Callousness and Affective Face Processing: Clarifying the Neural Basis of Behavioral-Recognition Deficits Through the Use of Brain Event-Related Potentials

Abstract

Callousness encompasses a lack of guilt, shallow affect, and deficient affiliative tendencies and relates to severe antisocial behavior. Across developmental stages, callousness is associated with abnormalities in emotional processing, including decreased physiological reactivity to emotional faces. The current study recruited an adult participant sample to investigate selective associations of callousness with deficits in behavioral performance and reduced neurophysiological response within a face-processing task. Participants who scored higher in callousness demonstrated decreased reactivity to fearful faces across temporal components of the electrocortical response along with reduced accuracy in identifying fearful faces. Further analyses demonstrated that late-positive potential amplitude alone was related to behavioral response and mediated the association between callousness and impaired recognition of fearful faces. These findings clarify the nature of face-processing deficits in relation to callousness and have implications for biologically informed interventions to reduce antisocial behavior.

Keywords

electrophysiology antisocial behavior affective processing brain facial expressions

The dispositional construct of callousness entails low guilt and remorse, shallow affect, low empathy, and deficient affiliative tendencies.¹ Highly callous individuals show distinct cognitive and affective characteristics as well as a particularly severe, aggressive, and stable pattern of antisocial behavior beginning in adolescence and continuing into adulthood (Frick, Ray, Thornton, & Kahn, 2014). As such, callousness is considered a central component of psychopathic personality (psychopathy) in children and adults (Frick et al., 2014; Patrick & Drislane, 2015). Studies have found that callousness is marked by a lack of sensitivity to others’ emotional states as well as by neural and behavioral deficits in responding to emotional faces (Dawel, O’Kearney, McKone, & Palermo, 2012; Marsh et al., 2008). Expressive faces are information-rich, visual-affective stimuli, and to perceive them effectively, visual processing of facial features is required along with the recognition of emotional-expressive elements (Frank & Stennett, 2001; Kanwisher, McDermott, & Chun, 1997). Sensitivity to the emotional content of faces in particular functions to orient attention, shape learning, and influence subsequent behaviors (Blair, 1995). Further research is needed to better understand the relationship of callousness with decreased sensitivity to affective facial cues, as indexed by impaired recognition performance and reduced neural responsiveness.

Dispositional Callousness in Adults

While callousness has been studied extensively within the youth psychopathy literature, with considerable evidence emerging for a critical distinction between conduct disorder with and without callous–unemotional traits (e.g., Frick et al., 2014; Viding & Kimonis, 2018), recent work has sought to index and validate this construct in adults (Brislin et al., 2017; Kimonis, Branch, Hagman, Graham, & Miller, 2013). Initial evidence from studies assessing callousness in adults provides evidence for emotional-reactivity deficits similar to those found in highly callous youth (Brislin et al., 2017; Fanti, Panayiotou, Kyranides, & Avraamides, 2016; Kyranides, Fanti, & Panayiotou, 2015; Mowle, Edens, Ruchensky, & Penson, 2018). However, research of this kind has yet to integrate data from the domains of physiology and behavior to better understand the time course of aberrant neural responding and its relationship to behavioral-recognition effects indicative of decreased emotional sensitivity.

Studies with child and adolescent participants have consistently found evidence for abnormal processing of facial (and other) emotional stimuli in a distinct subgroup of individuals diagnosed with conduct disorder: those exhibiting callous features alongside impulsive-disinhibitory symptoms (Herpers, Scheepers, Bons, Buitelaar, & Rommelse, 2014). Brislin et al. (2017) recently presented evidence for facial-processing deficits in adults high in callousness, but callousness was highly correlated with disinhibitory symptoms in this sample. In addition, another recent study of adolescents found that participants with conduct disorder who also scored high in callous–unemotional (CU) traits were better at identifying fearful faces, although CU traits overall were associated with poorer emotion recognition (Martin-Key, Graf, Adams, & Fairchild, 2018). Thus, further research is needed to determine whether observed deficits in adults are specific to callousness or attributable in part to other symptomatic features (facets) of psychopathy.

The triarchic model posits that three distinct but critical facets give rise to psychopathic personality: boldness, callousness (termed meanness within the model), and disinhibition. The current study was undertaken to investigate whether decreased physiological and behavioral sensitivity to emotional cues reflects the unique contributions of callousness, or whether boldness or disinhibition also contribute to affective-processing deficits (or perhaps suppress them; Skeem, Polaschek, Patrick, & Lilienfeld, 2011). Boldness is marked by low threat reactivity, and it is theorized that boldness overlaps with callousness through a shared fearless temperament. However, previous studies of adolescents have not examined the role of boldness, instead focusing on measures of callousness and disinhibition. Disinhibition correlates to a moderate positive degree with callousness in most operationalizations of the triarchic-model constructs (Patrick & Drislane, 2015). By evaluating overlapping versus unique contributions of distinct facets of psychopathy to both neural and behavioral indicants of impaired affective face processing, we sought to inform the clinical understanding of psychopathy as well as other clinical conditions marked by dispositional callousness (e.g., narcissistic personality disorder; Kotov et al., 2017).

Neural Mechanisms of Facial Processing

The neural mechanisms of face perception (i.e., higher-level visual processing of faces; Kanwisher, McDermott, & Chun, 1997) have been studied extensively in healthy adults in the service of understanding basic neurophysiological processes underlying emotional-stimulus recognition and reactivity. A meta-analysis of face-processing studies using functional MRI (fMRI) determined that presentations of emotional faces elicited increased neural activation in a number of visual, limbic, temporoparietal, and prefrontal areas and that this activation differed as a function of emotion type (i.e., fear, anger, disgust, sadness, happiness; Fusar-Poli et al., 2009). fMRI studies, such as those examined in this meta-analysis, are considered spatially sensitive, providing information about differential activation in specific areas of the brain. In contrast, the use of event-related potentials (ERPs) measured using electroencephalography (EEG) provides temporal specificity; that is, it provides information regarding the time course of brain reactivity. For example, the N170, which is sensitive to salient stimuli more broadly, is one component of the face-elicited ERP response. The N170 is a negative deflection that peaks approximately 170 ms after the presentation of a stimulus and occurs maximally at temporal-parietal scalp sites. As in the meta-analysis by Fusar-Poli et al. (2009), who demonstrated face-related activation in the visual cortex, Jiang et al. (2009) demonstrated that the N170 is related to face detection and categorization in healthy adults. Further, the N170 component is reliably larger for emotional relative to neutral face stimuli (for a review, see Hajcak, Weinberg, MacNamara, & Foti, 2012). As such, the N170 constitutes an early cortical response related to face detection and categorization that is sensitive to emotional content and thus potentially useful for clarifying callousness-related impairments in affective face processing.

Another early ERP component implicated in face perception is the P200, a positive-going parietal-waveform deflection occurring approximately 200 ms after face presentation that reflects the encoding of emotional content in facial expressions (Eimer, Holmes, & McGlone, 2003; Paulmann & Pell, 2009). Evidence from the meta-analysis of fMRI study findings by Fusar-Poli et al. (2009) suggests that the limbic system and insular cortex are critical for differentiating between the six basic affective expressions. Within the limbic system, amygdala activation occurs while viewing fearful, happy, and sad faces, with the strongest activation evident for fearful faces, whereas the insula is selectively activated when viewing disgusted faces and, to a lesser extent, angry faces. These differences in functional brain activation are posited to reflect the diverse types of information conveyed by facial expressions, with the amygdala and other limbic regions involved in the emotional response to exteroceptive sensory stimuli and the insular region involved in the emotional response to interoceptive sensory stimuli and body sensations (Fusar-Poli et al., 2009). Although fMRI research provides evidence that different emotions are encoded in different brain regions, impairments in affective processing may also reflect differences in how quickly certain emotional cues are encoded. Therefore, the later-onset P200 represents another important indicator of affective face processing, with potential utility for clarifying neural aspects of callousness-related processing impairments.

Research has also demonstrated that the late-positive potential (LPP), a longer-duration parietal ERP component (i.e., 400–900 ms), is enhanced for affective relative to neutral visual stimuli, including faces (Hajcak et al., 2006; Schupp et al., 2000). Studies have consistently demonstrated a positive association between the amplitude of the LPP and the motivational salience of visual-foreground stimuli (e.g., greater reactivity for more- vs. less-arousing affective pictures; Briggs & Martin, 2009; Weinberg & Hajcak, 2010). Together, this research indicates that the LPP reflects neural activity involved in sustained attention to emotional content (Hajcak et al., 2012). Further, simultaneous EEG-fMRI research has demonstrated associations between LPP amplitude and the degree of activation in the visual cortex (Sabatinelli, Lang, Keil, & Bradley, 2007) as well as in the temporal cortices, amygdala, orbitofrontal cortex, and insula (Liu, Huang, McGinnis-Deweese, Keil, & Ding, 2012). Liu et al. (2012) have also shown that the coupling between the LPP and functional brain activation is category-specific, with pleasant foreground scenes and unpleasant scenes activating different extended brain networks. The LPP is thus a well-understood late-ERP component that is critical to emotional processing and potentially helpful for clarifying neural aspects of impaired face recognition in high-callous individuals.

Generality Versus Specificity of Facial-Affect Processing Deficits Associated With Callousness

Behavioral, physiological, and neuroimaging studies have demonstrated abnormalities in emotional processing among children high in callousness. In particular, meta-analytic work has demonstrated that these children show deficits in accurately identifying affective facial and vocal stimuli (Dawel et al., 2012), with reported effect sizes largest for fearful compared with other emotional stimuli (Blair, Colledge, Murray, & Mitchell, 2001; Marsh & Blair, 2008). Blair (1995) hypothesized that deficient processing of distress cues (e.g., fear expressions) contributes to psychopathic tendencies by inhibiting normal social learning and interfering with moral development. In line with this view is evidence that children high in callousness show reduced attention to the eye regions when processing emotional faces (Billeci et al., 2019; Dadds, El Mansry, Wimalaweera, & Guastella, 2008), and this abnormality relates in turn to deficient emotion recognition and low empathy (Billeci et al., 2019; Dadds et al., 2008; Dadds, Jambrak, Pasalich, Hawes, & Brennan, 2011). In addition, fMRI studies have reliably demonstrated that youth high in callousness exhibit diminished amygdala reactivity to fearful face stimuli (Jones, Laurens, Herba, Barker, & Viding, 2009; Lozier, Cardinale, VanMeter, & Marsh, 2014; Marsh et al., 2008; Poeppl et al., 2019). However, much of this research has focused on reactivity to fearful faces, and thus the current study sought to clarify whether callousness is associated with decreased reactivity to fearful faces specifically or to affective facial expressions more broadly.

Current Study Aims and Hypotheses

Based on evidence for impaired recognition of and reduced brain reactivity to emotional face stimuli in children and adolescents high in callousness, the current work tested for analogous effects in young adults. The first major aim, building upon recent work (Brislin et al., 2017), was to evaluate whether callousness is associated with reduced sensitivity to emotional faces in general or fearful faces specifically:

Hypothesis 1a: Participants with high scores in callousness would exhibit less accurate identification of emotional expressions, with fearful faces showing the largest effect (see Dawel et al., 2012; Marsh & Blair, 2008).

Hypothesis 1b: Adults with high scores in callousness would exhibit decreased neural reactivity (i.e., decreased amplitude of N170, P200, and LPP responses) to all emotional faces, with the largest effect for fearful faces (see Brislin et al., 2017).

Although the primary hypotheses of our study focused on associations of callousness with abnormalities in face processing, it is important in studies of specific facets (subdimensions) of psychopathy to consider their covariance with other facets of psychopathy and how this can affect relations with theory-relevant criterion measures (Patrick & Drislane, 2015; Skeem et al., 2011). In the current work, this called for evaluating whether associations between callousness and affective processing were unique to this facet of psychopathy or partly attributable to (or perhaps suppressed by; Skeem et al., 2011) co-occurring levels of boldness or disinhibition.

In particular, Viding and colleagues’ (2012) reported increased amygdala reactivity to fearful faces (relative to healthy control subjects) in adolescents who exhibited conduct problems but scored low in callousness. Such individuals are likely to be high in disinhibition per se (e.g., Sica, Ciucci, Baroncelli, Frick, & Patrick, 2019; Venables et al., 2012) and exhibit heightened rather than deficient stress reactivity (Frick, Lilienfeld, Ellis, Loney, & Silverthorn, 1999; Patrick, Fowles, & Krueger, 2009). Accordingly, we formulated the following specific, but more tentative hypotheses for the trait of disinhibition:

Hypothesis 2a: Disinhibition might be associated with enhanced recognition accuracy for negative emotional faces, especially fear, when controlling for its overlap with callousness

Hypothesis 2b: Disinhibition might be associated with increased ERP reactivity to negative emotional faces, especially fear, when controlling for its overlap with callousness.

A further aim of the current study was to determine whether (a) the predicted neurophysiological deficits reflect a process in common with impaired emotion recognition or (b) associations of these two variables with dispositional callousness are separate. Our third hypothesis favored the former of these possibilities:

Hypothesis 3: Neurophysiological and behavioral deficits, although assessed in distinct measurement modalities, may reflect a common process and thus covary with one another and with callousness across participants.

Method

Participants

Participants were 127 adults (65 women) with a mean age of 19.53 years (SD = 3.67); 125 of these were recruited through undergraduate psychology courses, the remainder (n = 2) being recruited via Craigslist advertisements.² The racial composition of the sample was 76% White, 9% Black, 3% Asian/Indian, and 3% more than one race; the remaining participants (9%) declined to identify their race. Participants completed a lab-testing session in which they were administered questionnaire measures and performed a computerized task (described below) while electrocortical activity was assessed.

Questionnaire measures

The Triarchic Psychopathy Measure (TriPM; Patrick, 2010) is a 58-item questionnaire developed to assess the three constructs of the triarchic model (Patrick et al., 2009), namely meanness, boldness, and disinhibition. The Meanness subscale of the TriPM, which indexes dispositional callousness (Drislane, Patrick, & Arsal, 2014; Patrick & Drislane, 2015), consists of 19 items that index deficient empathy, exploitation of others, and proactive aggressiveness. The Boldness subscale comprises 19 items assessing high self-confidence and social assuredness, emotional resiliency, and fearlessness. The Disinhibition subscale consists of 20 items tapping impulsiveness, irresponsibility, boredom proneness, and thievery. Items of the TriPM are answered on a 4-point Likert scale ranging from 0 (mostly false) to 3 (mostly true). The TriPM’s subscales demonstrate good convergent and discriminant validity in relation to measures of personality as well as psychopathy and other clinical problems across various samples (Drislane, Patrick, & Arsal, 2013; Sellbom & Phillips, 2013). In the current sample, the subscales showed good internal-consistency reliabilities (see Table S1 in the Supplemental Material available online) and intercorrelations consistent with those reported in previous studies (see Table S2).

Laboratory task procedure

As part of a larger task battery, participants completed a facial-emotion-recognition task during which EEG was continuously recorded. Participants viewed face stimuli (Ekman & Friesen, 1976) expressing anger, disgust, fear, happiness, sadness, and surprise at six levels of expressive intensity ranging from low to high; intensity has been found to modulate behavioral performance (accuracy) and ERP amplitude (Marsh, Yu, Pine, & Blair, 2010; Sprengelmeyer & Jentzsch, 2006). Each face was presented for 500 ms, after which the participant had 3,500 ms to choose one of six emotion labels for the face. Overall accuracy scores (percentage correct of 12 trials) were calculated for each expression as a function of intensity, collapsed down to three levels (low, middle, and high) to increase score stability and simplify analyses.

Physiological measurement and data reduction

Scalp EEG activity was recorded from 128 electrode sites using a NeuroScan Quik-Cap (Compumedics USA, Charlotte, NC). The raw EEG signal was continuously recorded at a rate of 1000 Hz using a Neuroscan Synamps system, band-pass filtered between 0.05 and 200 Hz, and referenced online to Quick-Cap nonstandard layout electrode site 64, corresponding to 10–20 system site CPz. The filtered continuous EEG recording was then divided into epochs offline from 1,000 ms before to 2,000 ms after stimulus onset and averaged across trials within each emotion condition. EEG data from the emotion-recognition task were quantified identically to the performance data, with 12 trials per condition. The average signal from each epoch was then baseline-corrected by subtracting from each aggregate time point the mean amplitude of EEG activity across a 500-ms prestimulus interval.

Analytic approach

As in prior studies of this kind (Jiang et al., 2009; Shannon, Patrick, Venables, & He, 2013), N170 amplitude was quantified as an aggregate across two clusters of temporal-parietal and parietal electrodes (left: sites corresponding to P5, P7, TP7, and T7; right: sites corresponding to P6, P8, TP8, and T8) referenced to the midline-site CPz. Activity from the midline parietal electrode site (PZ), referenced to linked mastoids, was used to quantify P200 and LPP amplitude (Brislin et al., 2017; Shannon et al., 2013). N170 and P200 ERP components were defined, respectively, as peak activity during windows of 150 to 230 ms and 150 to 300 ms following face-stimulus onset. LPP response was defined as mean activity during a subsequent window of 400 to 980 ms.

As an initial analytic step, two-way repeated measures analyses of variance (ANOVAs) were used to test for the effects of emotion (six levels) and intensity (three levels) on behavioral- and physiological-response measures in the sample as a whole. Bivariate correlation and regression analyses were then used to test Hypotheses 1 and 2, pertaining to associations of behavioral-recognition and ERP responses to faces with scores on the three scales of the TriPM; the regression analyses were used to test for associations of callousness and the other two triarchic traits (disinhibition, boldness) with physiological and behavioral indices of face processing, when controlling for their overlap with one another (see Drislane & Patrick, 2017; Drislane, Patrick, & Arsal, 2014). Effects for the single behavioral measure, recognition accuracy, were tested using a .05 significance threshold. Effects for the four brain ERP measures—right and left N170, midline P200, and midline LPP—were tested using a corrected α threshold of p ≤ .0125 (i.e., .05/4).³ Finally, Hypothesis 3 was tested by examining bivariate correlations between physiological- and behavioral-response measures and through the use of hierarchical regression to test for unique versus overlapping contributions of reduced emotion-recognition accuracy and physiological reactivity in predicting TriPM Meanness scores.

Results

Emotion-recognition accuracy and triarchic psychopathy facets

Significant Facial Expression × Intensity interactions were found for recognition accuracy (see Supplemental Results in the Supplemental Material). Therefore, the analytic plan for Hypothesis 1a was amended post hoc to allow for variability in the predicted callousness-accuracy relationship as a function of intensity level. Specifically, we ran a two-way mixed-model ANOVA with TriPM Meanness scores included as a continuous between-subjects factor and fear-face intensity included as a discrete within-subjects factor. This analysis revealed a significant quadratic component to the Meanness × Intensity interaction, F(1, 117) = 4.14, p < .05, η_p² = .03, reflecting a significant association between meanness and accuracy at the middle-intensity level only and not at the low or high levels (see Table 1). This interaction is depicted graphically in Figure 1, which shows average fear-recognition accuracy at each intensity level for participants in the top and bottom quartiles of the score distribution for TriPM Meanness. Two-way mixed-model ANOVAs for the other facial expressions yielded no significant main or interactive effects for meanness, and correlational analyses revealed no significant association for meanness with expressions other than fear at any level of intensity (Table 1).

Table 1.

Associations between TriPM Scores and the Accurate Identification of Emotions

Face type	r (β)			R
Face type	Boldness	Meanness	Disinhibition	R
Emotion recognition (total)	−.03 (−0.01)	−.13 (−0.07)	−.14 (−0.11)	.16
Anger	−.01 (−0.02)	.02 (0.03)	.00 (−0.12)	.02
Low intensity	−.08 (−0.07)	.01 (−0.02)	.09 (0.10)	.12
Mid intensity	.01 (−0.01)	.02 (0.05)	−.05 (−0.08)	.07
High intensity	.05 (0.04)	.02 (0.04)	−.05 (−0.07)	.08
Disgust	−.01 (−0.02)	−.07 (−0.01)	−.13 (−0.13)	.13
Low intensity	.04 (0.04)	−.10 (−0.03)	−.20* (−0.18)	.19
Mid intensity	−.12 (−0.12)	−.07 (−0.02)	−.06 (−0.06)	.13
High intensity	.05 (0.04)	−.01 (0.03)	−.09 (−0.11)	.11
Fear^a	.04 (0.08)	−.14 (−0.17)	−.05 (0.04)	.16
Low intensity	.07 (0.10)	−.09 (−0.12)	−.06 (0.00)	.13
Mid intensity	.03 (0.09)	−.20* (−0.23*)	−.10 (0.01)	.22
High intensity	.01 (0.03)	−.05 (−0.10)	.03 (0.08)	.09
Happiness	−.07 (−0.07)	−.11 (−0.04)	−.15 (−0.13)	.17
Low intensity	−.07 (−0.07)	−.09 (−0.01)	−.14 (−0.14)	.16
Mid intensity	−.02 (−0.01)	−.14 (−0.10)	−.14 (−0.09)	.16
High intensity	−.10 (−0.11)	−.01 (0.04)	−.03 (−0.06)	.11
Sadness	−.07 (−0.07)	−.10 (−0.01)	−.16 (−0.16)	.17
Low intensity	−.06 (−0.07)	−.06 (0.02)	−.12 (−0.13)	.14
Mid intensity	−.05 (−0.06)	−.05 (0.02)	−.11 (−0.13)	.13
High intensity	−.05 (0.04)	−.13 (−0.06)	−.15 (−0.12)	.17
Surprise	−.09 (−0.10)	−.08 (0.01)	−.13 (−0.13)	.16
Low intensity	−.11 (−0.14)	−.02 (0.09)	−.10 (−0.15)	.17
Mid intensity	−.04 (−0.03)	−.08 (−0.06)	−.07 (−0.05)	.10
High intensity	−.06 (−0.06)	−.13 (−0.05)	−.15 (−0.13)	.17

Note: N = 119. TriPM = Triarchic Psychopathy Measure; r = Pearson correlation coefficient; β = standardized coefficient from regression model incorporating scores for the TriPM scales as predictors.

Hypothesized a priori.

p < .05.

Fig. 1.

Average accuracy score for identification of fearful faces at low, medium, and high levels of expressive intensity for individuals scoring in the top (solid black line) versus bottom (solid gray line) quartiles on the TriPM Meanness scale compared with participants scoring in the middle two quartiles (dashed line).

In contrast with meanness, counterpart analyses for TriPM Disinhibition yielded a significant negative association with recognition accuracy for low-intensity disgust faces but no significant association with recognition accuracy for faces of any other type—including fearful faces—at any intensity level. TriPM Boldness showed no significant association with accuracy for any facial expression at any intensity level. When all three scales were entered into a regression model as predictors of fear-recognition accuracy at the medium-intensity level, TriPM Meanness emerged as the only significant, unique predictor, and higher scores on this TriPM scale predicted poorer recognition accuracy at this intensity level.

Brain response and triarchic psychopathy facets

No effects of affective face intensity were evident for the N170 and P200 ERP components (see the Supplemental Results in the Supplemental Material) and thus correlations of the three TriPM scales with N170 and P200 were examined for each affective face type, collapsing across intensity levels. These correlational results are presented in Table 2.

Table 2.

Associations between TriPM Scores and ERP Responses to Emotional Faces

Face type	r (β)			R
Face type	Boldness	Meanness	Disinhibition	R
N170 (left)
Anger	.14 (0.11)	.07 (0.11)	−.10 (−0.15)	.19
Disgust	.12 (0.09)	.05 (0.11)	−.12 (−0.18)	.19
Fear^a	.10 (0.02)	.15 (0.29*)	−.13 (−0.28*)	.29
Happiness	.11 (0.07)	.08 (0.14)	−.09 (−0.17)	.19
Sadness	.12 (0.05)	.14 (0.22)	−.08 (−0.19)	.23
Surprise	.11 (0.07)	.07 (0.12)	−.11 (−0.17)	.18
N170 (right)
Anger	.08 (0.02)	.15 (0.21)	−.03 (−0.13)	.19
Disgust	.16 (0.10)	.18 (0.21)	−.01 (−0.12)	.23
Fear^a	.05 (−0.04)	.21 (0.30*)	.00 (−0.15)	.25
Happiness	.10 (0.03)	.17 (0.26)	−.07 (−0.20)	.25
Sadness	.09 (0.03)	.19 (0.23)	.02 (−0.10)	.21
Surprise	.06 (−0.01)	.17 (0.22)	−.01 (−0.12)	.20
P200
Anger	−.10 (−0.06)	−.09 (−0.12)	.03 (0.09)	.14
Disgust	−.12 (−0.08)	−.09 (−0.14)	.09 (0.16)	.19
Fear^a	−.12 (−0.05)	−.15 (−0.25*)	.11 (0.23)	.26
Happiness	−.10 (−0.05)	−.12 (−0.17)	.07 (0.15)	.18
Sadness	−.08 (−0.04)	−.11 (−0.15)	.03 (0.12)	.15
Surprise	−.08 (0.01)	−.16 (−0.28)	.14 (0.27)	.28
LPP
Anger	.10 (0.12)	.03 (−0.06)	.08 (0.11)	.14
Disgust	.04 (0.05)	−.07 (−0.02)	−.14 (−0.13)	.15
Fear^a	.06 (0.14)	−.19 (−0.29*)	−.03 (0.11)	.25
Happiness	−.03 (0.02)	−.09 (−0.17)	.08 (0.16)	.16
Sadness	.13 (0.22)	−.16 (−0.30*)	−.01 (0.14)	.28
Surprise	−.02 (0.04)	−.11 (−0.20)	.08 (0.17)	.19

Note: N = 118. ERP = event-related potential; TriPM = Triarchic Psychopathy Measure; r = Pearson correlation coefficient; β = standardized coefficient from regression model incorporating scores for the TriPM scales as predictors; LPP = late-positive potential.

Hypothesized a priori.

p ≤ .0125.

TriPM scale scores were not significantly associated with N170 amplitude to emotional faces at the zero-order level. However, regression models including all three TriPM scales as predictors of N170 to fearful faces revealed a cooperative suppressor effect (Cohen & Cohen, 1975) in which weak zero-order associations of meanness and disinhibition with N170 response became stronger in the joint-prediction context. Associations for meanness with both right and left N170 became significantly positive (reflecting diminished amplitude of the negative-going response at higher levels of meanness), whereas associations for disinhibition became more negative (i.e., reflecting enhanced amplitude of response), achieving significance at the left temporal-parietal site. Regression analyses for the other facial expressions revealed that meanness and disinhibition showed no significant associations with N170 response to facial expressions other than fear in either bivariate or regression analyses, and boldness showed no significant associations with N170 response to facial expressions in correlation or regression analyses.

TriPM Meanness was not significantly associated with P200 response to fearful faces at the bivariate level, but a regression analysis including TriPM Boldness and Disinhibition scores as copredictors did yield a significant negative β regression coefficient for meanness (see Table 2). Again, cooperative suppression was evident between meanness and disinhibition, such that their nonsignificant, opposing relations with P200 to fearful faces increased to significance within the regression model. Meanness was not significantly associated with amplitude of P200 response to any other emotional expressions, and disinhibition and boldness showed no significant associations with P200 response to facial expressions of any type in either bivariate or regression analyses.

Given evidence for a linear effect of expressive intensity on LPP reactivity (see Supplemental Results in the Supplemental Material), we tested for effects of TriPM Meanness on LPP response to each facial expression as a function of intensity, using a two-way mixed-model ANOVA that included both meanness and intensity as continuous and discrete factors, respectively. No significant interactive effects of meanness and intensity were evident for LPP, and thus overall LPP amplitude (collapsing across intensity levels) was used for each facial expression in subsequent analyses. Meanness was not significantly predictive of LPP amplitude at the zero-order level for any facial expression; however, meanness showed a significant negative association with LPP response to fearful and sad faces in regression models controlling for boldness and disinhibition (see Table 2).

Emotion-recognition accuracy, brain response, and triarchic psychopathy facets

Bivariate correlations were first used to test for associations between emotion-recognition accuracy and ERP responses for each facial expression across participants, irrespective of TriPM Meanness score (see Table S3 in the Supplemental Material). Covariation between recognition accuracy and brain responsiveness was evident only for the LPP, which showed greater amplitude in relation to higher recognition accuracy for disgusted, fearful, and happy faces and in relation to recognition accuracy as a whole (i.e., across all face types). Amplitude of LPP response to sad faces was also significantly related to recognition accuracy as a whole but not to recognition accuracy for sad faces specifically.⁴

Given that emotion-recognition accuracy for fearful faces showed a significant bivariate association with LPP response to fearful faces, a three-step hierarchical regression analysis was performed to evaluate whether fear-recognition accuracy and LPP response to fearful faces operated as unique or overlapping predictors of TriPM Meanness (see Table S4 in the Supplemental Material). In Step 1, TriPM Boldness and Disinhibition were entered as covariates. In Step 2, mid-intensity fear-recognition accuracy was entered as a predictor, resulting in a significant model R² change (β = −0.17, p = .045). In Step 3, LPP response to fearful faces was entered as the final predictor. At this step, LPP response evidenced a significant β coefficient, and its inclusion in the model produced a significant increase in R² (p < .05). The predictive association for fear-recognition accuracy was reduced to nonsignificance at this step of the model (β = −0.11, p > .05), indicating that its association overlapped with that of LPP.

Discussion

The current study used a novel experimental approach to evaluate how variations in the psychopathic trait of callousness, operationalized as TriPM Meanness, relate to neural processing and the behavioral recognition of emotional expressions. The measurement within the same task of temporally sensitive neural responsivity (via ERPs) along with behavioral performance (via emotion-recognition accuracy) allowed for a direct and nuanced examination of brain-behavior dynamics associated with the aberrant face processing exhibited by high-callous individuals. These data yielded evidence that deficits in reactivity to fearful faces are present across the time course of face processing and that later elements of this neural cascade are associated with impaired manifest performance in identifying fearful faces. Findings from the current study also highlight the importance of accounting for co-occurring disinhibitory tendencies in research on callousness.

Recognition accuracy for emotional faces and relations with callousness

The negative association between recognition accuracy for fearful faces and TriPM Meanness scores, at both the bivariate level and within the regression model, accords with previous research demonstrating negative associations between trait callousness and recognition accuracy for fear expressions (Brislin et al., 2017; Dawel et al., 2012). Analyses that examined the interaction between meanness and expressive intensity revealed a significant quadratic effect for meanness in the identification of fearful faces (see Fig. 1). This finding indicates that individuals who scored high in meanness were less sensitive to fearful faces, such that they needed to appear at a higher level of intensity to be accurately identified. Follow-up analyses indicated that individuals who scored high in meanness were less accurate at identifying fearful faces at the mid-intensity level specifically, consistent with a higher recognition threshold. Moreover, the Meanness × Intensity interaction was significant only for fearful faces, despite the fact that average accuracy scores for fearful faces were not significantly different from those for anger and disgust (i.e., they were all similarly “difficult”). Given these results, future studies seeking to examine behavioral effects in community adults should consider the intensity level of affective face stimuli as a moderator.

Physiological response to emotional faces and relations with callousness

In preliminary analyses examining basic task effects, facial expression and intensity level were not related to either right or left N170, suggesting that this very early component of brain response to faces was relatively insensitive to variations in distinct affective-expressive features. Notably, prior work has shown a differential N170 response for affective compared with neutral faces (e.g., Anokhin & Golosheykin, 2010; Paulmann & Pell, 2009), so it may be that N170 is responsive to affective features generally but not to nuances of expression. For the P200 component of the face-ERP response, there was a main effect of affective face type, reflecting a reduced amplitude of reactivity to angry faces relative to faces of other types. The amplitude of the later LPP was lower as well for angry faces relative to other face types, and happy faces also evoked a smaller LPP than fearful, disgusted, sad, or surprised faces.

With regard to callousness, results from the current study replicate and, importantly, extend previous findings indicating that individuals with high levels of callousness exhibit decreased ERP amplitude to fearful faces from a very early point in neural processing (Fig. 2). Findings reported here are consistent with results reported by Brislin et al. (2017) and Eisenbarth and colleagues (2013) demonstrating associations for callousness with N170 and P200 responses to fearful faces. In addition, the current study found that higher scores on TriPM Meanness were associated with lesser amplitude of LPP response to fearful faces. The Brislin et al. (2017) study did not find associations between LPP amplitude and callousness; however, the parameters of the task used in the current work differed in notable ways from the task used in that study. In the current study, participants were asked to view and then categorize each face stimulus, a task likely to evoke greater elaborative-associative processing of faces, reflected in the LPP response. In contrast, the task used by Brislin et al. (2017) required participants to simply view the emotional face stimuli. Consistent with the findings from the current study, previous studies have found heightened TriPM Meanness to be associated with blunted LPP response to images of aggressive situations (van Dongen, Brazil, van der Veen, & Franken, 2018). Replication and further investigation of the relationship between LPP amplitude and callousness observed here will likely require the use of more cognitively engaging tasks. Considered as whole, current study findings suggest that, among individuals high in callousness, when controlling for co-occurring facets of psychopathy, fearful faces elicit a weaker neural response across the entire time course of viewing, and this neural response contributes to deficits in categorizing the affective features of fearful faces.

Fig. 2.

Average brain event-related potential (ERP) waveforms for fearful face stimuli for participants scoring in the top (black) and bottom (gray) tertiles on the Triarchic Psychopathy Measure (TriPM) Meanness scale. The average waveforms for the N170 ERP component, graphed in (a), are quantified as average activity measured at electrodes corresponding to 10–20 site P8, one of the right temporal-parietal electrodes used to form the right N170 cluster, referenced to the midline-site CPz for participants scoring high versus low in meanness. The average waveforms for the P200 and LPP components, graphed in (b), are quantified as average activity measured at the midline parietal scalp site (corresponding to 10–20-site PZ), referenced to linked mastoids, for participants scoring high versus low on the TriPM Meanness scale.

Results of the current study also demonstrated a cooperative suppressor effect in the correlations of meanness and disinhibition with ERP response to fearful faces. When controlling for the overlap between TriPM Meanness and scores for the other two TriPM scales, the magnitude of associations for both meanness and disinhibition with ERP components increased. Note that higher meanness was associated with blunted amplitudes of both earlier (N170, P200) and later (LPP) responses to fearful faces that became more pronounced when controlling for disinhibition, whereas higher disinhibition was associated with enhancements of early ERP responses (N170, P200) that became more pronounced when controlling for meanness. This finding has interesting clinical implications, given that highly disinhibited individuals showing enhanced neural reactivity to fearful facial cues early in the processing cascade may differ in behavioral presentation from highly callous individuals showing reduced early reactivity to fearful faces. For example, highly disinhibited individuals may be more likely to carry diagnoses associated with problematic impulsive and reactive behavior (e.g., substance-use disorder, borderline personality disorder) and exhibit aggressive and rule-breaking behavior as a result of poor emotion regulation. From this perspective, shifting from a purely report-based (questionnaire, interview) measurement of callous and disinhibitory proclivities toward incorporating measures from other modalities, including neurophysiology, can provide insight into heterogeneity within diagnoses such as antisocial personality disorder.

In addition to differences in ERP response to fearful faces, a significant negative association was also evident for TriPM Meanness with LPP reactivity to sad faces when controlling for overlap with TriPM Disinhibition. In addition, although regression βs did not reach the strict threshold for significance given multiple comparisons, TriPM Meanness demonstrated negative albeit nonsignificant associations with LPP amplitude to emotional faces beyond fear (e.g., surprise). Thus, although effects of meanness were consistent and robust for fearful faces—with significant reductions in response observed for all ERP components—observed effects also suggest that high callousness may be associated with a broader impairment in neural response to distress displays, as hypothesized by Blair (1995). In contrast, high meanness was related to impaired behavioral performance (recognition accuracy) only for fearful faces. This suggests that the blunted late-neural (LPP) reactivity observed for sad faces in participants high in callousness reflected some nonperformance-related deficit—perhaps in the elaborative-associative (i.e., connotative) processing that normally occurs for affective stimuli.

Interrelations among brain response, behavioral performance, and callousness

When examining associations between ERP amplitude and emotion-recognition accuracy, LPP was the only component to demonstrate significant associations with accurate identification of faces—specifically, fearful, disgusted, and happy faces. Given that high TriPM meanness was associated with both blunted LPP response and impaired behavioral performance for fearful faces only, hierarchical regression models were used to evaluate the unique versus overlapping associations of behavioral response and LPP amplitude with meanness. When entered as a predictor following boldness, disinhibition, and recognition accuracy, LPP response to fearful faces emerged as a significant negative predictor of TriPM meanness, and recognition accuracy became nonsignificant. This result indicates that the variance in fearful-face recognition that intersected with meanness was accounted for by the interface between LPP and meanness, thereby providing the first direct evidence that impaired recognition of fearful faces in highly callous individuals is attributable to deficient neural responsiveness.

Current study findings also provide important insight into how brain and behavior relate to each other and how they relate in turn to personality traits. Results from our analyses suggest that early processing of fearful faces contributed to later elaborative processing, which, in turn, was significantly and positively associated with the accurate identification of fearful faces. High TriPM meanness, controlling for boldness and disinhibition, was significantly associated with decreased amplitude of all ERP responses to fearful faces, as well as with decreased accuracy of behavioral response.⁵

Limitations and future directions

There are some limitations that should be borne in mind when considering findings from the current work. First, most participants were college students. Follow-up work with adults from the general community as well as with clinical samples (e.g., clients in mental-health settings, prisoners) that include broader representations of age levels and degrees of callousness is needed to establish the generalizability of these findings. In addition, effect sizes for associations between behavioral response and callousness were modest compared with those reported in other studies (Brislin et al., 2017; Dawel et al., 2012). This may be due to the adult, nonclinical nature of the sample. Although considerable variation in TriPM meanness scores was evident in our sample, behavioral effects might well have been stronger if more individuals with extreme levels of meanness had been tested. A further limitation of the study is its cross-sectional nature. Future studies will need to utilize longitudinal designs to determine the developmental course of observed face-processing deficits and the extent to which impairments in behavioral and brain response covary with dispositional callousness across time.

Notwithstanding these limitations, the current study provides valuable new insights into neuropsychological processes underlying aberrant processing of facial expressions in highly callous individuals. Future work incorporating brain-response variables into the measurement of trait callousness may help to quantify callousness in a way that differentiates it more clearly from disinhibition. Results of the current study also provide further evidence that dispositional callousness has referents in diverse domains of measurement and that a multimethod approach will be important to conceptualizing, assessing, and mitigating the effects of this dispositional factor. In line with recent initiatives of the National Institute of Mental Health (Kozak & Cuthbert, 2016), National Institute on Alcohol Abuse and Alcoholism (Kwako, Momenan, Litten, Koob, & Goldman, 2016), and National Research Council (2015), the current work highlights the possibility of utilizing brain and behavioral indicators together with report-based measures to form a cross-domain measurement model for callousness—as has been done recently for the psychopathy-related construct of inhibitory control (inhibition-disinhibition; Venables et al., 2018).

Supplemental Material

Brislin_Supplemental_Material – Supplemental material for Callousness and Affective Face Processing: Clarifying the Neural Basis of Behavioral-Recognition Deficits Through the Use of Brain Event-Related Potentials

Supplemental material, Brislin_Supplemental_Material for Callousness and Affective Face Processing: Clarifying the Neural Basis of Behavioral-Recognition Deficits Through the Use of Brain Event-Related Potentials by Sarah J. Brislin and Christopher J. Patrick in Clinical Psychological Science

Footnotes

Acknowledgements

We are grateful to E. R. Perkins for providing input on a draft of this manuscript and to Kara Hulstrand and Keenan Roberts for assistance with data collection.

Action Editor

Scott O. Lilienfeld served as action editor for this article.

Author Contributions

S. J. Brislin and C. J. Patrick developed the study concept and contributed to the study design. S. J. Brislin analyzed and interpreted the data under the supervision of C. J. Patrick. S. J. Brislin drafted the manuscript, and C. J. Patrick provided critical revisions. Both authors approved the final version of the manuscript for submission.

ORCID iD

Sarah J. Brislin

Declaration of Conflicting Interests

The author(s) declared that there were no conflicts of interest with respect to the authorship or the publication of this article.

Funding

This work was supported by U.S. Army Grant W911NF-14-1-0018, National Science Foundation Graduate Research Fellowship Award 952090, a dissertation research award from the American Psychological Association, and National Institute on Alcohol Abuse and Alcoholism Grant T32-AA007477. The views, opinions, and/or findings contained in this report are those of the authors and shall not be construed as an official position, policy, or decision of the U.S. Department of the Army unless so designated by other documents.

Supplemental Material

Additional supporting information can be found at

Notes

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