 14 participants
from the neutral movement group. I then conducted a one-way ANOVA on this subset of
participants. For this analysis, the overall ANOVA was not significant, F(6, 239) = 1.57,
p = .167. The linear contrast comparing fear and anger revealed a significant difference
between fear (M = 3.65, SD = 1.05) and anger (M = 3.05, SD = 1.27), t(239) = 1.99, p =
.048. Linear contrasts comparing fear to movement control and anger to movement
47
control revealed a marginal difference between fear (M = 3.65, SD = 1.05) and movement
control (M = 3.09, SD = .85), t(239) = 1.72, p = .087, but no significant difference
between anger and movement control, t = .17, p = .87.
4 Discussion In line with my predictions, I found that when participants made fearful facial
expressions they reported stronger empathic reactions to the images than when
participants made angry facial expressions. These results offer the first evidence that
manipulating approach- and withdrawal-related affect can influence empathic
responding. While these results provide initial support for a causal connection between
withdrawal motivation and empathic concern, some inconsistencies in these results
warrant attention. The manipulation check showed that fear expressions generated more
fear than anger expressions, but also more anger than anger expressions. The fact that I
obtained the predicted effects for empathic concern despite these patterns of self-reported
affect suggests that the influence of facial expressions on empathy may not be mediated
by self-reported affect, and may be influenced by more automatic affective processes.
This explanation is consistent with the fact that the relationship between the fear and
anger conditions showed very little change upon removing participants who didn’t report
the expected emotional response to the fear and anger facial expressions.
As with Study 2, an alternative way to interpret these results is to suggest that anger is
associated with dampened empathy compared to fear because of its inherent anti-social
nature. Again, however, this explanation is unlikely given the potential for anger to take
on prosocial characteristics in the context of injustice, and given the anti-social nature of
fear (Eisenberger & Lieberman, 2004; Vitaglione & Barnett, 2003). A second alternative
interpretation for these findings, and those in Study 2, is that empathic concern is
dampened by approach motivation, rather than encouraged by withdrawal motivation.
The secondary analysis of the subset of participants who responded in the predicted
manner to the manipulation showed that fear marginally heightened empathy relative to a
movement control group, while anger had no significant dampening effect. Still, the
possibility that approach may dampen empathic reactions remains plausible, and will be
addressed in more detail in the general discussion.
48
Despite some discrepancies, the results from this final, experimental study suggest that
withdrawal motivation may have a causal influence on empathic concern. This
corroborates findings from the first three studies, which provide convergent evidence that
empathic concern is related to both state and trait measures of withdrawal motivation.
Taken together, these four studies provide consistent support for the overarching
hypothesis that empathic concern stems from withdrawal-motivated escape tendencies.
49
Chapter 6: General Discussion
1 Summary At the outset of these investigations I proposed that empathic reactions have adaptive
value above and beyond their impact on helping behavior and resultant indirect fitness
benefits. Based on the idea that emotional reactions to the environment facilitate adaptive
behaviors – fear and disgust, for instance, facilitate escape and withdrawal – I suggested
that catching these emotional reactions from a person who shares one’s environment
should also facilitate one’s own adaptive behaviors. In other words, other people who are
present within the same environmental context can provide second-hand information
about how to behave adaptively, and empathic reactions constitute a process by which
that information can be utilized.
Based on research on the negativity bias (Rozin & Royzman, 2001), which posits that
evolutionary pressure to avoid threat is stronger than pressure to obtain reward, I
suggested threat-avoidance should be the primary driver of empathic responding. Thus, I
hypothesized that emotional contagion, as well as downstream reactions of empathic
concern, should be related to processes of threat-avoidance and withdrawal. Results of
four studies showed that this is, in fact, the case. In Studies 1 and 2, I examined
dispositional indicators of approach and withdrawal motivation, and determined the
relationship between these variables and empathic responding. In Study 1, I found that a
neural correlate of withdrawal motivation – right-frontal EEG asymmetry – was
predictive of people’s empathic responses to charity photos. Furthermore, this
relationship was mediated by sadness, a reaction that is representative of a basic
emotional contagion reaction. Thus, these findings suggest that dispositional withdrawal
motivation makes people more susceptible to emotional contagion, at least in response to
targets experiencing withdrawal-related emotions like sadness (c.f. Harmon-Jones &
Allen, 1998) and distress. This initial contagion reaction is then predictive of the
empathic concern response, which involves the additional step of making a distinction
between the self and the target (de Waal, 2008).
50
In Study 2, I conducted a conceptual replication of Study 1, this time using measures of
dispositional emotional reactivity as indicators of approach and withdrawal motivational
tendencies. Here, I attempted to expand on my initial findings by addressing two
unanswered questions. First, did I find a relationship between right-frontal asymmetry
and empathy because empathy is related to negative affect, as the emotional valence
model of frontal EEG asymmetry would predict, or did I find this relationship because
empathy is related to withdrawal affect, as the motivational direction model of frontal
EEG asymmetry would predict? Second, does withdrawal motivation predict empathic
concern only in contexts in which the target is also experiencing withdrawal-related
emotions, or does it predict empathic concern in positive contexts as well?
Here, I focused specifically on the emotions of fear and anger as these emotions share the
same negative valence, but differ in terms of their motivational direction, with fear
reflecting withdrawal motivation, and anger reflecting approach motivation. I found that
fear predicted emotional contagion – both positive and negative – and that this contagion
reaction mediated the indirect relationship between fear and empathic concern.
Furthermore, I found that physical aggression, but not other subscales of the AQ, was a
negative predictor of empathic concern towards both positive and negative targets, again
mediated through emotional contagion. These relationships suggest that withdrawal-
related emotional tendencies are predictive of greater emotional contagion, which is in
turn predictive of empathic concern, whereas approach-related emotional tendencies have
the opposite relationship with empathic reactions. Consistent with a motivational-
direction interpretation of Study 1, these findings held when controlling for positive and
negative affect, suggesting that empathy is related to withdrawal motivation specifically,
and not negative affect generally.
In Study 3, I moved away from dispositional measures of withdrawal motivation and
explored state facial reactions towards targets using facial EMG. Here I found that
suffering images, as compared to non-suffering images, elicited a greater empathic
response and also stronger activity in the levator labii and corrugator supercilli facial
muscle regions – regions associated with disgust and general negative affect,
respectively. I found that greater levator labii activity was predictive of greater empathic
51
responding to suffering compared to non-suffering images, a relationship that was
mediated by feelings of sadness. Mirroring the results I obtained at a dispositional level
of analyses, these results suggest the following process: a strong withdrawal reaction,
reflected by the disgust facial reaction, predicts greater emotional contagion, and then
greater empathic concern.
Finally, in Study 4 I attempted to experimentally manipulate state levels of approach- and
withdrawal-related emotions in order to investigate whether these variables can have a
casual influence on empathic responding. Focusing again on fear and anger, I found that
people who made facial muscle configurations consistent with fear showed greater
empathic concern than those who made configurations consistent with anger. These
results further corroborated findings from the first three studies, and provided evidence
that manipulating motivational direction via emotional facial expression can influence the
degree of empathic concern a person feels. Specifically, withdrawal emotions like fear
encourage empathic concern relative to approach emotions like anger.
Integrating the findings from these four studies, I find evidence for the relationship
between empathy and withdrawal motivation across two levels of analysis (state and
trait), across two types of study design (correlational and experimental), and across
multiple methodological approaches (self-report, psychophysiological, and
neuroscientific). Thus, there is substantial convergence indicating that empathic concern
stems from a basic motivational system governing withdrawal and escape. Considered in
a broader theoretical context, these findings suggest directions for future research that
have the potential to further expand our understanding of the driving forces behind
empathic concern.
2 Limitations The studies described herein have provided converging evidence that empathy reflects
withdrawal motivation, but they also have limitations that raise further questions and
suggest avenues for future research. First, in all four studies emotional contagion and
empathic concern were measured using self-report responses to images. Although this
scenario may give us insight into the way that people respond in analogous situations
52
outside the laboratory – for instance, when reacting to charity advertisements – it is still
unclear how these findings would translate to contexts in which the target is present and
involved in the interaction. I suspect that in a real-world interaction scenario, the effects
we have documented here would be stronger, given that emotional reactions would likely
be enhanced, and the potential for the partner to provide information about the current
environment would be heightened. Nevertheless, this possibility remains to be
experimentally tested.
The experimental context used in these studies may also limit the external validity of our
results in that participants don’t have a clear option to avoid the empathy-inducing
situation, as they often would in real-life interactions (Cesario et al., 2010). It is possible
that people high on withdrawal-motivation are responding with emotional contagion and
empathic concern in our studies because they don’t have other emotion-regulation
strategies – such as escape – available to them (unless they choose not to complete the
experiment). This raises interesting questions about whether people who exhibit high
levels of withdrawal motivation actually display more empathy in real-world contexts, or
whether they regulate this affect in other ways, thereby avoiding the need to feel empathy
(Cameron & Payne, 2011).
One further limitation of this series of studies is that approach motivation was only
independently assessed using the emotion of anger. Anger is theoretically interesting in
the context of the questions addressed here, given that it is a negative emotion that is also
associated with approach-motivation (Stemmler et al., 2007; Wacker et al., 2003).
Nevertheless, anger may not be representative of all approach-motivational emotions
when it comes to its relationship with empathy. The approach-motivational aspects of
anger are reflected in efforts to harm the target (Harmon-Jones & Sigelman, 2001),
raising the possibility that its negative relationship with empathy may be descriptive of
aggressive, but not appetitive forms of approach-motivational affect. In fact, based on my
theoretical account, which posits that others’ emotions can provide second-hand
information about the environment, it seems plausible that it would be adaptive to show
emotional contagion for appetitive emotions that imply the presence of reward. For
instance, if one person observes someone else eagerly approaching an ambiguous
53
stimulus, it could be adaptive to adopt this approach-motivational affect. Assessing other
forms of approach-motivational affect, particularly those implicated in pursuing reward,
could clarify this possibility.
3 Future Directions
3.1 Threat vs. Challenge
Overall, the results of the studies discussed herein have supported the view that empathic
concern reflects withdrawal motivation. Nevertheless, there may be some instances where
the behavioral outcomes of empathic concern exhibit approach-motivational tendencies,
as when a person rushes over to help their friend who has been injured, or when a parent
reaches out to their crying child. Viewed through the lens of the stress and coping
literature, a scenario in which one is faced with the suffering or distress of another person
could be characterized as a stressor – a situation in which one’s evaluation of the ratio of
resources to demands would determine the resultant behavioral and physiological
reaction (Tomaka, Blascovich, Kelsey, & Leitten, 1993; Lazarus & Folkman, 1984).
When a person perceives their resources to be adequate (or more than adequate) in
addressing the present demands, they are making a challenge appraisal, but when they
perceive their resources to be inadequate relative to the demands, they are making a
threat appraisal. Challenge and threat appraisal are associated with different physiological
and performance outcomes, with challenge predicting efficient cardiovascular
functioning and strong performance, and threat predicting inefficient cardiovascular
functioning and weak performance (Tomaka et al., 1993). Thus, the type of appraisal that
one makes in response to another person in need may have important consequences for
the type of action that they take.
An intriguing possibility is that when one is faced with the suffering of another person,
the type of appraisal one makes will determine whether one helps or flees the situation.
Past research provides some support for this hypothesis. For instance, a person’s feelings
of self-efficacy – essentially reflective of one’s evaluation of resources – are an important
determinant of whether or not they agree to help someone in need (Caprara & Steca,
2005; 2007). Furthermore, threat responses tend to result in disengagement and
54
avoidance, which would be consistent with a fleeing response (Lazarus & Folkman,
1984; Folkman, Lazarus, Dunkel-Schetter, DeLongis, & Gruen, 1986). Thus, threat and
challenge appraisals may encourage helping and fleeing responses, respectively.
Along these lines, it is also possible that the behavioral options available to an individual
will determine how empathy will manifest itself in action (or inaction). For instance,
people who are high on dispositional withdrawal might escape empathy-inducing
situations if the environment afforded that option (Batson, 1987; Cesario et al., 2010;
Cialdini et al., 1987). In all of the studies discussed herein, participants did not have clear
options for escaping the situation, aside from discontinuing the experiment. It is possible
that if this option were more available, participants would have chosen this as a way to
avoid feeling empathic emotion (Cialdini et al., 1987; Cameron & Payne, 2011). Future
research exploring this possibility has the potential to provide important insights into the
circumstances and dispositional characteristics that lead people to help or ignore people
in need.
3.2 Approach Motivation and the Inhibition of Empathy
Although I have interpreted these results as suggestive of a positive link between
withdrawal motivation and empathy, I have also accumulated evidence of a negative link
between approach motivation and empathy. Relative to withdrawal motivation, indicators
of approach motivation were consistently related to a dampened empathic response, and
this was true even when approach was assessed without reference to withdrawal, as with
self-reported physical aggression in Study 2.
Precedent for this possibility is offered by research on the link between power motivation
and empathy. Power, although not synonymous with approach, has been linked with
approach motivational systems, and can be seen as a characteristic manifestation of BAS.
Based on their analysis of how power influences behavior, Keltner, Gruenfeld and
Anderson (2003) claim that high power is associated greater approach and dampened
inhibition, constructs associated with BAS and BIS activity, respectively. High power has
also been found to decrease perspective taking and empathic responding (Galinsky,
55
Magee, Inesi, & Gruenfeld, 2006), suggesting that approach motivation may discourage
empathic responsivity towards others.
3.3 Self-Regulation of Empathy
Consistent with the idea of empathy-inducing situations as stressors, these findings
strongly suggest that empathy – at least in response to others’ suffering – is an aversive
emotional experience. This suggests the possibility that people use emotion regulation
strategies to reduce empathic reactions in much the same way they do for other types of
negative affect (Gross, 1998; Cameron & Payne, 2011). If this is the case, it suggests that
helping may, in a sense, be an emotion regulation strategy, aimed at reducing ones’ own
personal distress. Indeed, this is the account proposed by advocates of distress-reduction
models of helping (Cialdini et al., 1973; Piliavin et al., 1981). Furthermore, it is
consistent with findings showing that people will engage in emotion regulation strategies
to prevent themselves from feeling overwhelming distress in the face of large numbers of
suffering individuals (Cameron & Payne, 2011).
Conceptualizing empathy in this way also suggests that things that diminish emotion
regulation capacity, such as ego-depletion and cognitive load – should impair people’s
ability to regulate empathy, and thus lead to greater expressions of empathic concern.
Potentially, if ego-depletion and cognitive load also dampen behavioral efforts at emotion
regulation, these phenomena should result in decreased helping responses as well.
Empirical tests of these possibilities could lead to an understanding of how ego-depleting
environments – like those in which one is consistently the target of stigma – could
effectively act like a double-edged sword, augmenting distressing empathic reactions, and
diminishing helping behaviors (Inzlicht, Tullett, Legault, & Kang, 2011).
4 Conclusion In four studies, I have provided evidence that empathic concern reflects withdrawal
motivation – the motivation to evade punishment and avoid threat. In light of theoretical
accounts of the adaptive value of emotional contagion, these findings are consistent with
the possibility that humans have motivational systems for detecting threat, and that the
56
emotions of others can provide an important indication of potential danger. Here, I
propose that empathic concern stems from these motivational systems, and provide
evidence that people with greater reactivity in those systems show stronger empathic
reactions towards others.
My conceptualization of empathic concern as a withdrawal-motivated reaction is a
significant departure from theories detailing the adaptive value of empathy, which largely
focus on empathy’s ability to encourage prosociality, and thereby generate indirect fitness
benefits. In addition to providing a novel theoretical perspective that could deepen our
understanding of the empathic process, the findings reported herein also suggest
interesting and valuable avenues for future research – avenues that could lead to a more
thorough understanding of when empathy leads to productive, prosocial behaviors.
Although, in a way, the proposed theoretical account characterizes empathy as a “selfish”
process, it may contribute to a truer understanding of human empathy, and thereby
suggest ways in which those “selfish” processes can be harnessed for selfless ends.
57
References
Adolphs, R., Tranel, D., Hamann, S., Young, A. W., Calder, A. J., Phelps, E. A.,…
Damasio, A. R. (1999). Recognition of facial emotion in nine individuals with
bilateral amygdala damage. Neuropsychologia, 37(10), 1111-1117.
Allen, J. J. B., Coan, J. A., & Nazarian, M. (2004). Issues and assumptions on the road
from raw signals to metrics of frontal EEG asymmetry in emotion. Biological
Psychology, 67, 183-218.
Allen, J. J. B., Iacono, W. G., Depue, R. A., Abrisi, M. (1993). Regional
electroencephalographic asymmetries in bipolar seasonal affective disorder before
and after exposure to bright light. Biological Psychiatry, 33, 642-646.
Ames, D. L., Jenkins, A. C., Banaji, M. R., & Mitchell, J. P. (2008). Taking another
person’s perspective increases self-referential neural processing. Psychological
Science, 19(7), 642-644.
Amodio, D. M., & Frith, C. D. (2006). Meeting of the minds: The medial frontal cortex
and social cognition. Nature Reviews Neuroscience, 7, 268-277.
Baron-Cohen, S. (1995). Mind-blindness: An essay on autism and theory of mind.
Cambridge, MA: MIT Press.
Baron-Cohen, S., Ring, H. A., Bullmore, E. T., Wheelwright, S., Ashwin, C., &
Williams, S. C. R. (2000). The amygdala theory of autism. Neuroscience and
Biobehavioral Reviews, 24(3), 355-364.
Barrett, K. C., & Campos, J. J. (1987). Perspectives on emotional development II: A
functionalist approach to emotions. In J. D. Osofsky (Ed.), Handbook of infant
development (2nd ed., pp. 555-578). Oxford: John Wiley & Sons.
Batson, C. D. (1987). Prosocial motivation: Is it ever truly altruistic? In L. Berkowitz
(Ed.) Advances in experimental social psychology (Vol. 20, pp. 65-122). San
Diego, CA: Academic Press.
Batson, C. D., Lishner, D. A., Cook, J., & Sawyer, S. (2005). Similarity and nurturance:
Two possible sources of empathy for strangers. Basic and Applied Social
Psychology, 17(1), 15-25.
58
Batson, C. D., Turk, C. L., Shaw, L. L., & Klein, T. R. (1995). Information function of
empathic emotion: Learning that we value the other’s welfare. Journal of
Personality and Social Psychology, 68(2), 300-313.
Benuzzi, F., Lui, F., Duzzi, D., Nichelli, P. F., & Porro, C. A. (2008). Does it look painful
or disgusting? Ask your parietal and cingulate cortex. Journal of Neuroscience, 28,
923-931.
Brown, S.-L., & Schwartz, G. E. (1980). Relationships between facial electromyography
and subjective experience during affective imagery. Biological Psychology, 11(1),
49-62.
Bruder, G. E., Fong, R., Tenke, C. E., Leite, P., Towey, J. P., Stewart, J. E.,… Quitkin, F.
M. (1997). Regional brain asymmetries in major depression with or without an
anxiety disorder: A quantitative electroencephalographic study. Biological
Psychiatry, 41, 939-948.
Brunet, E., Sarfati, Y, Hardy-Baylé, M.-C., & Decety, J. (2000). A PET investigation of
the attribution of intentions with a nonverbal task. NeuroImage, 11(2), 157-166.
Buss, A. H., & Perry, M. (1992). The aggression questionnaire. Journal of Personality
and Social Psychology, 63(3), 452-459.
Cameron, C. D., & Payne, B. K. (2011). Escaping affect: How motivated emotion
regulation creates insensitivity to mass suffering. Journal of Personality and Social
Psychology, 100, 1-15.
Cacioppo, J. T., Berntson, G. G., Larsen, J. T., Poehlmann, K. M., & Ito, T. A. (2000).
The psychophysiology of emotion. In R. Lewis & J. M. Haviland-Jones (Eds.), The
handbook of emotion (2nd ed., pp. 173-191). New York, NY: Guilford Press.
Caprara, G. V., & Steca, P. (2005). Self-efficacy beliefs as determinants of prosocial
behavior conducive to life satisfaction across ages. Journal of Social & Clinical
Psychology, 24(2), 191-217.
Caprara, G. V., & Steca, P. (2007). Prosocial agency: The contribution of values and self-
efficacy beliefs to prosocial behavior across ages. Journal of Social & Clinical
Psychology, 26(2), 218-239.
Carruthers, P. & Smith, P. K. (1996). Theories of theories of mind. Cambridge:
Cambridge University Press.
59
Carver, L. J., & Vaccaro, B. G. (2007). 12-month-old infants allocate increased neural
resources to stimuli associated with negative adult emotion. Developmental
Psychology, 43, 54–69.
Cesario, J., Plaks, J. E., Hagiwara, N., Navarette, C. D., & Higgins, E. T. (2010). The
ecology of automaticity: How situational contingencies shape action semantics and
social behavior. Psychological Science, 2(9), 1131-1317.
Church, R. M. (1959). Emotional reaction of rats to the pain of others. Journal of
Comparative Physiological Psychology, 52, 132-134.
Cialdini, R. B., Brown, S. L., Lewis, B. P., Luce, C., & Neuberg, S. L. (1997).
Reinterpreting the empathy-altruism relationship: When one into one equals
oneness. Journal of Personality and Social Psychology, 73(3), 481-494.
Cialdini, R. B., Darby, B. K., & Vincent, J. E. (1973). Transgression and altruism: A case
for hedonism. Journal of Experimental Social Psychology, 9(6), 502-516.
Cialdini, R. B., Schaller, M., Houlihan, D., Arps, K., Fultz, J., Beaman, A. L. (1987).
Empathy-based helping: Is it selflessly or selfishly motivated? Journal of
Personality and Social Psychology, 52(4), 749-758.
Coan, J. A., & Allen, J. J. B. (2003). Frontal EEG asymmetry and the behavioral
activation and inhibition systems. Psychophysiology, 40, 106-114.
Coan, J. A., Allen, J. J. B., & Harmon-Jones, E. (2001). Voluntary facial expressions and
hemispheric asymmetry over the frontal cortex. Psychophysiology, 38, 912-925.
Cunningham, W. A., Johnson, M. K., Raye, C. L., Gatenby, J. C., Gore, J. C., & Banaji,
M. R. (2004). Separable neural components in the processing of black and white
faces. Psychological Science, 15(12), 806-813.
Cunningham, W. A., Raye, C. L., & Johnson, M. K. (2004). Implicit and explicit
evaluation: fMRI correlates of valence, emotional intensity, and control in the
processing of attitudes. Journal of Cognitive Neuroscience, 26(10), 1717-1729.
Darwin, C. (1872). The expression of emotions in man and animals. New York, NY:
Philosophical Library.
Davidson, R. J. (1993). The neuropsychology of emotion and affective style. In M. Lewis
& J. M. Haviland (Eds.), Handbook of emotions (2nd ed., pp. 143-154). New York,
NY: Guilford Press.
60
Davidson, R. J. (1995). Cerebral asymmetry, emotion, and affective style. In R. J.
Davidson, & K. Hudgahl (Eds.), Brain asymmetry (pp. 361-387). Cambridge, MA:
MIT Press.
Davidson, R. J., Ekman, P., Saron, C. D., Senulis, J. A., & Friesen, W. V. (1990).
Approach-withdrawal and cerebral asymmetry: Emotional expression and brain
physiology: I. Journal of Personality and Social Psychology, 58(2), 330-341.
Davidson, R. J., Marshall, J. R., Tomarken, A. J., & Henriques, J. B. (2000). While a
phobic waits: Regional brain differences in electrical and autonomic activity in
social phobics during anticipation of public speaking. Biological Psychiatry, 47(2),
85-95.
Davidson, R. J., Schaffer, C. E., & Saron, C. (1985). Effects of lateralized presentations
of faces on self-reports of emotion and EEG asymmetry in depressed and non-
depressed subjects. Psychophysiology, 22, 353-364.
Davies M., & Stone, T. (1995a). Folk psychology: The theory of mind debate. Oxford:
Blackwell Publishers Ltd.
Davies, M., & Stone, T. (1995b). Mental simulation: Evaluations and applications.
Oxford: Blackwell Publishers Ltd.
Davis, M. (1992). The role of the amygdala in fear and anxiety. Annual Review of
Neurscience, 15, 353-375.
Dawson, G., Panagiotides, H., Klinger, L. G., & Hill, D. (1992). The role of frontal lobe
functioning in the development of infant self-regulatory behavior. Brain and
Cognition, 20, 152-175.
de Gelder, B., Snyder, J., Greve, D., Gerard, G., & Hadjikhani, N. (2004). Fear fosters
flight: A mechanism for fear contagion when perceiving emotion expressed by a
whole body. Proceedings of the National Academy of Sciences, 101, 16701-16706.
de Waal, F. B. M. (2008). Putting the altruism back into altruism: The evolution of
empathy. Annual Review of Psychology, 59, 279-300.
Decety, J., & Lamm, C. (2006). Human empathy through the lens of social neuroscience.
Scientific World Journal, 6, 1146-1163.
Decety, J., & Lamm, C. (2007). The role of the right temporoparietal junction in social
interaction: How low-level computational processes contribute to meta-cognition.
61
The Neuroscientist, 13(6), 580-593.
Dimberg, U. (1997). Facial reactions: Rapidly evoked emotional responses. Journal of
Psychophysiology, 11(2), 115-123.
Dimberg, U. (1982). Facial reactions to facial expressions. Psychophysiology, 19(6), 643-
647.
Dimberg, U., & Thunberg, M. (1998). Rapid facial reactions to emotional facial
expressions. Scandanavian Journal of Psychology, 39(1), 39-45.
Duclos, S. E., Laird, J. D., Schneider, E., Sexter, M., Stern, L., Van Lighten, O. (1989).
Emotion-specific effects of facial expressions and postures on emotional
experience. Journal of Personality Social Psychology, 57(1), 100-108.
Eisenberger, N. I., & Lieberman, M. D. (2004). Why rejection hurts: A common neural
alarm system for physical and social pain. Trends in Cognitive Sciences, 8(7), 294-
300.
Ekman, P. (1992). Facial expressions in emotion: New findings, new questions.
Psychological Science, 3, 34-38.
Elliot, A. J., & Church, M. A. (1997). A hierarchical model of approach and avoidance
achievement motivation. Journal of Personality and Social Psychology, 72, 218-
232.
Elliot, A. J., & Thrash, T. M. (2002). Approach-avoidance motivation in personality:
Approach and avoidance temperaments and goals. Journal of Personality and
Social Psychology, 82, 804-818.
Eslinger, P. J., Moore, P., Troiani, V., Antani, S., Cross, K., Kwok, S., & Grossman, M.
(2007). Oops! Resolving social dilemmas in frontotemporal dementia. Journal of
Neurology, Neurosurgery and Psychiatry, 78, 457-460.
Flavell, J. H., & Miller, P. H. (1998). Social cognition. In D. Kuhn & R. Siegler (Vol.
Eds.), W. Damon (Series Ed.) Handbook of child psychology: Vol. 2. Cognition,
perception, and language (pp. 851-898). New York: Wiley.
Folkman, S., Lazarus, R. S., Dunkel-Schetter, C., DeLongis, A., & Gruen, R. J. (1986).
Dynamics of a stressful encounter: Cognitive appraisal, coping, and encounter
outcomes. Journal of Personality and Social Psychology, 50(5), 992-1003.
Fox, N. A., & Davidson, R. J. (1988). Patterns of brain electrical activity during facial
62
signs of emotion in 10-month-old infants. Developmental Psychology, 24(2), 230-
236.
Frederickson, B. L. (2001). The role of positive emotions in positive psychology: The
broaden-and-build theory of positive emotions. American Psychologist, 56(3), 218-
226.
Fridja, N. H., Kuipers, P., & ter Schure, E. (1989). Relations among emotion, appraisal,
and emotional action readiness. Journal of Personality and Social Psychology,
57(2), 212-228.
Fridlund, A. J., & Cacioppo, J. T. (1986). Guidelines for electromyographic research.
Psychophysiology, 23(5), 567-587.
Fultz, J., Schaller, M., & Cialdini, R. (1988). Empathy, sadness, and distress: Three
related but distinct vicarious affective responses to another’s suffering. Personality
and Social Psychology Bulletin, 14, 312-325.
Gable, P. A., & Harmon-Jones, E. (2008). Approach-motivated positive affect reduces
breadth of attention. Psychological Science, 19, 476-482.
Gable, P. A., & Harmon-Jones, E. (2010). The effect of low versus high approach-
motivated positive affect on memory for peripherally versus centrally presented
information. Emotion, 10(4), 599-603.
Galinsky, A. D., Magee, J. C., Inesi, M. E., & Gruenfeld, D. H. (2006). Power and
perspectives not taken. Psychological Science, 17(12), 1068-1074.
Gallagher, H. L. & Frith, C. D. (2003). Functional imaging of ‘theory of mind.’ Trends in
Cognitive Sciences, 7(2), 77-83.
Geer, J. H. (1965). The development of a scale to measure fear. Behavior Research and
Therapy, 3(1), 45-53.
Gehring, W. J., Goss, B., Coles M. G. H., Meyer, D. E., & Donchin, E. (1993). A neural
system for error detection and compensation. Psychological Science, 4, 385-390.
Goetz, J. L., Keltner, D., & Simon-Thomas, E. (2010). Compassion: An evolutionary
analysis and empirical review. Psychological Bulletin, 136, 351-374.
Goldman, A. I. (2006). Simulating minds: The philosophy, psychology, and neuroscience
of mind-reading. Oxford: Oxford University Press.
Goldstein, K. (1939). The Organism: An Holistic Approach to Biology, Derived from
63
Pathological Data in Man. New York, NY: American Book Company.
Gopnik, A., & Meltzoff, A. N. (1997). Words, thoughts, and theories. Cambridge, MA:
MIT Press.
Gratton, G., Coles, M. G. H., & Donchin, E. (1983). A new method for off-line removal
of ocular artifact. Electroencephalography and Clinical Neurophysiology, 55, 458-
484.
Gray, J. A. (1987). The psychology of fear and stress (2nd ed.). Cambridge, UK:
Cambridge University Press.
Gray, J. A., & McNaughton, N. (2000). The Neuropsychology of Anxiety: An Enquiry
into the Functions of the Septo-Hippocampal System. New York, NY: Oxford
Press.
Gross, J. J. (1998). The emerging field of emotion-regulation: An integrative review.
Review of General Psychology, 2(3), 271-299.
Gutsell, J. N., & Inzlicht, M. (2010). Empathy constrained: Prejudice predicts reduced
mental simulation of actions during observation of outgroups. Journal of
Experimental Social Psychology, 46, 841-845.
Gutsell, J. N., & Inzlicht, M. (2012). Perspective-taking reduces group biases in neural
motor resonance. Manuscript submitted for publication.
Gutsell, J. N., & Inzlicht, M. (in press). Intergroup differences in the sharing of emotive
states: Neural evidence of an empathy gap. Social Cognitive Affective
Neuroscience.
Hajcak, G., & Foti, D. (2008). Errors are aversive: Defensive motivation and the error-
related negativity. Psychological Science, 19, 103-108.
Hajcak, G., McDonald, N., & Simons, R. F. (2003). Anxiety and error-related brain
activity. Biological Psychology, 64, 77–90.
Hajcak, G., McDonald, N., & Simons, R. F. (2004). Error-related psychophysiology and
negative affect. Brain and Cognition, 56, 189–197.
Hamilton, W. D. (1964). The genetical evolution of social behavior. II. Journal of
Theoretical Biology, 7(1), 17-52.
64
Harmon-Jones, E. (2004). Contributions from research on anger and cognitive dissonance
to understanding the motivational functions of asymmetric frontal brain activity.
Biological Psychology, 67, 51-76.
Harmon-Jones, E., & Allen, J. B. (1997). Behavioral activation sensitivity and resting
frontal EEG asymmetry: Covariation of putative indicators related to risk for mood
disorders. Journal of Abnormal Psychology, 106, 159-163.
Harmon-Jones, E., & Allen, J. J. B. (1998). Anger and frontal brain activity: EEG
asymmetry consistent with approach motivation despite negative affective valence.
Journal of Personality and Social Psychology, 74, 1310-1316.
Harmon-Jones, E., & Gable, P. A. (2008). Incorporating motivational intensity and
direction into the study of emotions: Implications for brain mechanisms of emotion
and cognition-emotion interactions. Netherlands Journal of Psychology, 64(4), 132-
142.
Harmon-Jones, E., Gable, P. A., & Peterson, C. K. (2010). The role of asymmetric frontal
cortical activity in emotion-related phenomena: A review and update. Biological
Psychology, 84, 451-462.
Harmon-Jones, E. & Sigelman, J. (2001). State anger and prefrontal brain activity:
Evidence that insult-related relative left-prefrontal activation is associated with
experienced anger and aggression. Journal of Personality and Social Psychology,
80, 797-803.
Harmon-Jones, E., Sigelman, J., & Bohlig, A., & Harmon-Jones, C. (2003). Anger,
coping, and frontal cortical activity: The effect of coping potential on anger-
induced left frontal activity. Cognition & Emotion, 17(1), 1-24.
Harris, L. T., & Fiske, S. T. (2006). Dehumanizing the lowest of the low: Neuroimaging
responses to extreme out-groups. Psychological Science, 17(10), 847-853.
Havas, D. A., Glenberg, A. M., Gutowski, K. A., Lucarelli, M. J., & Davidson, R. J.
(2010). Cosmetic use of botulinum toxin-A affects processing of emotional
language. Psychological Science, 21(7), 895-900.
Hecht, D. (2011). An inter-hemispheric imbalance in the psychopath’s brain. Personality
and Individual Differences, 51(1), 3-10.
65
Henrich, J. (2004). Cultural group selection, coevolutionary processes and large-scale
cooperation. Journal of Economic Behavior and Organization, 53(1), 3-35.
Henriques, J. B., & Davidson, R. J. (1990). Regional brain electrical asymmetries
discriminate between previously depressed and healthy control subjects. Journal of
Abnormal Psychology, 99, 22-31.
Henriques, J. B., & Davidson, R. J. (1991). Left-frontal hypoactivation in depression.
Journal of Abnormal Psychology, 100, 535-545.
Henriques, J. B., & Davidson, R. J. (1997). Brain electrical asymmetries during cognitive
task performance in depressed and nondepressed subjects. Biological Psychiatry,
42, 1039-1050.
Hoffman, M. L. (1975). Developmental synthesis of affect and cognition and its
implications for altruistic motivation. Developmental Psychology, 11, 607-622.
Hoffman, M. L. (1976). Empathic distress in the newborn. Developmental Psychology,
12, 175-176.
Ikes, W. (1997). Empathic Accuracy. New York, NY: Guilford Press.
Inzlicht, M., & Al-Khindi, T. (in press). ERN and the placebo: A misattribution approach
to studying the arousal properties of the error-related negativity. Journal of
Experimental Psychology: General.
Inzlicht, M., & Tullett, A. M. (2010). Reflecting on God: Religious primes can reduce
neurophysiological response to errors. Psychological Science, 21, 1184-1190.
Inzlicht, M., Tullett, A. M., Legault, L, & Kang, S. K. (2011). Lingering effects:
Stereotype threat hurts more than you think. Social Issues and Policy Review, 5(1),
227-256.
Izard, C. E. (1972). Patterns of emotions: A new analysis of anxiety and depression. San
Diego, CA: Academic Press.
Izard, C. E. (1992). Basic emotions, relations among emotions, and emotion-cognition
relations. Psychological Review, 99(3), 561-565.
Jackson, P. L., Meltzoff, A. N., & Decety, J. (2005). How do we perceive the pain of
others? A window into the neural processes involved in empathy. NeuroImage,
24(3), 771-779.
66
Jacobs, G. D., & Snyder, D. (1996). Frontal brain asymmetry predicts affective style in
men. Behavioral Neuroscience, 110, 3-6.
Janig, W. (2003). The autonomic nervous system and its coordination by the brain. In R.
J. Davidson (Ed.), Handbook of affective sciences. (pp. 135-186). New York, NY:
Oxford University Press.
Jeannerod, M. (1994). The representing brain: Neural correlates of motor intention and
imagery. Behavioral and Brain Sciences, 17(2), 187-524.
Jenkins, A. C., Macrae, C. N., & Mitchell, J. P. (2008). Repetition suppression of
ventromedial prefrontal activity during judgments of self and others. Proceedings
of the National Academy of Sciences, 105(11), 4507-4512.
Keltner, D., & Gross, J. J. (1999). Functional accounts of emotions. Cognition and
Emotion, 13(5), 467-480.
Keltner, D., Gruenfeld, D. H., & Anderson, C. (2003). Power, approach, and inhibition.
Psychological Review, 110(2), 265-284.
Kentgen, L. M., Tenke, C. E., Pine, D. S., Fong, R., Klein, R. G., & Bruder, G. E. (2000).
Electroencephalographic asymmetries in adolescents with major depression:
Influence of comorbidity with anxiety disorders. Journal of Abnormal Psychology,
109, 797-802.
Knoch, D., Pascual-Leone, A., Meyer, K., Treyer, V., & Fehr, E. (2006). Diminishing
reciprocal fairness by disrupting the right prefrontal cortex. Science, 314, 829-832.
Knutson, B., & Wimmer, G. E. (2007). Reward: Neural circuitry for social valuation. In
E. Harmon-Jones & P. Winkielman (Eds.), Social neuroscience: Integrated
biological and psychological explanations of social behavior (pp. 157-175). New
York, NY: Guilford Press.
Kornblum, S., Hasbroucq, T., & Osman, A. (1990). Dimensional overlap: Cognitive basis
for stimulus-response compatibility – a model and taxonomy. Psychological
Review, 97, 253-270.
Krebs, D. (1975). Empathy and altruism. Journal of Personality and Social Psychology,
32(6), 1134-1146.
Lamm, C., Batson, C. D., & Decety, J. (2007). The neural substrate of human empathy:
Effects of perspective-taking and cognitive appraisal. Journal of Cognitive
67
Neuroscience, 19, 42-58.
Lang, P. J. (1995). The emotion probe: Studies of motivation and attention. American
Psychologist, 50(5), 372-385.
Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2008). International affective picture
system (IAPS): Affective ratings of pictures and instruction manual. Technical
Report A-8. University of Florida, Gainesville, FL.
Lang, P. J., Greenwald, M. K., Bradley, M. M., & Hamm, A. O. (1993). Looking at
pictures: Affective, facial, visceral, and behavioral reactions. Psychophysiology,
30(3), 261-273.
Langford, D. J. (2006). Social modulation of pain as evidence for empathy in mice.
Science, 312, 1967-1970.
Larsen, J. T., Norris, C. J., & Cacioppo, J. T. (2003). Effects of positive and negative
affect on electromyographic activity over zygomaticus major and corrugator
supercilii. Psychophysiology, 40(5), 776-785.
Larson, M. J., Fair, J. E., Good, D. A., & Baldwin, S. A. (2010). Empathy and error
processing. Psychophysiology, 47, 415-424.
Lazarus, R. S. (1991). Emotion and adaptation. Oxford: Oxford University Press.
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York, NY:
Springer.
LeDoux, J. (1986). Sensory systems and emotion: A model of affective processing.
Integrative Psychiatry, 4, 237-238.
LeDoux, J. (1996). The emotional brain: The mysterious underpinnings of emotional life.
New York, NY: Simon & Schuster.
Levenson, R. W. (1994). Human emotions: A functional view. In P. Ekman & R. J.
Davidson (Eds.), The nature of emotion: Fundamental questions (pp. 123-126).
New York, NY: Oxford University Press.
Levenson, R. W. (2003). Blood, sweat, and fears: The autonomic architecture of emotion.
In P. Ekman, J. J. Campos, R. J. Davidson, & F. B. M. de Waal (Eds.), Emotions
inside out (pp. 348-366). New York, NY: The New York Academy of Sciences.
68
Levenson, R. W., Ekman, P., & Friesen, W. V. (1990). Voluntary facial action generates
emotion-specific autonomic nervous system activity. Psychophysiology, 27(4), 363-
384.
Light, S. N., Coan, J. A., Zahn-Waxler, C., Frye, C., Goldsmith, H. H., & Davidson, R. J.
(2009). Empathy is associated with dynamic change in prefrontal brain electrical
activity during positive emotion in children. Child Development, 80(4), 1210-1231.
Lindsley D. B., & Wicke, J. D. (1974). The electroencephalogram: Autonomous
electrical activity in man and animals. In R. Thompson & N. Patterson (Eds.),
Bioelectric recording techniques (pp. 3-79). New York: Academic Press.
Luu, P., Collins, P., & Tucker, D. M. (2000). Mood, personality and self-monitoring:
Negative affect and emotionality in relation to frontal lobe mechanisms of error
monitoring. Journal of Experimental Psychology: General, 129, 43–60.
Macrae, C. N., Moran, J. M., Heatheron, T. F., Banfield, J. F., & Kelley, W. M. (2004).
Medial prefrontal activity predicts memory for self. Cerebral Cortex, 14(6), 647-
654.
Maner, J. K., Luce, C. L., Neuberg, S. L., Cialdini, R. B., Brown, S., & Sagarin, B. J.
(2002). The effects of perspective taking on motivators for helping: Still no
evidence for altruism. Personality and Social Psychological Bulletin, 28, 1601-
1610.
McIntosh, D. N. (1996). Facial feedback hypotheses: Evidence, implications, and
directions. Motivation and Emotion, 20(2), 121-147.
Mukamel, R., Ekstrom, A. D., Kaplan, J., Iacobini, M., & Fried, I. (2010). Single-neuron
responses in humans during execution and observation of actions. Current Biology,
20(8), 750-756.
Muller, D., Judd, C. M., & Yzerbyt, V. Y. (2005). When moderation is mediated and
mediation is moderated. Journal of Personality and Social Psychology, 89(6), 852-
863.
Mumme, D. L., Fernald, A., & Herrera, C. (1996). Infants’ responses to facial and vocal
emotional signals in a social referencing paradigm. Child Development, 67, 3219–
3237.
Nash, K. N., McGregor, I. D., & Inzlicht, M. (2011). Left EEG asymmetry predicts
69
reduced stress and muted error-related negativity. Manuscript submitted for
publication.
Nusslock, R., Shackman, A. J., Harmon-Jones, E., Alloy, L. B., Coan, J. A., &
Abramson, L. Y. (2011). Cognitive vulnerability and frontal brain asymmetry:
Common predictors of first prospective depressive episode. Journal of Abnormal
Psychology, 120, 497-503.
Oaten, M., Stevenson, R. J., & Case, T. I. (2009). Disgust as a disease-avoidance
mechanism. Psychological Bulletin, 135(2), 303-321.
Oatley, K., & Jenkins, J. M. (1992). Human emotions: Function and dysfunction. Annual
Review of Psychology, 43, 55-85.
Olvet, D. M., & Hajcak, G. (2008). The error-related negativity (ERN) and
psychopathology: Toward an endophenotype. Clinical Psychology Review, 28(8),
1343-1354.
Oppenheimer, D. M., Meyvis, T., & Davidenko, N. (2009). Instructional manipulation
checks: Detecting satisficing to increase statistical power. Journal of Experimental
Social Psychology, 45, 867-872.
Panksepp, J. (1998). Affective neuroscience: The foundations of human and animal
emotion. New York, NY: Oxford University Press.
Panksepp, J. (2003). At the interface of the affective, behavioral, and cognitive
neurosciences: Decoding the emotional feelings of the brain. Brain and Cognition,
52, 4-14.
Panksepp, J. (2009). The trans-species core SELF: The emergence of active cultural and
neuro-ecological agents through self-related processing within subcortical-cortical
midline networks. Consciousness and Cognition, 18, 193-215.
Pellegrino, G., Fadiga, L., Fogassi, V., Gallese, V., & Rizzolatti, G. (1992).
Understanding motor events: A neurophysiological study. Experimental Brain
Research, 91(1), 176-180.
Peterson, C. K., Shackman, A. J., & Harmon-Jones, E. (2008). The role of asymmetrical
frontal cortical activity in aggression. Psychophysiology, 45, 86-92.
Phelps, E. A., O’Connor, K. J., Cunningham, W. A., Funayama, E. S., Gatenby, J. C.,
Gore, J. C., & Banaji, M. R. (2000). Performance on indirect measures of race
70
evaluation predicts amygdala activation. Journal of Cognitive Neuroscience, 12(5),
729-738.
Phillips, R. G., & LeDoux, J. E. (1992). Differential contribution of amygdala and
hippocampus to cued and contextual fear conditioning. Behavioral Neuroscience,
106(2), 274-285.
Pickard, G. E., & Silverman, A.-J. (1981). Direct retinal projections to the hypothalamus,
piriform cortex, and accessory optic nuclei in the golden hamster as demonstrated
by a sensitive anterograde horseradish peroxidase technique. The Journal of
Comparative Neurology, 196(1), 155-172.
Piliavin, J.A., Dovidio, J. F., Gaertner, S. L., & Clark, R. D. III. (1981). Emergency
intervention. New York, NY: Academic.
Plutchik, R. (1980). Emotion: A psychoevolutionary synthesis. New York: Harper and
Row.
Plutchik, R. (1990). Evolutionary bases of empathy. In N. Eisenberg (Ed.), Empathy and
its development. Cambridge, UK: Cambridge University Press.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling procedures for
assessing and comparing indirect effects in multiple mediator models. Behavioral
Research Methods, 40, 879-891.
Preston, S. D., & de Waal, F. B. M. (2002). Empathy: Its ultimate and proximal bases.
Behavioral and Brain Sciences, 25, 1-72 (2002).
Price, G. R. (1970). Selection and covariance. Nature, 227, 520-521.
Price, G. R. (1972). Extension of covariance selection mathematics. Annals of Human
Genetics, 35(4), 485-490.
Prinz, W. (1987). Ideo-motor action. In H. Heuer & A. F. Sanders (Eds.) Perspectives on
perception and action. Hillsdale, NJ: Lawrence Erlbaum Associates.
Prinz, W. (1997). Perception and action planning. European Journal of Cognitive
Psychology, 9(2), 129-154.
Quirin, M., Kazén, M., Hardung, N., & Kuhl, J. Hemispheric asymmetry and social
motivation: Relationships of the affiliation and power motive with resting EEG
alpha. Manuscript submitted for publication.
Richeson, J. A., Todd, A. R., Trawalter, S., & Baird, A. A. (2008). Eye-gaze direction
71
modulates race-related amygdala activity. Group Processes and Intergroup
Relations, 11(2), 233-246.
Rizzolatti, G., & Craighero, L. (2004). The mirror-neuron system. Annual Review of
Neuroscience, 27, 169-192.
Rozin, P., Haidt, J., & McCauley C. R. (2000). Disgust. In M. Lewis, & J. M. Haviland-
Jones (Eds.), Handbook of Emotions, (ed. 2, pp. 637-653). New York, NY:
Guilford Press.
Rozin, P., Lowery, L., & Ebert, R. (1994). Varieties of disgust faces and the structure of
disgust. Journal of Personality and Social Psychology, 66, 870-881.
Rozin, P., & Royzman, E. B. (2001). Negativity bias, negativity dominance, and
contagion. Personality and Social Psychology Review, 5(4), 296-320.
Santesso, D. L., & Segalowitz, S. J. (2009). The error-related negativity is related to risk
taking and empathy in young men. Psychophysiology, 46, 143-152.
Schaffer, C. E., Davidson, R. J., & Saron, C. (1983). Frontal and parietal
electroencephalogram asymmetry in depressed and nondepressed subjects.
Biological Psychiatry, 18, 753-762.
Schaller, M., & Cialdini, R. B. (1988). The economics of empathic helping: Support for a
mood management motive. Journal of Experimental Social Psychology, 24(2), 333-
353.
Schaller, M., & Duncan, L. A. (2007). The behavioral immune system: Its evolution and
social psychological implications. In J. P. Forgas, M. G. Haselton, & W. von
Hippel (Eds.), Evolution and the social mind: Evolutionary psychology and social
cognition (pp. 293-307). New York, NY: Psychology Press.
Scherer, K. R. (1994). Emotion serves to decouple stimulus and response. In P. Ekman &
R. J. Davidson (Eds.), The nature of emotion: Fundamental questions (pp. 127-
130). New York, NY: Oxford University Press.
Schutter, D. J. L. G., van Honk, J., d’Alfonso, A. A. L., Postma, A., & de Haan, E. H. F.
(2001). Effects of slow rTMS at the right dorsolateral prefrontal cortex on EEG
asymmetry and mood. Neuroreport, 12, 445–447.
Schwartz, G. E., Weinberger, D. A., & Singer, J. A. (1981). Cardiovascular
differentiation of happiness sadness, anger, and fear following imagery and
72
exercise. Psychosomatic Medicine, 43(4), 343-364.
Shackman, A. J., Salomons, T. V., Slagter, H. A., Fox, A. S., Winter, J. J., & Davidson,
R. J. (2011). The integration of negative affect, pain, and cognitive control in the
cingulate cortex. Nature Reviews Neuroscience, 12, 155-167.
Shamay-Tsoory, S. G., Tomer, R., Berger, B. D., Goldsher, D., & Aharon-Peretz, J.
(2005). Impaired “affective theory of mind” is associated with right ventromedial
prefrontal damage. Cognitive and Behavioral Neurology, 18(1), 55-67.
Shaw, L. L., Batson, C. D., & Todd, R. M. (1994). Empathy avoidance: Forestalling
feeling for another in order to escape the motivational consequences. Journal of
Personality and Social Psychology, 67, 879-887.
Siegal, M., & Varley, R. (2002). Neural systems involved in ‘theory of mind.’ Nature
Reviews Neuroscience, 3, 463-471.
Singer, T., & Lamm, C. (2009). The social neuroscience of empathy. The Year in
Cognitive Neuroscience 2009. Annual New York Academy of Sciences, 1156, 81-
96.
Singer, T., Seymour, B., O’Doherty, J., Kaube, H., Dolan, R. J., & Frith, C. D. (2004).
Empathy for pain involves the affective but not sensory components of pain.
Science, 303, 1157-1162.
Sobel, M. E. (1982). Asymptotic intervals for indirect effects in structural equations
models. In S. Leinhart (Ed.), Sociological methodology 1982 (pp. 290-312). San
Francisco: Jossey-Bass.
Stark, R., Walter, B., Schienle, A., & Vaitl, D. (2005). Psychophysiological correlates of
disgust and disgust sensitivity. Journal of Psychophysiology, 19, 50-60.
Stemmler, G. (1992). Differential psychophysiology: Persons in situations. New York,
NY: Springeriop
Stemmler, G., Aue, T., & Wacker, J. (2007). Anger and fear: Separable effects of
emotion and motivational direction on somatovisceral responses. International
Journal of Psychophysiology, 66(2), 141-153.
Stewart, J. L., Towers, D. N., Coan, J. A., & Allen, J. J. B. (2011). The oft-neglected role
of parietal EEG asymmetry and risk for major depressive disorder.
Psychophysiology, 48, 82-95.
73
Stotland, E. (1969). Exploratory investigations of empathy. In L. Berkowitz (Ed.)
Advances in experimental social psychology (Vol. 4, pp. 271-314). New York,
NY: Academic Press, Inc.
Strack, F., Martin, L. L., & Stepper, S. (1988). Inhibiting and facilitating conditions of
the human smile: A non-obtrusive test of the facial feedback hypothesis. Journal of
Personality and Social Psychology, 54(5), 768-777.
Stuss, D. T., Gallup, G. G., Jr., & Alexander, M. P. (2001). The frontal lobes are
necessary for ‘theory of mind.’ Brain, 124(2), 279-286.
Sutton, S. K., & Davidson, R. J. (1997). Prefrontal brain asymmetry: A biological
substrate of the behavioral approach and inhibition systems. Psychological Science,
8, 204-210.
Tassinary, L. G., Cacioppo, J. T., & Vanman, E. J. (2007). The skeletomotor system:
surface electromyography. In J. T. Cacioppo, L. G. Tassinary, & G. G. Berntson
(Eds.), Handbook of Psychophysiology (3rd ed., pp. 267-299). Cambridge,
England: Cambridge University Press.
Taylor, S. E. (1991). Asymmetrical effects of positive and negative events: The
mobilization-minimization hypothesis. Psychological Bulletin, 110(1), 67-85.
Terzian, H., & Cecotto, C. (1959). Determination and study of hemisphere dominance by
means of intracarotid sodium amytal injection in man: II. Electroencephalographic
effects. Bolletino della Societa Ztaliana Sperimentale, 35, 1626–1630.
Tomaka, J., Blascovich, J., Kelsey, R. M., & Leitten, C. L. (1993). Subjective,
physiological, and behavioral effects of threat and challenge appraisal. Journal of
Personality and Social Psychology, 65(2), 248-260.
Tomarken, A. J., Davidson, R. J., Wheeler, R. E., & Doss, R. (1992). Individual
differences in anterior brain asymmetry and fundamental dimensions of emotion.
Journal of Personality and Social Psychology, 62, 676-687.
Tomarken, A. J., Davidson, R. J., Wheeler, R. E., & Kinney, L. (1992). Psychometric
properties of resting anterior EEG asymmetry: Temporal stability and internal
consistency. Psychophysiology, 29, 576-592.
74
Tooby, J., & Cosmides, L. (1990). The past explains the present: Emotional adaptations
and the structure of ancestral environments. Ethology and Sociobiology, 11, 375-
424.
Trivers, R. L. (1971). The evolution of reciprocal altruism. The Quarterly Review of
Biology, 46(1), 35-57.
Vaish, A., Grossman, T., & Woodward, A. (2008). Not all emotions are created equal:
The negativity bias in social-emotional development. Psychological Bulletin, 134,
383-403.
van Honk, J., & Schutter, D. J. L. G. (2006). From affective valence to motivational
direction: The frontal asymmetry of emotion revisited. Psychological Science, 17,
963-965.
Vitaglione, G. D., & Barnett, M. A. (2003). Assessing a new dimension of empathy:
Empathic anger as a predictor of helping and punishing desires. Motivation and
Emotion, 27(4), 301-325.
Vogeley, K., Bussfield, P., Newen, A., Herrmann, S., Happé, F., Falkai, P.,… Zilles, K.
(2001). Mind reading: Neural mechanisms of theory of mind and self-perspective.
NeuroImage, 14, 170-181.
Vrana, S. R. (1993) The psychophysiology of disgust: Differentiating negative emotional
contexts with facial EMG. Psychophysiology, 30, 279-286.
Wacker, J., Chavanon, M.-L., & Stemmler, G. (2010). Resting EEG signatures of agentic
extraversion: New results and meta-analytic integration. Journal of Research in
Personality, 44, 167-179.
Wacker, J., Heldmann, M., & Stemmler, G. (2003). Separating emotion and motivational
direction in fear and anger: Effects on frontal asymmetry. Emotion, 3(2), 167-193.
Watson, D. (2000). Mood and temperament. New York, NY: Guilford Press.
Watson, D., Clark, L. A., Tellegen, A. (1988). Development and validation of brief
measures of positive and negative affect: The PANAS scales. Journal of
Personality and Social Psychology, 54(6), 1063-1070.
Wegner, D. M. (1980). The self in prosocial action. In D. M. Wegner & R. R. Vallacher
(Eds.), The self in social psychology (pp. 131-157). New York: Oxford University
Press.
75
Wellman, H. M., Cross, D., & Watson, J. (2001). Meta-analysis of theory-of-mind
development: The truth about false belief. Child Development, 72(3), 655-684.
Wheeler, R. E., Davidson, R. J., & Tomarken, A. J. (1993). Frontal brain asymmetry and
emotional reactivity: a biological substrate of affective style. Psychophysiology, 30,
82-89.
Wicker, B., Keysers, C., Plailly, J., Royet, J.-P., Gallese, V., & Rizzolatti, G. (2003).
Both of us disgusted in my insula: The common neural basis of seeing and feeling
disgust. Neuron, 40(3), 655-664.
Wiedemann, G., Pauli, P., Dengler, W., Lutzenberger, W., Birbaumer, N., Buchkremer,
G. (1999). Frontal brain asymmetry as a biological substrate of emotions in
patients with panic disorders. Archives of General Psychiatry, 56, 78-84.
Winkielman, P., & Berridge, K. C. (2004). Unconscious emotion. Current Directions in
Psychological Science, 13, 120-123.
Woody, S. R., & Tolin, D. F. (2002). The relationship between disgust sensitivity and
avoidant behavior: Studies of clinical and non-clinical samples. Journal of Anxiety
Disorders, 16, 543-559.
Yartz, A. R., & Hawk, L. W., Jr. (2002). Addressing the specificity of affective startle
modulation: Fear versus disgust. Biological Psychology, 59(1), 55-68.
Yeung, N. (2004). Relating cognitive and affective theories of the error-related
negativity. In M. Ullsperger & M. Falkenstein (Eds.), Error, Conflicts, and the
Brain: Current Opinions on Performance Monitoring (pp. 63-70). Leipzig: MPI of
Cognitive Neuroscience.
Zajonc, R. B., & McIntosh, D. N. (1992). Emotions research: Some promising questions
and some questionable promises. Psychological Science, 3(1), 70-74.
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Appendix A
Condition Facial Movement Instructions
Sadness Raise the inner corners of your eyebrows and pull them up and together in the center of your forehead. Pull the corners of your lips down. Raise your cheeks and pull your lip corners down against the upward pull. Glance down.
Happiness Raise your cheeks. If it is hard to do try squinting a little. Part your lips and let your lip corners come up.
Fear Raise your eyebrows as high as you can and pull the inner corners of your brows together. Raise your upper eyelids and tighten your lower eyelids. Let your mouth drop open and stretch your lips horizontally. It may help to use a muscle in your neck to pull your lip corners horizontally.
Disgust Wrinkle your nose, let your lips part. Pull your lower lip down. Let your tongue move forward in your mouth but you don’t need to stick it out.
Anger Pull your eyebrows down and together. Raise your upper eyelids. Now tighten your lower eyelids. Narrow, tighten, and press your lips together, pushing your lower lip up a little.
Movement Control Raise your eyebrows and pull them up and together in the center of your forehead. Part your lips and let your lip corners come up.
No Movement Control N/A
77
Copyright Acknowledgments
The content of Chapter 2 is currently in press at Psychophysiology:
Tullett, A. M., Harmon-Jones, E., & Inzlicht, M. (in press). Right-frontal cortical
asymmetry predicts empathic reactions: Support for a link between withdrawal
motivation and empathy. Psychophysiology.
78
Notes
1. These two sets of images were matched on the basis of gender, race, age, body
position, and general context, but were selected so that they differed in the degree of
physical suffering depicted. In Study 1, self-reported reactions were collapsed across the
images because of high reliabilities across the two sets (αs > .75), and because the
relationships between frontal EEG asymmetry and self-report variables did not differ
across the two sets. In Study 3, the two sets are analyzed separately because the
relationship between EMG activity and self-report variables differed substantially across
the two sets.
2. Frontal asymmetry scores are also commonly analyzed at electrodes F7/F8. In our
sample, however, the F7 electrode site was excluded for 13 participants because of
excessive noise identified prior to data analysis. Due to the substantially reduced sample
size of participants with F7/F8 data, I have not included analyses of these electrode sites.
79
Tables
Table 1. Means and standard deviations for emotion intensity ratings of the images
Images Ratings
Joy Anger Disgust Sadness Surprise Fear Suffering
M SD M SD M SD M SD M SD M SD M SD
Set A 1.59 .55 1.43 .35 1.34 .42 2.05 .37 1.40 .39 1.57 .45 1.84 .43 Set B 1.12 .17 3.10 .59 1.94 .77 3.45 .55 1.77 .82 2.35 .67 4.10 .58 Overall 1.36 .34 1.57 .43 1.64 .53 2.75 .34 1.57 .43 1.96 .47 2.97 .45
Note. Missing items were replaced with the series mean. Table 2. Reliabilities and descriptive statistics for key variables
α M SD
1. Empathic Concern .86 2.81 .63 2. Sadness .89 2.68 .85 3. Personal Distress .93 2.80 .87 4. F4F3 - .12 .33 5. FC4FC3 - .04 .12 6. CP4CP3 - .01 .22 7. P4P3 - .06 .21
Table 3. Bivariate correlations between key variables
1 2 3 4 5 6 7
1. Empathic Concern .78** .67** -.41* -.05 .33† .62** 2. Sadness .90** -.52** -.12 .16 .37* 3. Personal Distress -.60** -.22 .15 .22 4. F4F3 .57** -.17 -.10 5. FC4FC3 .40* .06 6. CP4CP3 .59 7. P4P3
Note. Ns vary between 27 and 30 due to excluded electrode sites. Negative correlations indicate a positive relationship between right-frontal asymmetry and the variable of interest. **p < .01, *p < .05, †p < .1.
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Table 4. Predicting empathic concern and empathic contagion from emotional disposition
Emotional Disposition
P Agg. V Agg. Anger Hostility Fear PA NA
Empathic Concern – Overall
-.38** -.25* -.08 -.14 .14 .18 .08
Empathic Concern – Sad Targets
-.34** -.25* -.10 -.21† .03 .06 .04
Empathic Concern – Happy Targets
-.26* -.15 -.03 .00 .21† .25* .10
Emotional Contagion – Overall
-.23† -.16 .03 .08 .31** .11 .16
Emotional Contagion – Sad Targets
-.18 -.14 .07 .06 .26* .00 .16
Emotional Contagion – Happy Targets
-.20† -.14 -.03 .09 .28* .19 .12
Note. P Agg. = Physical Aggression; V Agg = Verbal Aggression; PA = Positive Affect; NA = Negative Affect. **p < .01, *p < .05, † p < .1. Table 5. Means and SDs for levator labii and corrugator supercilli EMG in response to
images
Image Type
Suffering Charity
Non-suffering Charity
Disgust Control Sad Control Scenery
Muscle M SD M SD M SD M SD M SD
Levator Labii
.33 1.27 .08 .80 1.86* 3.76 .14 1.47 .25 1.20
Corrugator Supercilli
.93 2.76 .01* .71 1.26 2.68 .31 .69 -.05* .45
Note. * p < .05 for pairwise comparisons with suffering charity within each electrode site.
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Table 6. Bivariate correlations between key variables for suffering charity images
1. 2. 3. 4. 5.
1. Levator Labii 2. Corrugator .80** 3. Empathic Concern .30† .24 4. Disgust .43** .24† .33* 5. Sadness .40* .36* .74** .32†
Note. **p < .01, *p < .05, †p < .1.
Table 7. Bivariate correlations between key variables for non-suffering charity images
1. 2. 3. 4. 5.
1. Levator Labii 2. Corrugator .33* 3. Empathic Concern -.28† .02 4. Disgust -.36* -.14 .54* 5. Sadness -.21 .16 .90** .59*
Note. **p < .01, *p < .05, † p < .1.
Table 8. Results of mediated moderation analysis
Original Model (DV = Empathic
Concern)
Mediator Model (DV = EMO-CONT)
Mediated Moderation Model (DV = Empathic
Concern)
Predictors b t b t b t
IT .56 10.40** .71 12.53** .06 1.03 LL .00 .01 .01 .17 .01 .12 IT*LL .15 2.15* .21 3.00* .01 .25 EMO-CONT .71 10.66** IT*EMO-CONT -.13 -2.60*
Note. DV = dependent variable; IT = image type; LL = levator labii activity; EMO-CONT = emotional contagion. Image type was coded where suffering = 1 and non-suffering = -1. **p < .01, *p < .05, † p < .1.
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a)
b)
c)
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