Psychiatry Research: Neuroimaging 221 (2014) 135–141

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Psychiatry Research: Neuroimaging journal homepage: www.elsevier.com/locate/psychresns

The neural correlates of the dominance dimension of emotion Matthew Jerram n, Athene Lee, Alyson Negreira, David Gansler Suffolk University, Psychology Department, 41 Temple Street, Boston, MA 02114, United States

art ic l e i nf o

a b s t r a c t

Article history: Received 15 August 2013 Received in revised form 21 November 2013 Accepted 25 November 2013 Available online 4 December 2013

Emotion has been conceptualized as a dimensional construct, while the number of dimensions – two or three – has been debated. Research has consistently identified two dimensions – valence and arousal – though ample evidence exists that three dimensions are necessary to describe emotion. One proposed third dimension, identified as dominance, is relevant in clinical syndromes, personality and consumer psychology. Dominance refers to an individual's sense of having an ability to affect the environment. Neuroimaging studies have generally focused on the two dimensions of valence and arousal, leaving the neural correlates of dominance unexplored. The current study used functional magnetic resonance imaging to explore the neural basis of dominance in 17 healthy male controls. Participants viewed images from the International Affective Picture System that were selected to represent high and low dominance conditions. Results indicated activation in paralimbic regions, including the bilateral anterior insula for high dominance and the right precuneus for low. The findings of this exploratory study support the consideration of dominance in dimensional models of emotion and suggest that further research is needed to understand the neural representation of dominance in emotional experience. & 2013 Elsevier Ireland Ltd. All rights reserved.

Keywords: Emotional dominance Dimensional model Functional magnetic resonance imaging (fMRI) International Affective Picture System Insula

1. Introduction Emotion has been conceptualized as a dimensional construct for more than a century (Wundt, 1896). In many models, three dimensions have been proposed to describe emotional experience (Osgood et al., 1957; Russell and Mehrabian, 1974; Bradley and Lang, 1994). Generally, these dimensions have been identified as valence, arousal and dominance. Valence refers to whether the experience is pleasurable, and arousal refers to autonomic arousal associated with the experience. Dominance, also called potency or agency, refers to the level to which the individual feels influence over a situation or control of the external environment during the emotional experience. Mehrabian (1996) described it as “feelings of control and influence over everyday situations, events and relationships versus feelings of being controlled and influenced by circumstances and others” (p. 2). Valence and arousal have been investigated using multiple modalities, including neuroimaging, and the neural correlates of these dimensions are well understood (e.g. Anders et al., 2004; Kensinger and Schachter, 2006). The neural correlates of dominance, however, have not been investigated directly. This lack of focus has been attributed to the lesser robustness of dominance as an dimension of emotion and its high association with valence in studies of emotional stimuli. According to Bradley

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and Lang (1994), valence and arousal together consistently explain 50% or more of the variance in ratings of emotional experience. Conversely, dominance rarely explains more than 15% of the variance. There have been concerns regarding the psychometric adequacy of dominance ratings because stimulus ratings made with a verbal semantic differential were not highly correlated with those made with a nonverbal semantic differential, while both techniques provided consistent ratings of valence and arousal (Bradley and Lang, 1994). Therefore, most current dimensional models of emotion experience rely on two axes—valence and arousal. Feldman Barrett and Russell (1999) acknowledged that valence and arousal, which define core affect from a dimensional perspective, do not adequately explain all the variance found in ratings of emotion. Therefore, in their circumplex model of emotion, a prototypical emotional episode is defined as a complex process that involves core affect and other components, like attribution of cause and meta-cognitive judgment. When developing the International Affective Picture System (IAPS), Lang et al. (2008) included the dimension of dominance, in addition to valence and arousal, to establish normative ratings for the pictures. They also used all three dimensions when developing normative ratings for the International Affective Digital Sounds (Bradley and Lang, 1999a), Affective Norms for English Words (Bradley and Lang, 1999b) and Affective Norms for English Text (Bradley and Lang, 2007). Two-dimensional models cannot describe emotional experience as fully as a three-dimensional model (Russell and Mehrabian, 1974;

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Shaver et al., 1987). For example, the experiences of fear and anger are experientially distinct emotional states. In a two-dimensional model, both would be identified similarly—high arousal, negative valence. Clearly, this does not reflect the subjective experience of these emotions, suggesting that the model would be improved with the addition of another dimension. Russell and Mehrabian (1974) demonstrated that dominance was able to distinguish between anger and fear, while valence and arousal were not—high dominance was associated with anger, while low dominance (also called “submission”) was associated with fear. Further, neuroimaging evidence has found that fear and anger are associated with different anatomic pathways (LeDoux, 1996) and with different frontal asymmetry (Coan et al., 2001). Dominance would help better define and differentiate emotional experiences within the dimensional model, which in turn would improve understanding of healthy and pathological emotional states. While there has been no focus on dominance in affective neuroscience, its place in a dimensional model of emotion has been considered by multiple researchers. Mehrabian (1996, 1997) and associates have focused considerable effort on understanding the Pleasure-Arousal-Dominance (PAD) model of emotion (Russell and Mehrabian, 1974) and have found that dominance plays a role in psychopathology (Mehrabian, 1997). Using factor analysis and multidimensional scaling, Shaver et al. (1987) found a threedimensional model was a better fit to emotion data than a twodimensional model. Fournier and Moskowitz (2000) illustrated that dominance is related to but not equivalent to valence by demonstrating that high and low dominance are both associated with reduced valence while moderate dominance is related to increased valence. Demaree et al. (2005) discussed the important of dominance in the understanding of brain laterality effects in emotional processing, noting it better explains research findings than other models and that data have supported the importance of dominance in psychopathology, specifically obsessive-compulsive disorder (Casado et al., 2011). While multiple researchers endorse a third emotional dimension, no consensus exists about the underlying construct. Blascovich and Mendes (2000) developed the concept of threat vs. challenge, in which they define “threat” as the perception that one does not have the resources to meet situational demands, while “challenge” is the perception that one can meet them. They note that the perception of threat or challenge is not static across time or situation. Approach/avoidance, sometimes referred to as the approach/withdrawal model, has also been a suggested label for the third dimension of emotional experience (Davidson, 1998; Carver and Harmon-Jones, 2009) and refers to an organism's likelihood of behaviorally approaching or avoiding a stimulus. These alternatives to dominance as the third emotional dimension have merit, and there is significant conceptual overlap between them and dominance. However, there are also relevant differences between dominance and these alternatives, such that understanding dominance may improve our understanding of emotional experience. For example, as conceptualized by Blascovich and Mendes (2000), the threat vs. challenge model relies on conscious appraisal of the situation, while dominance does not. They assert that in order for threat or challenge to be perceived, it must be understood that there is a goal that must be met to perpetuate or enhance well-being and the individual must anticipate evaluation by the self or others. Further, it is not a model of emotion, per se, but more a model of motivation, with emotional, cognitive and physiological contributors to behavior. For example, a threat or challenge may be perceived during an exam, which will be determined by the individual's cognitive assessment of the exam's requirements, the resources necessary to complete the exam and the consequences of not passing the exam, as well as the emotional response to the exam (including the physiological

response). Dominance, however, would describe only that part of the emotional state that relates to the individual's sense of agency in that context. Dominance may influence the perception of threat or challenge, but there is a higher level of cognition, usually conscious, that is a component of a threat vs. challenge appraisal but not dominance. In fact, given the threat vs. challenge model's wider scope, further understanding of dominance might assist in better understanding the affective component of threat vs. challenge. The approach–avoidance model also has multiple strengths, and there is research evidence to demonstrate neural substrates, particularly the amygdala and ventral striatum, of approach and avoidance behaviors (Jensen et al., 2003; Andrzejewski et al., 2005; Schlund et al., 2010). Conceptually, dominance offers facets to the understanding of emotion independent of those offered by an approach–avoidance model. Perhaps the most salient difference is that levels of dominance will not have a linear relationship with an approach–avoidance continuum. In other words, high dominance will not necessarily be associated with approach behaviors, and low dominance will not automatically produce avoidance. For example, behaviors related to social dominance (or lack thereof) do not neatly fit into approach–avoidance categories. In some situations, high dominance will lead to approach behaviors, but in others will lead to avoidance behavior or an absence of behavior. This suggests that dominance may allow for a level of complexity in understanding emotion, particularly in its relationship with social behavior, that is more limited with an approach– avoidance model. Research indicates that the inclusion of a third factor in the dimensional model of emotion is conceptually valid, and there is sound reasoning to suggest that dominance is a useful model for that third dimension. One area that has been fruitful in supporting the presence of valence and arousal as dimensions of emotion has been neuroimaging. As described above, several studies have identified neural correlates for valence and arousal. It seems reasonable, therefore, to explore dominance as a dimension of emotion through the same techniques. No previous neuroimaging studies on dominance as a component of emotion have been reported. Some neuroimaging research has focused on the cognitive experience of attributing oneself as the agent of one's own action—called “agency” in these studies. This conceptualization of agency is similar to emotional dominance lacking the affective component. Farrer and Frith (2002), Farrer et al. (2003) conducted a series of positron emission tomography studies to examine the neural correlates of agency in the absence of an affective component. Results indicated that attributing a motor action to oneself activated the bilateral anterior insula and premotor cortex, while attributing action to another activated the right inferior parietal lobe. The current study seeks to determine if neural correlates of dominance could be observed. It was hypothesized that high dominance images would activate regions of the brain distinct from those activated by low dominance images. Though this study is primarily exploratory, specific brain regions were hypothesized; it was expected that dominance would be associated with activity within a network of regions that have been identified as important for processing emotional experience and representation of the self in the environment, particularly the insula, the temporoparietal junction, the premotor area, the cingulate gyrus, the precuneus, and the medial prefrontal cortex (Farrer and Frith, 2002; Farrer et al., 2003; Anders et al., 2004; Kensinger and Schachter, 2006). Further, given the relationship of high dominance to anger, it was hypothesized that activity in regions associated with high dominance would be positively correlated with trait anger, while regions associated with low dominance would be uncorrelated.

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2. Methods 2.1. Participants The study was approved by Institutional Review Boards at Suffolk University and Tufts Medical Center (TMC). Twenty male healthy control individuals were recruited through an advertisement on an online messaging board (craigslist.org) and through word-of-mouth. The sample was only male to avoid confounds due to documented sex-related brain structural and functional differences (Goldstein et al., 2001, 2010) and to reflect the authors' broader research interests in the neural correlates of impulsivity and aggression, behavioral issues that are characterized by anger (a high dominance emotion) and are more common in men (Coccaro, 2012). Exclusion criteria included head injury with loss of consciousness ( 41 min), major mental or neurological illness, chemical dependency, developmental disorder or significant problems with aggression and impulsivity. Data from three participants were excluded due to corrupted functional images, leaving a final sample of 17 (see Table 1 for demographic details). 2.2. Behavioral measures

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as those of dead bodies or of injuries, and such stimuli were excluded if, by visual inspection by the authors, the image was judged to be likely to cause significant discomfort to the participants. Overall, 117 images were selected from the IAPS images; 60 were classified as “high dominance” (HD) and 57 were classified as “low dominance” (LD). (Four images from LD were duplicates with separate image numbers; only one of the duplicate images was included. This did not impact statistical analyses.) Table 2 provides a complete list of the slides for each condition. Based on the normative ratings, HD and LD images had significantly different mean dominance ratings, t(1 1 5) ¼12.54, P o 0.001. Contrary to expectations, there was a significant difference in arousal ratings between the HD and LD images, t(1 1 5) ¼  7.78, P o 0.001; no difference was found in valence ratings, t(1 1 5) ¼1.73, N.S. Effect sizes of both arousal and valence rating differences were substantially smaller than the effect size for the dominance rating difference (see Table 3). 2.4. Stimulus presentation Images were presented during functional magnetic resonance imaging (fMRI) using an ASI Eloquence stimulus presentation system through an E-Prime script running on a Windows operating system. Participants viewed the stimuli on a full color LCD screen inside a stimulus presentation apparatus in the scanner that fit over the head coil. Participants were provided with a button box to allow for behavioral response.

Each participant performed several psychological tests to characterize the participant's general cognitive and emotional functioning, including specific assessment of traits of interest in the broader context of the project. Among these was the State-Trait Anger Expression Inventory—2 (STAXI-2; Spielberger, 1999). This is a self-report measure of the experience of and behavioral responses to anger. It consists of 57 Likert-scale items and produces several scales and subscales; most relevant to the current study is the Trait Anger—Angry Temperament (T-Ang/ T) subscale. This scale assesses the propensity of an individual to experience anger without specific provocation and, of the STAXI-2 scales, is most conceptually aligned with a tendency to perceive relatively high dominance. Participants were also administered the Vocabulary and Matrix Reasoning subtests of the Wechsler (1999) Abbreviated Scale of Intelligence (Psychological Corporation) to determine estimated IQ (WASI-IQ).

Imaging data were acquired on a 3T Phillips Achieva MRI scanner with a standard quadrature head coil. Functional images were collected in the axial plane using a T2-weighted echo planar imaging sequence (repetition time (TR) ¼ 2 s, field of view (FOV)¼ 256, acquisition matrix ¼ 128  128, 30 slices with no gap, 1.8  1.8  4 mm3 resolution). High-resolution anatomic images were collected in the sagittal plane for each participant using a multiplanar rapidly acquired gradient echo sequence (MPRAGE, TR ¼ 11 ms, FOV ¼580, 301 slices, 1  1  0.6 mm3 resolution).

2.3. Stimuli

2.6. fMRI paradigm

Stimuli were selected from the International Affective Picture System (IAPS) (Lang et al., 2008), which is a set of color photographs with normative ratings for dominance, valence and arousal, collected using the Self-Assessment Manikin (Bradley and Lang, 1994). These ratings were used to select stimuli for the high and low dominance conditions. Stimuli were selected to maximize the difference between the mean dominance ratings of each condition. Previous research has found that valence and dominance are highly correlated, though this was not found in the relation between arousal and dominance (Lang et al., 2008). Therefore, the range of valence ratings for the selection of images was restricted to the lower half (1–5) of the total range; this reflected the authors' research program with broader interests in behaviors associated with negative emotional states. No restrictions were placed on the range of arousal ratings. The IAPS has many images of a graphic nature, such

Stimuli were presented in three 5-min runs. In each run, stimuli of a particular type (HD or LD) were presented in 30-s blocks. During each run, five blocks of each condition were presented. Blocks were counterbalanced to avoid order effects. Within each block, six stimulus images were presented with a 5-s interstimulus interval. The length of stimulus presentation was randomly varied between 1 and 4 s. This was done to prevent the participant's being able to anticipate the length of exposure and to help maintain attention to the stimuli. Participants were asked to respond to the stimuli by pressing a button on the button box when the image changed. They were not asked to evaluate the image in any way to reduce conscious cognitive processing of the image. This method of participant response has been used in previous research with the IAPS (Goldstein et al., 2005). 2.7. Procedure After granting informed consent, participants completed the psychological assessments. When the battery was completed, participants underwent scanning. Upon completion, participants were debriefed regarding the images observed during fMRI and provided with a small honorarium for their participation.

Table 1 Demographic characteristics of study participants. Characteristic

2.5. Scanning parameters

Participants (n¼ 17) 2.8. fMRI data analysis

Age, years Education, years WASI FSIQ

Mean

SD

Range

28.85 16.3 120.95

7.69 2.08 9.08

20–45 12–21 100–133

2.8.1. Preprocessing Preprocessing and data analysis were conducted using Statistical Parametric Mapping-8 (SPM-8, Wellcome Department of Cognitive Neurology, University College London, 2008). Functional data were motion-corrected, spatially

Table 2 IAPS stimuli utilized in the study. Stimulus type High dominance Low dominance

IAPS number 1052, 1090, 1110, 1274, 1275, 1301, 2100, 2104, 2110, 2210, 2271, 2440, 2456, 2457, 2691, 2700, 2718, 2722, 2730, 2900.1, 3022, 3185, 4505, 4510, 4550, 4572, 4621, 5130, 6241, 6242, 6555, 6571, 7025, 7031, 7078, 7136, 7224, 7234, 8230, 8480, 9008, 9045, 9080, 9090, 9101, 9160, 9210, 9360, 9417, 9424, 9430, 9432, 9452, 9471, 9491, 9584, 9596, 9831, 9832, 9922 1022, 1040, 1050, 1070, 1300, 1304, 1525, 1930, 2590, 2661, 2683, 5300, 5961, 5970, 5971, 5972, 5973, 6000, 6200, 6210, 6244, 6250.1, 6263, 6300, 6370, 6550, 6562, 6930, 7079, 8485, 9001, 9010, 9002, 9050, 9120, 9186, 9230, 9270, 9400, 9403, 9423, 9426, 9582, 9590, 9592, 9600, 9610, 9611, 9620, 9621, 9623, 9905, 9908, 9909, 9925, 9927, 9930

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3. Results

Table 3 Characteristics of chosen IAPS stimuli. Characteristic

High dominance Low dominance Effect size of difference M (SD)

Dominance rating 5.09 (0.72) Valence rating 3.85 (0.43) Arousal rating 4.22 (1.16)

M (SD)

Cohen's d

3.74 (0.39) 3.67 (0.60) 5.64 (0.73)

2.45 0.31 1.48

normalized to Montreal Neurological Institute (MNI) space, and smoothed before statistical analysis using standard SPM methods. Spatial normalization to the canonical EPI template image (SPM-8) was done without modulation using affine transformation and trilinear interpolation and included resampling at 2-mm isotropic voxels. Given the strength of the magnet and voxel size, a 5-mm full width at half-maximum (FWHM) Gaussian smoothing was considered appropriate to compensate for differences in localization across participants. Additionally, motion and intensity artifact was evaluated for each scan using Artifact Detection Tools (ART; Whitfield-Gabrieli, 2009a). Scans were to be considered outliers if z-score equivalents related to signal intensity exceeded 3.0 or if motion correction values exceeded 5 mm for translational adjustments or 3 rad for rotational adjustment. No outliers were detected. 2.8.2. Primary analyses In the first level (intrasubject) analysis, the standard hemodynamic response function (HRF) was convolved with the block onset/offset times using the general linear model (GLM). Six motion regressors were included as covariates. Contrast analyses were performed and regressor weight (beta coefficient) contrasts for the primary conditions of interest (HD and LD) were obtained. Specifically, two contrasts were defined: HD 4LD, LD 4HD. Second level (intersubject) analyses were performed across the entire brain volume. A one-sample t test was used to examine brain activation differences between HD and LD conditions. The resultant SPM T-maps were thresholded voxelwise at Po 0.001 uncorrected for multiple comparisons and a cluster extent of 5 voxels. Reported clusters were significant at Po 0.05 with a familywise error correction. Coordinates in MNI space for each cluster were used to determine anatomic location.

3.1. Primary analyses of dominance 3.1.1. High dominance versus low dominance Significant activation was observed in the HD4 LD condition in the bilateral anterior insula (MNI coordinates: 44, 4,  6 and  40, 0,  6). Activation was also observed within the right lateral occipital gyrus (46,  82, 4), the right fusiform gyrus (16,  42,  22), the left lingual gyrus (  16,  70,  10), the right precentral gyrus (38, 2, 28) and the left culmen (  34,  36,  24). 3.1.2. Low dominance versus high dominance One cluster was found to be significantly activated in the LD4HD condition—in the right posterior precuneus (8,  78, 40) Figs. 1 and 2. 3.2. Secondary analyses 3.2.1. High dominance versus low dominance controlling arousal Secondary analysis found overlapping voxels in the right insula, as well as in the right right precentral gyrus and cerebellum, indicating that there was activation in these areas when HD 4LD was tested alone and with arousal controlled. Overlap was not found in the left anterior insula, the left lingual gyrus, the left fusiform gyrus, or the right occipital gyrus. 3.2.2. Low dominance versus high dominance controlling arousal The primary analysis detected activation in the right precuneus for the LD4HD comparison. Secondary analysis did not identify overlapping voxels in this region, indicating that there was activation in these areas when LD oHD was tested alone but not when LDoHD was tested with arousal controlled. 3.3. Behavioral correlation

2.8.3. Secondary analyses Given the significant differences in arousal ratings of images across condition, follow-up analyses were performed to account for arousal ratings. For each dominance condition block, the average arousal rating for the images was calculated using the normative rating provided with the IAPS. Those values were then included using parametric modulation at the individual level of analysis. Thus, dominance was set as a block condition, and the average arousal rating for each block was included as a parameter. Contrast analyses were performed and regressor weight (beta coefficient) contrasts for the primary conditions of interest (HD and LD) were obtained while regressor weights for the parametric modulator were set to zero, indicating activity associated with high and low dominance contrasts while the arousal rating was controlled. Second level (intersubject) analyses were performed across the entire brain volume. A one-sample t test was used to examine brain activation differences between HD and LD conditions while average arousal rating per block was held constant. The resultant SPM T-maps were thresholded voxelwise at Po 0.005 uncorrected for multiple comparisons and a cluster extent of 5 voxels. In the secondary analyses, clusters were considered confirmatory if they spatially overlapped clusters observed in the primary analyses. Overlap was determined using mask images created from statistically thresholding the T-maps for the primary analysis (dominance condition comparison alone) and the secondary analysis (dominance condition comparison controlling for arousal rating). T-maps were binarized such that voxels that reached statistical threshold were included in the map and all others were excluded. The maps were then overlaid and clusters of common voxels were identified in MNI space using the xjView toolbox (http:// alivelearn.net/xjview). 2.8.4. Correlational analyses Percent signal change (PSC) values were extracted from foci identified in the primary analyses to examine the correlation of signal change to the behavioral measure of angry temperament, T-ANG/T. Regions of interest (ROIs) were defined as 10-mm spheres centered on the maximum voxel within each significant cluster from the primary analyses. PSC values were obtained for each ROI using the REX toolbox for SPM (Whitfield-Gabrieli, 2009b). These values were entered into SPSS 17 (SPSS, 2007) with scores from the T-ANG/T, and Spearman correlations were performed. As a control measure, PSC values were also correlated with WASI-IQ (Table 4).

Results of the correlations between PSC in ROIs and T-ANG/T scores indicated one finding that was nearly significant—HD 4LD activity in the left insula (ρ¼0.50, P ¼0.056). PSC in the HD 4LD cluster in the right insula was moderately correlated with T-ANG/T (ρ¼0.44, P¼ 0.10). While neither result reached statistical significance, the results indicate that insular activity accounted for 19– 25% of the variance in T-ANG/T. Similarly, the correlation of right premotor cortex PSC and T-ANG/T accounted for 20% of the variance (ρ¼0.45, P ¼0.10). In contrast, PSC in the LD4HD ROI, in the right precuneus, was weakly correlated with T-ANG/T (ρ¼  0.26, P ¼0.34), accounting for only 7% of the variance. The reversed direction of the HD 4LD-T-ANG/T and LD4HD-T-ANG/T correlations is noteworthy as well, indicating that increased activation was associated with increased T-ANG/T in regions associated with high dominance, while the reverse was true for regions associated with low dominance. No correlations with WASI-IQ were significant for any region. The strongest relationships to WASI-IQ were found with right premotor cortex PSC (ρ¼0.31, P ¼0.23) and precuneus PSC (ρ¼0.29, P ¼0.27), accounting for no more than 9% of variance. These results indicate some specificity of the relationship of these regions to T-ANG/T.

4. Discussion Results of this study demonstrated that the hypothesized dimension of emotion of dominance is represented in neural structures. This is the first study to our knowledge to find neural correlates for dominance as a dimension of emotion. The strongest

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result was in the anterior insula for HD 4LD. Further, results indicated that brain activity related to dominance is differentially correlated with a behavioral trait theoretically aligned with dominance—angry temperament. The results of this study indicate that dominance is relevant to the processing of emotional stimuli and should be considered in dimensional models. It is important also to note that this is a preliminary study and the results of this work would need to be replicated. The finding of neural correlates of this dimension has significant implications across multiple areas of research into emotion, including social and affective neuroscience, neuroeconomics and basic emotion theory. The most salient activation in the HD 4LD condition was observed in the anterior insula (AI) bilaterally, known to be an integral part of the emotion system—a meta-analysis identified the AI as among the most commonly activated regions in emotion studies (Kober et al., 2008). The AI has been associated with selfattribution and empathy, as well as interoceptive awareness (Carr et al., 2003), and identified, along with the anterior cingulate, as a core of the “salience” network, which is central to the determination of the contextual importance of stimuli and the relative activation of the default mode network and central executive network (Menon and Uddin, 2010). Based on the somatic marker hypothesis (Damasio, 1996), the AI is central to re-enacting somatic states quickly to retrieve relevant episodic memories for

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decision-making that have an emotional component. As described above, Farrer and Frith (2002) found that the experience of attributing a motor action to oneself (as opposed to another) activated the AI bilaterally, mirroring the results of this study, though their paradigm was cognitive. Tractography research has also suggested that the AI shares connections with other regions of activation observed in this study—the precuneus, the fusiform and lingual gyri (Jakab et al., 2012). These formulations are consistent with hypotheses that the AI may be central to the processing of emotional dominance in the brain. Dominance requires the individual to assess internal resources and states, as well as the external environment, and to make predictions about likely outcomes, in an emotional context. All of these functions have been observed to activate the AI (Kurth et al., 2010). Further, dominance has been suggested to be a dimension separate from valence and arousal, and studies have demonstrated that the AI activates to both positive and negative stimuli and approach and avoidance stimuli (Lamm and Singer, 2010). Interestingly, one study (Nielen et al., 2009) has found that, while valence and arousal alone activate independent regions, the interaction of valence and arousal activates the AI. These data suggest that emotion-related activity in the AI is not specific to valence or arousal alone, which could be consistent with the association of AI activity and dominance processing.

Table 4 Clusters of significantly different activation between dominance conditions with peak voxel location and t-score. Brain area

Cluster size

High dominance 4low dominance R Insula (incl. R Lat. Occ. Gyrus)

4,795

L Culmen (Cerebellum)

676

R Fusiform Gyrus

324

L Lingual Gyrus R Precentral Gyrus

208 381

L Insula

713

Low dominance 4high dominance R Precuneus

278

X

Y

Z

t-Score

44 42 46  34  42  26 16 26 2  16 38 48 52  40  28  50

4 4  82  36  32  62  42  50  52  70 2 14 4 0  10 2

6 6 4  24  22  10  22  14  22  10 28 26 34 6 6 6

8.25 7.74 7.58 6.85 5.57 4.76 5.99 5 4.79 5.88 5.7 5.04 4.84 5.68 5.42 4.64

8 2

 78  78

40 36

5.5 5.39

Fig. 2. bar graph representing the mean T-value (with error bars) for all voxels within clusters of activation. Bars ascending from the horizontal axis represent the HA4LA comparison while bars descending from the horizontal axis represent the LA4HA comparison.

Fig. 1. Images are presented in radiological convention (right ¼left). Image A (left) shows activation in the HA 4LA condition in the bilateral insula and right premotor area. Image B (right) shows activation in the LA4HA condition in the precuneus. Color represents the T-value of the activated voxel, as shown by the color bar.

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However, the AI is one of the most commonly activated regions in functional neuroimaging studies, appearing across multiple functional paradigms. This suggests a lack of specificity in AI function, making the interpretation of AI activation difficult and suggesting that our results may be a function of general information processing, not processing specific to emotional dominance. However, our interpretation has support from a recent meta-analysis (Chang et al., 2013) that reported a reliable functional parcellation of the insula. The results of this analysis indicated that the ventral AI, where the activation foci of this study are found, are consistently related to emotion and autonomic function and that it is, in fact, the dorsal AI that appears to have a more nonspecific activation history. Therefore, while there may be room to dispute our conclusion that the AI is related to dominance specifically, the conclusion that our results are related to emotion processing appears to be valid and the conclusion that the activity in AI, specifically the ventral AI, is most likely related to dominance-related processing seems reasonable. While the AI is likely central to dominance, the other observed regions in the HD4LD condition – the lingual and fusiform gyri, lateral occipital gyrus, premotor area and cerebellar culmen – have also all been implicated in emotion processing (Geday et al., 2003; Scheuerecker et al., 2007; Fusar-Poli et al., 2009; Aziz-Zadeh et al., 2010). The lingual gyrus has been shown to be active in response to emotional face recognition and attention, and it has not been found to respond differentially to positively or negatively valenced images, suggesting that dominance, as a separate dimension, may play a role in its activity (Scheuerecker et al., 2007). The fusiform gyrus has also been found to activate in response to emotional stimuli—most studies have examined emotional faces, but fusiform activity has been observed with other types of emotional stimuli as well (Geday et al., 2003; Hadjikhani and de Gelder, 2003). The premotor area has been found to be involved with emotional processing in addition to its more commonly understood role of planning movements (Scheuerecker et al., 2007). In high dominance situations, an individual feels more freedom to act and may begin to imagine or plan for action, as opposed to low dominance situations where action is considered ineffective. This may explain the relative increase in activity to the HD 4LD condition. Activation was observed for the LD 4HD condition in the right precuneus, though this activation was not separable from level of arousal. The precuneus is a region involved with self-reflection and consciousness, especially in terms of modeling the perspectives of others (Jeannerod, 2007). Cavanna and Trimble (2006) found support for the association of the precuneus with visuospatial imagery, episodic memory retrieval, theory of mind, and experiences of agency. Along with other regions, the precuneus is also part of the brain's default mode network (DMN) (Buckner et al., 2008). Precuneus activation was also observed in response to the attribution of an action to another person in the aforementioned dominance study (Farrer and Frith, 2002). Finally, it is a region known to be interconnected with the AI (Jakab et al., 2012). The precuneus may involve the attempt to model the likely actions of others when one expects to have little or no influence. A particularly interesting consideration in the relationship between low dominance and precuneus activity is the possible involvement of the DMN. DMN activity has been associated with mind-wandering (Mason et al., 2007) and increased creativity (Takeuchi et al., 2011), which are more internally focused and abstract processes than tasks associated with decreased DMN activity. This suggests that low dominance prompts an individual to redirect attention internally and may indicate an attempt to disconnect from external stimuli to avoid them, such as in dissociative states or to generate creative methods to cope with them.

The results of this study indicated activity in brain regions that have also been shown to respond to specific emotional states elicited by IAPS stimuli, particularly the AI. Britton et al. (2006) found that the AI, as well as the hippocampus and orbitofrontal cortex, responded to anger-inducing IAPS images while fearinducing images activated the visual cortex and hippocampus. These results indicate distinct neural correlates for high dominance (anger) and low dominance (fear) emotions elicited by the IAPS, and the insula activity in response to anger is consistent with the results of the current study. The insula has also been activated with IAPS images that elicit disgust (Mataix-Cols et al., 2008). The primary limitation of this study was that it was impossible to develop a stimulus set that uniquely varied dominance without also varying valence or arousal. Given that previous research had more reliably demonstrated a strong relationship between valence and dominance, the focus of stimulus development was on creating a set of stimuli that varied dominance independently of valance. While this was successfully implemented, the same could not be said for arousal, though the effect size difference for dominance across conditions was substantially larger than for arousal across conditions. The primary analyses found robust effects of high versus low dominance stimuli. The secondary analyses were consistent with the idea that dominance cannot be considered a perfectly orthogonal dimension of emotion. This lack of orthogonality, however, also appears with valence and arousal, which have been found to be non-orthogonal; for example, they co-activate brain regions. That finding indicates that the dimensions of emotion cannot be considered strictly orthogonal, which is somewhat intuitive, and, in this context, the results of this study most likely reflect the contribution of dominance processing. To the best of our knowledge, no other neuroimaging study has used dominance as an experimental variable or covariate. Overall, the results indicate that dominance should be considered in research in the dimensional model of emotion and further research should refine the contribution of dominance to the neural representation of emotional experience.

Acknowledgements This work was supported by funds provided by the Psychology Department of Suffolk University to MWJ and DAG.

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