Dissociable effects of psychopathic traits on cortical and subcortical visual pathways during facial emotion processing:
An ERP study on the N170
PEDRO R. ALMEIDA,a,b FERNANDO FERREIRA-SANTOS,a JOANA B. VIEIRA,a,c PEDRO S. MOREIRA,a,b
FERNANDO BARBOSA,a and JOÃO MARQUES-TEIXEIRAa a Laboratory of Neuropsychophysiology, Faculty of Psychology and Educational Sciences, University of Porto, Porto, Portugal
School of Criminology, Faculty of Law, University of Porto, Porto, Portugal
Faculty of Medicine, University of Porto, Porto, Portugal
b c Abstract
This study examined the relation between psychopathic traits and the brain response to facial emotion by analyzing the
N170 component of the ERP. Fifty-four healthy participants were assessed for psychopathic traits and exposed to images of emotional and neutral faces with varying spatial frequency content. The N170 was modulated by the emotional expressions, irrespective of psychopathic traits. Fearless dominance was associated with a reduced N170, driven by the low spatial frequency components of the stimuli, and dependent on the tectopulvinar visual pathway. Conversely, coldheartedness was related to overall enhanced N170, suggesting mediation by geniculostriate processing. Results suggest that different dimensions of psychopathy are related to distinct facial emotion processing mechanisms and support the existence of both amygdala deficits and compensatory engagement of cortical structures for emotional processing in psychopathy.
Descriptors: Psychopathic traits, N170, Facial emotion
Although psychopathy has frequently been related to impairments in processing facial fear, with these deficits being regarded as building blocks in the developmental emergence of the psychopathic phenotype (e.g., Blair, 2005), behavioral studies are not unanimous in supporting these deficits. Results vary from the report of no differences between groups (Glass & Newman,
2006) to deficits in specific emotions (Blair et al., 2004), general impairments (Hastings, Tangney, & Stuewig, 2008), or even enhanced ability to detect facial emotion (Book, Quinsey, &
Langford, 2007). Studies that show impaired processing (Blair &
Cipolotti, 2000; Blair et al., 2004; Iria & Barbosa, 2009;
Mitchell, Avny, & Blair, 2006; Montagne et al., 2005; Munro et al., 2007) either rely on morphed images (Blair & Cipolotti,
2000; Blair et al., 2004; Mitchell et al., 2006; Montagne et al.,
2005) or on fast-paced experimental tasks (Iria & Barbosa, 2009;
Munro et al., 2007). On the contrary, when participants are stimulated with 100% intensity pictures and given unlimited time to answer, studies tend to show no impairments (Campanella,
Vanhoolandt, & Philippot, 2005; Glass & Newman, 2006;
Gordon, Baird, & End, 2004; Pham & Philippot, 2010) or superior performance by individuals scoring higher in psychopathy (Book et al., 2007; Del Gaizo & Falkenbach, 2008). Functional brain imaging studies of facial emotion processing in psychopathy have reported reduced amygdala response in adults
(Gordon et al., 2004) and children (Jones, Laurens, Herba,
Barker, & Viding, 2009) with psychopathic tendencies, but higher activation of the dorsolateral prefrontal cortex (DLPFC; Gordon
Psychopathy is a syndrome comprising a cluster of affective, interpersonal, and behavioral attributes, such as a disregard for the rights of others, a tendency to lie and manipulate, impulsivity, sensation seeking, shallow affect, lack of self-control, empathy, or remorse (Hare, 2007). Psychopaths are described as bold and/or mean individuals, who usually express these characteristics by behaving in ways considered morally inappropriate, to gain some sort of material or social benefit (Patrick, Fowles, & Krueger,
2009). There is evidence that psychopathic traits are continuously distributed in the general population (Krueger, Markon, Patrick, &
Iacono, 2005; Lilienfeld & Widows, 2005; Skeem, Polaschek,
Patrick, & Lilienfeld, 2011), and, when present in high levels, are associated with increased tendency to engage in antisocial, but not necessarily criminal, behavior (Cooke & Michie, 2001; Kahn,
Byrd, & Pardini, 2013; Viding, Simmonds, Petrides, &
Frederickson, 2009).
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Pedro R. Almeida (SFRH/BD/38711/2007), Fernando Ferreira-Santos
(SFRH/BD/64071/2009), and Joana B. Vieira (SFRH/BD/76254/2011) were supported by the Portuguese Foundation for Science and Technology.
The authors would like to thank Eva C. Martins for her suggestions regarding data anaysis and Sofia Leite for her assistance in data collection. The authors would further like to thank the anonymous reviewers for their valuable comments that helped improve the quality of the paper.
Address correspondence to: Pedro R. Almeida, Laboratório de
Neuropsicofisiologia, Faculdade de Psicologia e de Ciências da Educação,
Universidade do Porto – Rua Alfredo Allen, 4200-135 Porto, Portugal.
E-mail: palmeida@fpce.up.pt
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646 et al., 2004). This reciprocal pattern of activation in response to socioaffective stimuli has been observed in other tasks, namely, involving semantic processing (Intrator et al., 1997; Kiehl et al.,
2001), negotiation (Rilling et al., 2007), moral judgment (Glenn,
Raine, & Schug, 2009; Glenn, Raine, Schug, Young, & Hauser,
2009), and theory of mind (Sommer et al., 2010), suggesting that individuals scoring higher in psychopathic traits may recruit areas devoted to strategic and effortful processing (such as the DLPFC) to analyze socioaffective information (Kiehl, 2006).
In the present study, we aimed to clarify how psychopathic traits affect the brain mechanisms involved in facial emotion processing by characterizing, for the first time, the response of the
N170 component to emotional faces in healthy individuals varying in psychopathic traits. The N170 component has been shown to be dominant for faces and eyes (Taylor, Itier, Allison, &
Edmonds, 2001) and is substantially reduced or absent in response to nonfacial stimuli (Bentin, Allison, Puce, Perez, &
McCarthy, 1996; Itier & Taylor, 2004). It is generated in a network containing the posterior fusiform gyrus (Deffke et al.,
2007), which has been extensively associated with face processing (Kanwisher, McDermott, & Chun, 1997). Several studies show that the N170 is sensitive to the emotional aspects of facial stimuli (Batty & Taylor, 2003; Blau, Maurer, Tottenham, &
McCandliss, 2007; Caharel, Courtay, Bernard, Lalonde, & Rebai,
2005; Leppänen, Moulson, Vogel-Farley, & Nelson, 2007; Rigato,
Farroni, & Johnson, 2010; but see Eimer & Holmes, 2002; Eimer,
Holmes, & McGlone, 2003; Holmes, Vuilleumier, & Eimer,
2003). According to dual-route models of emotion processing, visual emotional information follows at least two distinct pathways to the visual cortex, and hence to the generators of the
N170 (Tamietto & de Gelder, 2010; but see Pessoa & Adolphs,
2010). The magnocellular tectopulvinar pathway (superior colliculi–pulvinar–amygdala) is thought to allow the rapid detection of emotional expressions by the amygdala, which in turn modulates cortical activity along various regions of the visual ventral stream through multiple reentrant connections (Tamietto
& de Gelder, 2010; Vuilleumier, Richardson, Armony, Driver, &
Dolan, 2004). This pathway depends essentially on coarse, low spatial frequency (LSF) information, to which fast-acting magnocellular neurons are especially responsive (Pourtois, Dan,
Grandjean, Sander, & Vuilleumier, 2005; Vuilleumier, Armony,
Driver, & Dolan, 2003). In contrast, the geniculostriate pathway
(lateral geniculate body of the thalamus–striate cortex) contains slower parvocellular neurons and conveys highly detailed visual information with both LSF and high spatial frequency (HSF) content (Merigan & Maunsell, 1993). A common method of differentiating cortical and subcortical influences in visual processing is the dissociation of the magno- and parvocellular visual channels. This is accomplished by manipulating the spatial frequency in which stimuli are presented (Holmes, Green, &
Vuilleumier, 2005; Pourtois et al., 2005; Vlamings, Goffaux, &
Kemner, 2009; Vuilleumier et al., 2004). In general, high spatial frequencies are critical for the processing of detailed visual shape and texture (e.g., Norman & Ehrlich, 1987; Tieger & Ganz,
1979), and low spatial frequencies convey coarse information about shadow-related contours of the face, regarding the relative positions of eyes, nose, and mouth (e.g., Bachmann, 1991;
Costen, Parker, & Craw, 1996). In this study, in addition to exposing participants to stimuli containing the full range of visual frequencies (broad spatial frequency, BSF), we also used stimuli selectively filtered for high and low spatial frequencies. Through this manipulation, we expected to gain additional insights into the
P.R. Almeida et al. brain mechanisms underlying facial emotion processing in psychopathy. Although the modulation of the visual cortex by the emotional properties of facial stimuli has been shown to be highly dependent on the amygdala (Hadj-Bouziane et al., 2012; Vuilleumier et al.,
2004), alterations of N170 amplitude may reflect either the contribution of amygdala output to the visual cortex (Vuilleumier et al.,
2004), or the engagement of neural populations along the visual cortex, independently of amygdala contribution (Gordon et al.,
2004; Rotshtein et al., 2010), and possibly under the influence of parietal and frontal regions (Barcelo, Suwazono, & Knight, 2000;
Corbetta, Shulman, Miezin, & Petersen, 1995). Emotional modulation of the visual cortex independent of amygdala output is illustrated in studies with amygdala-lesioned patients (Rotshtein et al.,
2010) and individuals with autism (Perlman, Hudac, Pegors,
Minshew, & Pelphrey, 2011). Amygdala-lesioned patients have been shown to be able to normalize their performance in relation to controls in facial identification tasks when relying on detailed feature analysis (Graham, Devinsky, & LaBar, 2006) or when instructed to focus their attention on the eyes of the target (Adolphs et al., 2005). Similarly, using a sample of children and adolescents,
Dadds and colleagues (2006) have shown that the association between callous-unemotional psychopathic traits and poorer ability to identify facial fear may be corrected by instructing participants to focus on the eyes of the target. Focusing attention on the eyes of the target has been shown to enhance the activation of the visual cortex, independently of amygdala activation (Perlman et al.,
2011). Given that abnormalities in facial emotion processing in psychopathy have been previously associated with amygdala impairment (Blair, 2005; Blair et al., 2004) and that in certain conditions individuals high in psychopathy are able to perform at the level of controls in facial emotion identification tasks, we expected to observe both correlates of reduced amygdala activity and the engagement of compensatory cortical mechanisms in individuals higher in psychopathic traits. Therefore, in individuals high in psychopathy, we expected (a) reductions in N170 to be driven by the tectopulvinar route, and hence be expressed mostly for LSF images; and (b) enhancements in N170 to be expressed as a function of geniculostriate-based processing, and thus be observed for both LSF and HSF stimuli. Such pattern of results would fit with the presence of compensatory engagement of cortical resources for processing facial emotion as a function of increasing psychopathic traits. Method
Participants
Fifty-four male adult participants (aged 18 or above) were recruited from the community (university and Internet forums). Descriptive statistics of demographic and psychopathy assessment values are presented in Table 1 (see Figure 1 for the distribution of psychopathy scores). Following previous studies with community samples
(e.g., Glenn, Raine, & Schug, 2009; Gordon et al., 2004), we restricted our sample to male participants, since this procedure increases the likelihood of enrolling participants with higher psychopathy scores. All participants were right-handed and had normal or corrected-to-normal vision. They also reported no history of neuropathologies, psychiatric illness, head injuries, or substance abuse. Informed consent was obtained from all participants before the beginning of the experiment, and participation in the study was monetarily compensated.
N170 and facial emotion in psychopathy
Table 1. Demographic
Assessment Values
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Characteristics
and
Psychopathy
Mean
Age
Years of education
PPI total
Fearlessness dominance
Self-centered impulsivity
Coldheartedness
SD
Min
Max
23.24
15.04
275.17
107.02
136.67
31.48
3.79
1.36
29.76
16.32
21.94
6.43
18
12
209
69
95
18
37
16
335
151
178
51
Measures
Participants were assessed with the Portuguese version of the
Psychopathic Personality Inventory–Revised (PPI-R; Lilienfeld &
Widows, 2005).1 The PPI-R is a self-report scale designed to assess psychopathic traits dimensionally in nonforensic participants. The dimensional assessment of psychopathy is consistent with the view that psychopathy is a set of traits distributed in continuum in the general population rather than a clinical taxon (Krueger et al.,
2005; Skeem et al., 2011), and therefore may be more reliably assessed using dimensional models of personality (Miller, Lynam,
Widiger, & Leukefeld, 2001). Although it has been developed in community samples, the PPI-R is strongly correlated with psychopathy measures used in forensic settings, such as the Hare
Psychopathy Checklist–Revised (PCL-R; Poythress et al., 2010).
The PPI-R’s items load into eight subscales, seven of which are organized into two higher-order factors: Machiavellian egocentricity, rebellious nonconformity, blame externalization, and carefree nonplanfulness compose the self-centered impulsivity (PPI ScI) factor, whereas the subscales social influence, fearlessness, and stress immunity are organized into the fearless dominance (PPI
FD) factor. One remaining subscale, coldheartedness, does not load on either factor and constitutes an independent dimension
(Benning, Patrick, Hicks, Blonigen, & Krueger, 2003; Benning,
1. Requests concerning the use of the Portuguese version of the instrument should be addressed to Psychological Assessment Resources, Inc.
Patrick, Blonigen, Hicks, & Iacono, 2005). These dimensions are related to distinct personality features and outcomes. Self-centered impulsivity is marked by traits of impulsivity, aggression, recklessness, and self-centeredness, and has been proposed to be closely related to the underlying dimension common to disinhibitory psychopathology (Blonigen, Hicks, Krueger, Patrick, & Iacono, 2005;
Krueger et al., 2002). Its scores are significantly related to antisocial behavior, substance abuse, disinhibition, and DSM-IV ratings of antisocial personality disorder (Benning et al., 2003, 2005;
Blonigen et al., 2010; Miller & Lynam, 2012). Fearless dominance, on the other hand, indexes interpersonal dominance, low anxiety, fearlessness, and narcissism, and has been found to be modestly related, or not at all, with externalizing behaviors such as antisocial behavior, substance abuse, or aggression (Benning et al., 2003,
2005; Miller & Lynam, 2012). Lastly, the coldheartedness subscale indexes callousness, lack of sympathy for others, deficient empathy, and disdain and lack of close attachments, and has been conceptualized as expressing to a great degree the “meanness” facet of psychopathy (Patrick et al., 2009).
Stimuli
A set of 20 pictures2 of five actors displaying facial expressions of anger, fear, disgust, and happiness, plus five neutral/calm expressions, was selected from among the European-American actors of the NimStim Face Stimulus Set3 (Tottenham, Hare, & Casey,
2009). Emotion categories (with the exception of calm/neutral faces) were matched for perceived arousal (according to reference values provided by Ferreira-Santos, de Haan, & Marques-Teixeira, unpublished observations). Pictures were converted to grayscale and enclosed within an oval frame to exclude all hair and nonfacial contours. For each original picture, a LSF and a HSF version was created (see Figure 2). Spatial content of the original images was filtered using a cutoff of > 24 cycles/image for HSF stimuli and of
< 6 cycles/image for the LSF stimuli. Stimuli were presented on a
19-inch screen located about 116 cm from the participant (vertical visual angle = 10°; horizontal visual angle = 7.64°) with a computer running Presentation 0.71 (2003, Neurobehavioral Systems,
Inc., Albany, CA).
Task
The experiment consisted of four blocks of 75 trials, with a short break between the second and third blocks. Each stimulus (one actor, with one expression, in one spatial frequency) was presented four times, once per block, for a total of 20 stimuli per condition
(each emotion for each spatial frequency). Each participant received a different sequence of stimuli, fully randomized within the block. For each trial, a fixation cross was shown for 1,000 ms, followed by a 200-ms stimulus presentation. Interstimulus interval was randomized between 1,000–1,200 ms. Participants were
Figure 1. Distribution of PPI total, fearless dominance, self-centered impulsivity, and coldheartedness scores.
2. Development of the MacBrain Face Stimulus Set was overseen by
Nim Tottenham and supported by the John D. and Catherine T. MacArthur
Foundation Research Network on Early Experience and Brain Development. Contact Nim Tottenham at tott0006@tc.umn.edu for more information concerning the stimulus set.
3. The pictures used were: Anger: 08F_AN_C, 01F_AN_C,
22M_AN_O, 07F_AN_O, 09F_AN_O; Disgust: 06F_DI_C, 29M_DI_C,
31M_DI_C, 06F_DI_O, 29M_DI_O; Fear: 07F_FE_C, 05F_FE_O,
36M_FE_O, 33M_FE_O, 10F_FE_O; Happiness: 01F_HA_O,
01F_HA_X, 05F_HA_X, 20M_HA_X, 31M_HA_X, 36M_HA_X;
Neutral: 02F_NE_C, 30M_NE_C, 35M_CA_C, 34M_NE_C, 32M_NE_O.
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P.R. Almeida et al. corrected from −200 to 0 ms, and averaged by condition for each participant. The peak amplitude of the N170 was measured on the
[130, 220] ms time window at P7 and P8. All data processing was performed using ASA, v. 4.8 (2011, ANT, Enschede, The Netherlands). A single trial analysis (see online Supporting Information) revealed no evidence of habituation across the experimental session. Statistical Analysis
The effect of psychopathic traits on the amplitude of the N170 in response to facial stimuli was analyzed using separate general linear models for each spatial frequency condition (BSF, HSF, and
LSF), with expression (anger, disgust, fear, happy, neutral) and hemisphere (right, left) as within-subject factors, and using the continuous zero-centered values of PPI FD, PPI ScI, and coldheartedness as continuous predictors. Interactions involving psychopathy were decomposed by analyzing the relation between the absolute N170 amplitude and the relevant psychopathy dimension at each level of the moderating variable. We used the absolute N170 amplitude for this analysis to simplify the readability of the correlation coefficients. Given that the N170 is a negative-going component, larger component amplitudes correspond to more negative voltages. The absolute N170 amplitude, on the other hand, is always positive, meaning that larger component amplitudes correspond to more positive values.
Figure 2. Examples of broad spatial frequency (BSF; left), high spatial frequency (HSF; middle), and low spatial frequency (LSF; right) stimuli used in the study.
instructed to pay attention to every stimulus but respond only to pictures of an occasionally appearing chair (7 per block) by pressing a button, using the index finger of the left hand for half of the trials, and the index finger of the right hand for the other half (the order of left- and right-handed responses was counterbalanced between participants). Speed and accuracy were equally emphasized in the task instructions.
Results
Mean values for N170 peak amplitude for each facial expression, spatial frequency, and electrode are presented in Table 2.
Electroencephalogram Recording and Signal Processing
Broad Spatial Frequencies
Electroencephalogram (EEG) data were acquired with an
Advanced Neuro Technology (ANT) Refa-32 amplifier, from 32 sites, according to the extended 10-5 International system, at a digitizing rate of 512 Hz, a recording band-pass of [DC, 138] Hz, and referenced to the average of both mastoids. An electrode located midway between Fpz and Fz served as ground. Impedances were kept below 10 kΩ at all sites.
The continuous EEG records were band-pass filtered offline at
[0.3, 30] Hz. A principal component analysis (PCA)-based artifact correction algorithm (Ille, Berg, & Scherg, 2002) was employed to correct the signal for eye blinks. Data were segmented into epochs of 800 ms (from −200 prestimulus to 600 ms poststimulus onset), subjected to visual inspection and manual rejection of artifacts
(visual detection of movement or muscular artifacts; an average of
18.21 (SD = 1.83) trials were included per condition), baseline
There were main effects of site, F(1,50) = 12.719, p < .001, η2 = .203, emotion, F(4,200) = 9.819, p < .001, η2 = .164, and p p fearless dominance, F(1,50) = 5.706, p = .021, η2 = .102, and a p significant Emotion × Coldheartedness interaction, F(4,200) =
2.831, p = .033, η2 = .054. The amplitude of the N170 was higher p on the right hemisphere, and all emotional faces elicited higher
N170 amplitudes than neutral expressions (Table 2, Figure 3).
Fearless dominance was inversely related with absolute N170 amplitude, r(52) = −.291, p = .031, (Figure 4), such that higher FD traits were associated with smaller amplitudes.
Given the Emotion × Coldheartedness significant interaction, the relation between the amplitude of the N170 and coldheartedness score was analyzed for each expression separately. There were significant positive associations between coldheartedness and
N170 amplitude for fear, r(52) = .295, p = .031, and happiness,
Table 2. Mean N170 Peak Amplitudes for Expressions Presented at BSF, LSF, and HSF
Broad spatial frequencies
Note. Standard deviations are presented in parentheses. BSF = broad spatial frequencies; LSF = low spatial frequencies; HSF = high spatial frequencies.
N170 and facial emotion in psychopathy
6
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6
BSF (P7)
2
-2
400
350
300
250
200
150
-4
-6
-6
-8
-8
Latency (ms)
6
Latency (ms)
6
LSF (P7)
2
LSF (P8)
4
2
400
400
300
300
350
250
250
350
200
150
100
50
0
200
-2
0
-50
400
350
300
250
200
150
100
50
-50
0
0
Amplitude (μV)
-100
4
-2
-4
-4
-6
-6
-8
-8
Latency (ms)
6
Latency (ms)
6
HSF (P7)
4
2
2
-2
150
100
0
0
-50
400
350
300
250
200
150
100
50
-50
0
0
Amplitude (μV)
-100
4
HSF (P8)
50
Amplitude (μV)
-100
100
-2
-4
Amplitude (μV)
-100
50
0
0
-50
400
350
300
250
200
150
100
50
0
-50
0
Amplitude (μV)
-100
4
2
Amplitude (μV)
-100
4
BSF (P8)
-2
-4
-6
Anger
Disgust
Fear
Happy
Neutral
-4
-6
-8
Latency (ms)
-8
Latency (ms)
Figure 3. ERP grand averages elicited at P7 (left) and P8 (right) by the different facial expressions of emotion for the three spatial frequencies. Positive voltage is plotted up. Time in milliseconds is on the x axis, and voltage in microvolts is on the y axis. Different emotions are color-coded. BSF = broad spatial frequencies; LSF = low spatial frequencies; HSF = high spatial frequencies.
r(52) = .335, p = .013, such that higher coldheartedness traits were associated with larger amplitudes. The effect was marginally significant for anger, r(52) = .262, p = .056, and, although effects were not significant, the direction of the association was the same for disgust, r(52) = .205, p = .133, and neutral expressions, r(52) = .194, p = .156, (Figure 5).
Low and High Spatial Frequencies
For LSF, there were main effects of site, F(1,50) = 19.655, p < .001, η2 = .282, such that the amplitude of the N170 was higher p at the right hemisphere, and emotion, F(4,200) = 4.888, p < .001, η2 = .089, such that facial expressions of happiness and fear p elicited higher N170 amplitudes than neutral faces, and fearful faces elicited higher amplitudes than expressions of disgust
(Table 2, Figure 3). There were also main effects of both PPI
FD, F(1,50) = 4.206, p = .046, η2 = .078, and coldheartedness, p F(1,50) = 4.778, p = .034, η2 = .087. Correlational analysis p revealed a trend towards reduced absolute amplitudes for participants with higher PPI FD, r(52) = −.243, p = .077, (Figure 3) and significantly enhanced N170 amplitudes for participants higher in coldheartedness, r(52) = .282, p = .039, (Figure 4).
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6.00
Broad spatial frequencies
4.00
700
600
500
400
300
200
0
100
0.00
-100
Amplitude (μV)
2.00
-2.00
Higher Fearless Dominance
-4.00
Lower Fearless Dominance
-6.00
-8.00
Latency (ms)
6.00
Low spatial frequencies
4.00
700
600
500
400
300
200
0
100
0.00
-100
Amplitude (μV)
2.00
-2.00
Higher Fearless Dominance
-4.00
Lower Fearless Dominance
-6.00
-8.00
Latency (ms)
6.00
High spatial frequencies
4.00
700
600
500
400
300
200
0
100
0.00
-100
Amplitude (μV)
2.00
-2.00
Higher Fearless Dominance
-4.00
Lower Fearless Dominance
-6.00
-8.00
Latency (ms)
Figure 4. ERP grand averages of participants scoring higher (n = 27) and lower (n = 27) in fearless dominance after a median split (left), and scatter plots of N170 absolute peak amplitude by fearless dominance scores (right). Amplitudes are collapsed across electrodes and emotional categories. Positive voltage is plotted upwards. The different spatial frequency conditions are plotted separately: BSF = broad spatial frequencies (top); LSF = low spatial frequencies
(middle); HSF = high spatial frequencies (bottom).
For HSF pictures, there were main effects of site, F(1,50) =
11.900, p = .001, η2 = .192, with higher amplitudes at the right p hemisphere, emotion, F(4,200) = 4.676, p = .009, η2 = .086, such p that fearful expressions elicited significantly higher amplitudes
than expressions of disgust and neutral faces (Table 2, Figure 3), and coldheartedness, F(1,50) = 6.539, p = .014, η2 = .116, such p that participants scoring higher in coldheartedness presented enhanced N170 absolute amplitudes, r(52) = .310, p = .023
N170 and facial emotion in psychopathy
6.00
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Broad spatial frequencies
4.00
700
600
500
400
300
200
0
100
0.00
-100
Amplitude (μV)
2.00
-2.00
Higher Coldheartedness
-4.00
Lower Coldheartedness
-6.00
-8.00
Latency (ms)
6.00
Low spatial frequencies
4.00
700
600
500
400
300
200
0
100
0.00
-100
Amplitude (μV)
2.00
-2.00
Higher Coldheartedness
-4.00
Lower Coldheartedness
-6.00
-8.00
Latency (ms)
6.00
High spatial frequencies
4.00
700
600
500
400
300
200
0
100
0.00
-100
Amplitude (μV)
2.00
-2.00
Higher Coldheartedness
-4.00
Lower Coldheartedness
-6.00
-8.00
Latency (ms)
Figure 5. ERP grand averages of participants scoring higher (n = 27) and lower (n = 27) in coldheartedness after a median split (left), and scatter plots of
N170 absolute peak amplitude by coldheartedness scores (right). Amplitudes are collapsed across electrodes and emotional categories. Positive voltage is plotted upwards. The different spatial frequency conditions are plotted separately: BSF = broad spatial frequencies (top); LSF = low spatial frequencies
(middle); HSF = high spatial frequencies (bottom).
(Figure 4). A significant Site × Emotion interaction, F(4,200) =
2.569, p = .039, η2 = .049, was also observed. The interaction was p decomposed by analyzing the effect of emotion at each electrode.
There were significant effects of emotion at both P8,
F(4,200) = 5.140, p = .003, η2 = .093, and P7, F(4,200) = 2.997, p p = .037, η2 = .057. For P8, happy and fearful expressions elicited p higher N170 amplitudes than facial expressions of disgust, and fearful facial expressions elicited higher amplitudes than neutral
652
P.R. Almeida et al.
faces. All pairwise differences lose significance after correction for multiple comparisons at P7.
Discussion
The assumption that psychopathy is related to impairments in facial emotion processing is pervasive in research (Dawel, O’Kearney,
McKone, & Palermo, 2012; Marsh & Blair, 2008). However, the behavioral evidence concerning these deficits is not robust (e.g.,
Book et al., 2007; Del Gaizo & Falkenbach, 2008; Glass &
Newman, 2006). In the present study, we analyzed the relation between different dimensions of psychopathy and facial emotion processing in a community sample, by examining the amplitude of the N170 component of the event-related potential. Our findings suggest that different dimensions of psychopathy are related to distinct patterns of fusiform activation in response to facial expressions: Participants with higher PPI FD scores presented reduced
N170 amplitudes to facial expressions, whereas higher coldheartedness scores were related to enhanced N170 responses. Moreover, the reduction of N170 amplitude as a function of PPI FD was restricted to LSF stimuli, whereas the enhancement predicted by coldheartedness was present across all spatial frequencies. This suggests that the reduction of N170 amplitudes in participants with higher fearless dominance scores may result from decreased input from the tectopulvinar pathway, and may specifically be the product of reduced amygdaline input to the visual cortex. The dependence of the activity of the visual cortex on the amygdala’s modulatory feedback has been shown in fMRI studies with amygdala-lesioned monkeys (Hadj-Bouziane et al., 2012) and humans (Vuilleumier et al., 2004). On the other hand, the enhancement of N170 in participants higher in coldheartedness may index increased responses of the primary and secondary visual cortices driven by input from the geniculostriate pathway and resulting from the compensatory engagement of other neural regions implicated in cognitive control or detailed visual analysis. These results may be interpreted in light of the hypothesis of amygdala dysfunction (Blair, 2005; Patrick, 1994) and point to the existence of cortical compensatory mechanisms for processing facial emotion in psychopathy. We address each of these interpretations below.
There is mounting evidence supporting the existence of amygdala abnormalities in psychopathy (Kiehl, 2006; Patrick, 1994).
This evidence comes from structural (Tiihonen, Hodgins, &
Vaurio, 2000; Yang, Raine, Colletti, Toga, & Narr, 2010) and functional neuroimaging studies (Birbaumer et al., 2005; Gordon et al.,
2004; Kiehl et al., 2001; Veit et al., 2002), in addition to results concerning impaired aversive conditioning (Lykken, 1957) and impaired emotional modulation of the startle reflex (Levenson,
Patrick, Bradley, & Lang, 2000; Patrick, 1994; Patrick, Bradley, &
Lang, 1993; Vanman, Mejia, Dawson, Schell, & Raine, 2003) in psychopathic populations. Importantly, amygdala abnormalities in psychopathy have been selectively related to dispositional fearlessness (Patrick, 1994), which is considered to underlie both the characteristics assessed by PPI FD and coldheartedness (Patrick,
2010; Patrick et al., 2009). In spite of sharing a common etiological substrate, fearless dominance and coldheartedness are related to distinct patterns of interpersonal functioning (Lilienfeld &
Widows, 2005; Patrick, 2010; Patrick et al., 2009) and are conceptualized as the result of distinct environmental influences shaping the fearlessness etiological process (Patrick, 2010; Patrick et al.,
2009). Fearless dominance has been described as indexing a general absence of trait and anticipatory anxiety and proficient functioning in social situations (Benning et al., 2003, 2005), and it
has been shown to correlate negatively with internalizing personality disorder symptoms such as anxiety, depression, fear, and suicide behavior (Blonigen et al., 2010; Douglas et al., 2008;
Miller & Lynam, 2012; Patrick, Edens, Poythress, Lilienfeld, &
Benning, 2006). In their influential meta-analysis concerning the nomological network of the PPI, Miller and Lynam (2012) conclude that fearless dominance is strongly related to a reduced experience of negative emotional states, such as neuroticism, negative emotionality, internalizing symptomatology, or behavioral disinhibition. This suggests that fearless dominance may share an etiological substrate common to anxiety disorders, and, hence, the functional results observed for this trait should be inversely related to those observed in anxiety. In fact, it has recently been shown that induced social anxiety enhances N170 amplitudes in participants with high dispositional social anxiety (Ofan, Rubin, & Amodio,
2013), and positive relations between anxiety and amygdala reactivity have been shown both for emotional (Ewbank et al., 2009) and neutral expressions (Somerville, Kim, Johnstone, Alexander,
& Whalen, 2004). The diminished N170 response, led by low spatial frequency stimuli, suggests that low trait anxiety displayed by participants with high PPI FD may be related to generally reduced amygdaline input to the extrastriate cortex in response to social stimuli. This effect may constitute a psychophysiological correlate of low anxiety, typically displayed by participants high in fearless dominance. In fact, subsequent analysis in our sample confirmed that N170 amplitude is inversely related to the scores in the stress immunity facet of the PPI FD dimension.
Coldheartedness, on the other hand, has been associated with the “meanness” facet of psychopathy (Miller & Lynam,
2012; Patrick et al., 2009). This dimension entails callousness, nonresponsiveness to other people’s distress, deficient empathy, disdain and lack of close attachments, exploitativeness, and empowerment through cruelty (Patrick, 2010). The positive association between coldheartedness and the amplitude of the N170, and the fact that it seems to be mediated by the geniculostriate pathway, suggests that individuals scoring higher in this trait may devote increased cortical resources to the analysis of structural features of facial stimuli. Thus, coldheartedness seems to be related to an increased cortical effort in processing facial emotion, possibly under the influence of areas dedicated to effortful control or detailed visual analysis (regions traditionally not associated with emotion processing). This is consistent with previous suggestions that individuals higher in psychopathic traits may devote alternative brain areas, such as the extrastriate visual cortex or the dorsolateral prefrontal cortex (associated, respectively, with feature-based analysis and abstract reasoning) for processing information with emotional (Birbaumer et al., 2005; Gordon et al.,
2004; Intrator et al., 1997; Kiehl et al., 2001) and socioaffective content (Glenn, Raine, & Schug, 2009; Glenn, Raine, Schug, et al.,
2009; Marsh & Cardinale, 2012; Rilling et al., 2007). Our data suggest that individuals high in the coldheartedness component of psychopathy are able to process facial emotion by devoting enhanced cortical resources to the fine-tuned analysis of the stimuli. As stated above, this sort of processing strategy has been shown to increase the activation of the fusiform gyri, independently of amygdala activation, in individuals with autism (Perlman et al.,
2011). The fact that the identification of facial affect in the presence of amygdala impairment is enabled by the compensatory engagement of cortical resources may also contribute to the resolution of the paradoxical observation that, despite evidence of amygdala dysfunction, participants higher in psychopathic traits are able to identify facial emotion (including fear and sadness) when the
N170 and facial emotion in psychopathy experimental task relies on full intensity (as opposed to degraded) stimuli (Book et al., 2007; Campanella et al., 2005; Del Gaizo &
Falkenbach, 2008; Glass & Newman, 2006; Gordon et al., 2004;
Pham & Philippot, 2010). Within these experimental conditions, participants higher in psychopathy are able to engage in featurebased analysis of the stimuli and identify the emotions displayed.
In fact, Contreras-Rodriguez et al. (2013) have recently presented supportive evidence for this model by reporting hyperactivation of visual and prefrontal cortices and reduced connectivity between the amygdala and visual and prefrontal areas during facial emotion processing in individuals higher in the affective-interpersonal component of psychopathy.
It should also be noted that our effects were not specific to fear, but extended to other emotional categories. Neurocognitive models of psychopathy, such as the integrated emotion system (IES; Blair,
2005), suggest that individuals high in psychopathy are specifically impaired in the processing of environmental stimuli associated with the distress of others (fear and sadness), and associate these impairments with abnormal amygdala functioning (for a recent review, see Blair, 2013). However, meta-analytic evidence points towards an involvement of the amygdala in the processing of facial expressions of emotion, independently of their valence, and not specifically in the processing of fear and sadness (Sergerie,
Chochol, & Armony, 2008). Hence, the fact that we have seen effects for the entire range of facial expressions does not preclude the interpretation of our data within the amygdala dysfunction hypothesis, but it poses problems to one of the central assumptions of the IES, which considers the impairment in recognizing distress cues in others as the main etiological mechanism for the emergence of psychopathic traits in adulthood (Blair, 2013).
Finally, we did not detect any relation between the PPI ScI factor and the neural correlates of facial emotion processing. As stated above, contrary to fearless dominance, self-centered impulsivity is strongly related to externalizing behavior (Blonigen et al., 2010; Miller & Lynam, 2012). At the etiological level, ScI seems to share a common substrate with disorders involving vulnerability towards disinhibitory psychopathology (Blonigen et al.,
2005, 2010; Krueger et al., 2002; Patrick et al., 2009; Skeem et al., 2011) and executive dysfunction (Ross, Benning, &
Adams, 2007). Importantly, these externalizing traits rely on pathophysiological processes, such as impairments in prefrontal and anterior cingulate structures subserving inhibitory control
(Gorenstein & Newman, 1980; Morgan & Lilienfeld, 2000;
Nelson, Patrick, & Bernat, 2011), distinct from those underlying the fearlessness-related components of psychopathy (Blair, 2005,
2013; Blonigen et al., 2005; Patrick, 2010; Ross et al., 2007). For instance, ERP studies on the P3 show that, whereas the PPI ScI is related to decreased amplitudes (Carlson, Thái, & Mclarnon,
2009; Nelson et al., 2011), which have been taken as indexing poor prefrontal functioning, this is not the case for fearless dominance, which is associated with increased P3 amplitudes (Carlson
& Thái, 2010). Our data thus support the dual conception of psychopathy (Fowles & Dindo, 2006) by illustrating distinct neurocognitive correlates for the fearlessness-related (i.e., FD and coldheartedness) and disinhibition-related (ScI) components of psychopathy. The question may emerge whether our results related to the fearless dominance dimension are actually relevant to the understanding of psychopathy. In fact, it has been questioned whether fearless dominance should be considered a relevant dimension in the construct of psychopathy, since this dimension appears to relate exclusively to positive adjustment characteristics (Miller & Lynam,
653
2012). However, the conceptual view of psychopathy as a probabilistic confluence of traits of distinct etiological origin and under different developmental pathways (Patrick et al., 2009) paves the way for the study of the correlates, etiology, and development of each trait. While considering that high FD traits are not sufficient for the emergence of psychopathic personality, excluding this component from the spectra of psychopathic characteristics would render psychopathy largely equivalent to antisocial personality disorder (Lilienfeld et al., 2012). Moreover, the affective and interpersonal features associated with FD and coldheartedness, such as low anxiety, low empathy, or callousness, constitute the distinctive characteristics of the primary psychopathic personality (Hicks,
Markon, Patrick, Krueger, & Newman, 2004; Poythress et al.,
2010). In fact, high ratings in psychopathic traits are usually associated with decreased risk for anxiety and mood disorders, especially when the relation between anxiety and antisocial behavior is accounted for (Hicks & Patrick, 2006), and cluster analytic studies show the PPI FD to be a marker of primary psychopathy (Hicks et al., 2004; Poythress et al., 2010). Fearless dominance, as well as coldheartedness, are considered distinct expressions of a mutual etiological process, trait fearlessness, which has been related to amygdala dysfunction (Patrick, 1994; Patrick et al., 2009). Accordingly, altered amygdala responses to facial stimuli (specifically fear and sadness) play an important role in predominant neurocognitive models concerning the emergence of both the callous-unemotional component and aberrant patterns of moral cognition and decision making observed in individuals high in psychopathy (Blair, 2005,
2013; Blair, White, Meffert, & Hwang, 2013; Marsh & Blair,
2008). Hence, although psychopathy as a syndrome may be distinguished by the confluence of traits of different etiological origins
(Fowles & Dindo, 2006; Patrick et al., 2009), the study of the traits by themselves is not of minor importance. In fact, understanding the physiological mechanisms underlying the manifestation of each phenotypic component constitutes a contribution towards tracing its pathophysiology and explaining its contribution for the emergence of the full-blown psychopathic spectra. This debate would benefit from the analysis of the functional brain correlates of the distinct dimensions underlying the psychopathic spectrum, as well as from the integration of these observations in neurocognitive models of psychopathy. Here, we show that the dimensions of psychopathy whose underlying etiology has been related to amygdala dysfunction do have a relation with the brain correlates of facial emotion processing. Our findings support the existence of cortical mechanisms that may compensate for the reduced amygdala response to socioaffective information in individuals with high fearlessness-related psychopathic traits.
One limitation of the present study is the low range of psychopathy values in the sample. The replication of these results in a carefully selected sample of criminal and noncriminal individuals with extreme levels of psychopathy would maximize their generalizability. Nevertheless, the nature of psychopathy as a confluence of traits distributed continuously in the population, rather than a taxonomic entity, has received increasing support (Marcus,
John, & Edens, 2004; Skeem et al., 2011), enabling its study not only in forensic, but also in community samples (Lilienfeld, 1998).
Supporting this view, it has been shown that psychopathic traits predict antisocial behavior and instrumental violence in both community and institutionalized individuals (Neumann & Hare, 2008;
Seals, Sharp, Ha, & Michonski, 2012; Woodworth & Porter, 2002).
Also, similar emotional and moral response patterns have been described in community and institutionalized samples at the behavioral (Bartels & Pizarro, 2011; Koenigs, Kruepke, Zeier,
654
P.R. Almeida et al.
& Newman, 2012), physiological (Lopez, Poy, Patrick, &
Molto, 2013; Rothemund et al., 2012), and neural levels
(Contreras-Rodriguez et al., 2013; Gordon et al., 2004), further reinforcing the idea that meaningful psychopathy-related effects may be investigated using participants from the community.
Accordingly, the study of psychopathic traits in nonforensic samples has been advocated as a means of characterizing the trait in its purest state, avoiding confounding factors of reclusion such as comorbidity, low IQ, or substance abuse (Barker et al., 2007;
Butler, Indig, Allnutt, & Mamoon, 2011).
Another potential limitation concerns the referencing scheme used in the EEG analysis. In fact, it has been discussed that, given the proximity to the N170 generators, the mastoids are not ideally located as reference sites for the analysis of the N170
(Rellecke, Sommer, & Schacht, 2013). In fact, the modulation of
N170 amplitude by facial expressions is smaller (but detectable)
under a mean mastoids reference than an average reference
(Rellecke et al. 2013). Our choice of reference in the present study was driven by the consideration that the number of channels (32) and scalp coverage (limited to the upper scalp) used are not ideal for the computation of an average reference (Dien,
1998). However, to test for possible effects of reference choice on our results, we have reanalyzed the data after rereferencing to the average of all electrodes and found that the pattern of results is the same.
In summary, our results suggest that different psychopathic traits are related to distinct patterns of brain activation during the processing of facial expressions. These patterns may reflect reduced amygdala input to the visual cortex as a function of fearless dominance and the compensatory engagement of cortical areas not traditionally associated with emotional processing as a function of coldheartedness.
References
Adolphs, R., Gosselin, F., Buchanan, T. W., Tranel, D., Schyns, P., &
Damásio, A. R. (2005). A mechanism for impaired fear recognition after amygdala damage. Nature, 433, 68–72. doi: 10.1038/nature03086
Bachmann, T. (1991). Identification of spatially quantised tachistoscopic images of faces: How many pixels does it take to carry identity? European Journal of Cognitive Psychology, 3, 87–103. doi: 10.1080/
09541449108406221
Barcelo, P., Suwazono, S., & Knight, R. T. (2000). Prefrontal modulation of visual processing in humans. Nature Neuroscience, 3, 399–403. doi:
10.1038/73975
Barker, E. D., Seguin, J. R., White, H. R., Bates, M. E., Lacourse, E.,
Carbonneau, R., Tremblay, R. E. (2007). Developmental trajectories of male physical violence and theft: Relations to neurocognitive performance. Archives of General Psychiatry, 64, 592–599. doi: 10.1001/ archpsyc.64.5.592 Bartels, D. M., & Pizarro, D. A. (2011). The mismeasure of morals: Antisocial personality traits predict utilitarian responses to moral dilemmas.
Cognition, 121, 154–161. doi: 10.1016/j.cognition.2011.05.010
Batty, M., & Taylor, M. J. (2003). Early processing of the six basic facial emotional expressions. Cognitive Brain Research, 17, 613–620. doi:
10.1016/S0926-6410(03)00174-5
Benning, S. D., Patrick, C. J., Blonigen, D. M., Hicks, B. M., & Iacono, W.
G. (2005). Estimating facets of psychopathy from normal personality traits: A step toward community epidemiological investigations. Assessment, 12, 3–18. doi: 10.1177/1073191104271223
Benning, S. D., Patrick, C. J., Hicks, B. M., Blonigen, D. M., & Krueger, R.
F. (2003). Factor structure of the Psychopathic Personality Inventory:
Validity and implications for clinical assessment. Psychological Assessment, 15, 340–350. doi: 10.1037/1040-3590.15.3.340
Bentin, S., Allison, T., Puce, A., Perez, E., & McCarthy, G.
(1996). Electrophysiological studies of face perception in humans.
Journal of Cognitive Neuroscience, 8, 551–565. doi: 10.1162/ jocn.1996.8.6.551 Birbaumer, N., Veit, R., Lotze, M., Erb, M., Hermann, C., Grodd, W., &
Flor, H. (2005). Deficient fear conditioning in psychopathy: A functional magnetic resonance imaging study. Archives of General Psychiatry, 62, 799–805. doi: 10.1001/archpsyc.62.7.799
Blair, R. J. R. (2005). Applying a cognitive neuroscience perspective to the disorder of psychopathy. Development and Psychopathology, 17, 865–
891. doi: 10.1017/S0954579405050418
Blair, R. J. R. (2013). The neurobiology of psychopathic traits in youths.
Nature Reviews Neuroscience, 14, 786–799. doi: 10.1038/nrn3577
Blair, R. J. R., & Cipolotti, L. (2000). Impaired social response reversal: A case of “acquired sociopathy.” Brain, 123, 1122–1141. doi: 10.1093/ brain/123.6.1122 Blair, R. J. R., Mitchell, D. G. V., Peschardt, K. S., Colledge, E., Leonard,
R. A., Shine, J. H., . . . Perrett, D. I. (2004). Reduced sensitivity to others’ fearful expressions in psychopathic individuals. Personality and
Individual Differences, 37, 1111–1122. doi: 10.1016/j.paid.2003.10.008
Blair, R. J. R., White, S. F., Meffert, H., & Hwang, S. (2013). Emotional learning and the development of differential moralities: Implications
from research on psychopathy. Annals of the New York Academy of
Sciences, 1299, 36–41. doi: 10.1111/nyas.12169
Blau, V. C., Maurer, U., Tottenham, N., & McCandliss, B. D. (2007).
The face-specific N170 component is modulated by emotional facial expression. Behavioral and Brain Functions, 3, 7. doi: 10.1186/17449081-3-7
Blonigen, D. M., Hicks, B. M., Krueger, R. F., Patrick, C. J., & Iacono, W.
G. (2005). Psychopathic personality traits: Heritability and genetic overlap with internalizing and externalizing psychopathology. Psychological Medicine, 35, 637–648. doi: 10.1017/S0033291704004180
Blonigen, D. M., Patrick, C. J., Douglas, K. S., Poythress, N., Skeem, J. L.,
Lilienfeld, S. O., . . . Krueger, R. F. (2010). Multi-method assessment of psychopathy in relation to factors of internalizing and externalizing from the personality assessment inventory: The impact of method variance and suppressor effects. Psychological Assessment, 22, 96–107. doi: 10.1037/a0017240
Book, A. S., Quinsey, V. L., & Langford, D. (2007). Psychopathy and the perception of affect and vulnerability. Criminal Justice and Behavior,
34, 531–544. doi: 10.1177/0093854806293554
Butler, T., Indig, D., Allnutt, S., & Mamoon, H. (2011). Co-occurring mental illness and substance use disorder among Australian prisoners.
Drug and Alcohol Review, 30, 188–194. doi: 10.1111/j.14653362.2010.00216.x
Caharel, S., Courtay, N., Bernard, C., Lalonde, R., & Rebaï, M. (2005).
Familiarity and emotional expression influence an early stage of face processing: An electrophysiological study. Brain and Cognition, 59,
96–100. doi: 10.1016/j.bandc.2005.05.005
Campanella, S., Vanhoolandt, M. E., & Philippot, P. (2005). Emotional deficit in subjects with psychopathic tendencies as assessed by the
Minnesota Multiphasic Personality Inventory-2: An event-related potentials study. Neuroscience Letters, 373, 26–31. doi: 10.1016/
j.neulet.2004.09.061
Carlson, S. R., & Thái, S. (2010). ERPs on a continuous performance task and self-reported psychopathic traits: P3 and CNV augmentation are associated with fearless dominance. Biological Psychology, 85, 318–
330. doi: 10.1016/j.biopsycho.2010.08.002
Carlson, S. R., Thái, S., & Mclarnon, M. E. (2009). Visual P3 amplitude and self-reported psychopathic traits: Frontal reduction is associated with self-centered impulsivity. Psychophysiology, 46, 100–113. doi:
10.1111/j.1469-8986.2008.00756.x
Contreras-Rodriguez, O., Pujol, J., Batalla, I., Harrison, B. J., Bosque, J.,
Ibern-Regas, I., . . . Cardoner, N. (2013). Disrupted neural processing of emotional faces in psychopathy. Social Cognitive and Affective Neuroscience. doi: 10.1093/scan/nst014
Cooke, D. J., & Michie, C. (2001). Refining the construct of psychopathy:
Towards a hierarchical model. Psychological Assessment, 13, 171–188. doi: 10.1037/1040-3590.13.2.171
Corbetta, M., Shulman, G. L., Miezin, F. M., & Petersen, S. E. (1995).
Superior parietal cortex activation during spatial attention shifts and visual feature conjunction. Science, 270, 802–805. doi: 10.1126/ science.270.5237.802 N170 and facial emotion in psychopathy
Costen, N. P., Parker, D. M., & Craw, I. (1996). Effects of high-pass and low-pass spatial filtering on face identification. Perception &
Psychophysics, 58, 602–612. doi: 10.3758/BF03213093
Dadds, M. R., Perry, Y., Hawes, D. J., Merz, S., Riddell, A. C., Haines,
D. J., . . . Abeygunawardane, A. I. (2006). Attention to the eyes and fear-recognition deficits in child psychopathy. British Journal of Psychiatry, 189, 280–281. doi: 10.1192/bjp.bp.105.018150
Dawel, A., O’Kearney, R., McKone, E., & Palermo, R. (2012). Not just fear and sadness: Meta-analytic evidence of pervasive emotion recognition deficits for facial and vocal expressions in psychopathy. Neuroscience and Biobehavioral Reviews, 36, 2288–2304. doi: 10.1016/
j.neubiorev.2012.08.006
Deffke, I., Sander, T., Heidenreich, J., Sommer, W., Curio, G., Trahms, L.,
& Lueschow, A. (2007). MEG/EEG sources of the 170-ms response to faces are co-localized in the fusiform gyrus. NeuroImage, 35, 1495–
1501. doi: 10.1016/j.neuroimage.2007.01.034
Del Gaizo, A. L., & Falkenbach, D. M. (2008). Primary and secondary psychopathic-traits and their relationship to perception and experience of emotion. Personality and Individual Differences, 45, 206–212. doi:
10.1016/j.paid.2008.03.019
Dien, J. (1998). Issues in the application of the average reference: Review, critiques, and recommendations. Behavior Research Methods, Instruments, & Computers, 30, 34–43. doi: 10.3758/BF03209414
Douglas, K. S., Lilienfeld, S. O., Skeem, J. L., Poythress, N. G., Edens, J.
F., & Patrick, C. J. (2008). Relation of antisocial and psychopathic traits to suicide-related behavior among offenders. Law and Human Behavior, 32, 511–525. doi: 10.1007/s10979-007-9122-8
Eimer, M., & Holmes, A. (2002). An ERP study on the time course of emotional face processing. NeuroReport, 13, 427–431. doi: 10.1097/
00001756-200203250-00013
Eimer, M., Holmes, A., & McGlone, F. P. (2003). The role of spatial attention in the processing of facial expression: An ERP study of rapid brain responses to six basic emotions. Cognitive, Affective, &
Behavioral Neuroscience, 3, 97–110. Retrieved from http://www
.ncbi.nlm.nih.gov/pubmed/12943325
Ewbank, M. P., Lawrence, A. D., Passamonti, L., Keane, J., Peers, P. V, &
Calder, A. J. (2009). Anxiety predicts a differential neural response to attended and unattended facial signals of anger and fear. NeuroImage,
44, 1144–1151. doi: 10.1016/j.neuroimage.2008.09.056
Fowles, D. C., & Dindo, L. (2006). A dual deficit model of psychopathy. In
C. J. Patrick (Ed.), Handbook of psychopathy (pp. 14–34). New York,
NY: Guilford.
Glass, S. J., & Newman, J. P. (2006). Recognition of facial affect in psychopathic offenders. Journal of Abnormal Psychology, 115, 815–
820. doi: 10.1037/0021-843X.115.4.815
Glenn, A. L., Raine, A., & Schug, R. A. (2009). The neural correlates of moral decision-making in psychopathy. Molecular Psychiatry, 14, 5–6. doi: 10.1038/mp.2008.104
Glenn, A. L., Raine, A., Schug, R. A., Young, L., & Hauser, M. D.
(2009). Increased DLPFC activity during moral decision-making in psychopathy. Molecular Psychiatry, 14, 909–911. doi: 10.1038/ mp.2009.76 Gordon, H. L., Baird, A. A., & End, A. (2004). Functional differences among those high and low on a trait measure of psychopathy. Biological
Psychiatry, 56, 516–521. doi: 10.1016/j.biopsych.2004.06.030
Gorenstein, E. E., & Newman, J. P. (1980). Disinhibitory psychopathology:
A new perspective and a model for research. Psychological Review, 87,
301–315. doi: 10.1037//0033-295X.87.3.301
Graham, R., Devinsky, O., & LaBar, K. S. (2006). Sequential ordering of morphed faces and facial expressions following temporal lobe damage.
Neuropsychologia, 44, 1398–1405. doi: 10.1016/j.neuropsychologia.
2005.12.010
Hadj-Bouziane, F., Liu, N., Bell., A. H., Gothard, K. M., Luh, W., Tootel.,
R. B, H, . . . Ungerleider, L. G. (2012). Amygdala lesions disrupt modulation of functional MRI activity evoked by facial expression in the monkey inferior temporal cortex. PNAS, 109, E3640–E3648. doi:
10.1073/pnas.1218406109
Hare, R. D. (2007). Psychological instruments in the assessment of psychopathy. In A. R. Felthous & H. Saß (Eds.), International handbook on psychopathic disorders and the law (pp. 41–67). New York,
NY: Wiley.
Hastings, M. E., Tangney, J. P., & Stuewig, J. (2008). Psychopathy and identification of facial expressions of emotion. Personality and Individual Differences, 44, 1474–1483. doi: 10.1016/j.paid.2008.01.004
655
Hicks, B. M., Markon, K. E., Patrick, C. J., Krueger, R. F., & Newman, J.
P. (2004). Identifying psychopathy subtypes based on personality structure. Psychological Assessment, 16, 276–288. doi: 10.1037/10403590.16.3.276
Hicks, B. M., & Patrick, C. J. (2006). Psychopathy and negative emotionality: Analyses of suppressor effects reveal distinct relations with emotional distress, fearfulness, and anger-hostility. Journal of Abnormal
Psychology, 115, 276–287. doi: 10.1037/0021-843X.115.2.276
Holmes, A., Green, S., & Vuilleumier, P. (2005). The involvement of distinct visual channels in rapid attention towards fearful facial expressions. Cognition & Emotion, 19, 899–922. doi: 10.1080/
02699930441000454
Holmes, A., Vuilleumier, P., & Eimer, M. (2003). The processing of emotional facial expression is gated by spatial attention: Evidence from event-related brain potentials. Cognitive Brain Research, 16, 174–184. doi: 10.1016/S0926-6410(02)00268-9
Ille, N., Berg, P., & Scherg, M. (2002). Artifact correction of the ongoing
EEG using spatial filters based on artifact and brain signal topographies.
Journal of Clinical Neurophysiology, 19, 113–124. doi: 10.1097/
00004691-200203000-00002
Intrator, J., Hare, R. D., Stritzke, P., Brichtswein, K., Dorfman, D., Harpur,
T., . . . Machach, J. (1997). A brain imaging (single photon emission computerized tomography) study of semantic and affective processing in psychopaths. Biological Psychiatry, 42, 96–103. doi: 10.1016/S00063223(96)00290-9
Iria, C., & Barbosa, F. (2009). Perception of facial expressions of fear:
Comparative research with criminal and non-criminal psychopaths.
Journal of Forensic Psychiatry & Psychology, 20, 66–73. doi: 10.1080/
14789940802214218
Itier, R. J., & Taylor, M. J. (2004). Effects of repetition learning on upright, inverted and contrast-reversed face processing using ERPs.
NeuroImage, 21, 1518–1532. doi: 10.1016/j.neuroimage.2003.
12.016
Jones, A. P., Laurens, K. R., Herba, C. M., Barker, G. J., & Viding, E.
(2009). Amygdala hypoactivity to fearful faces in boys with conduct problems and callous-unemotional traits. American Journal of Psychiatry, 166, 95–102. doi: 10.1176/appi.ajp.2008.07071050
Kahn, R. E., Byrd, A. L., & Pardini, D. A. (2013). Callous-unemotional traits robustly predict future criminal offending in young men. Law and
Human Behavior, 37, 87–97. doi: 10.1037/b0000003
Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The fusiform face area: A module in human extrastriate cortex specialized for face perception. Journal of Neuroscience, 17, 4302–4311.
Kiehl, K. A. (2006). A cognitive neuroscience perspective on psychopathy:
Evidence for paralimbic system dysfunction. Psychiatry Research, 142,
107–128. doi: 10.1016/j.psychres.2005.09.013
Kiehl, K. A., Smith, A. M., Hare, R. D., Mendrek, A., Forster, B. B., Brink,
J., & Liddle, P. F. (2001). Limbic abnormalities in affective processing by criminal psychopaths as revealed by functional magnetic resonance imaging. Biological Psychiatry, 50, 677–684. doi: 10.1016/S00063223(01)01222-7
Koenigs, M., Kruepke, M., Zeier, J., & Newman, J. P. (2012). Utilitarian moral judgment in psychopathy. Social, Cognitive, and Affective Neuroscience, 7, 708–714. doi: 10.1093/scan/nsr048
Krueger, R. F., Hicks, B. M., Patrick, C. J., Carlson, S. R., McGue, M., &
Iacono, W. G. (2002). Etiological relationships among substance dependence, antisocial behavior, and personality: Modeling the externalizing spectrum. Journal of Abnormal Psychology, 111, 411–424. doi:
10.1037//0021-84X.111.3.411
Krueger, R. F., Markon, K. E., Patrick, C. J., & Iacono, W. G. (2005).
Externalizing psychopathology in adulthood: A dimensional-spectrum conceptualization and its implications for DSM-V. Journal of Abnormal
Psychology, 114, 537–550. doi: 10.1037/0021-843X.114.4.537
Leppänen, J. M., Moulson, M. C., Vogel-Farley, V. K., & Nelson, C. A.
(2007). An ERP study of emotional face processing in the adult and infant brain. Child Development, 78, 232–245. doi: 10.1111/j.14678624.2007.00994.x
Levenson, G. K., Patrick, C. J., Bradley, M. M., & Lang, P. J. (2000). The psychopath as observer: Emotion and attention in picture processing.
Journal of Abnormal Psychology, 109, 373–385. doi: 10.1037/0021843X.109.3.373
Lilienfeld, S. O. (1998). Methodological advances and developments in the assessment of psychopathy. Behavior Research and Therapy, 36,
99–125. doi: 10.1016/S0005-7967(97)10021-3
656
Lilienfeld, S. O., Patrick, C. J., Benning, S. D., Berg, J., Sellbom, M., &
Edens, J. F. (2012). The role of fearless dominance in psychopathy:
Confusions, controversies, and clarifications. Personality Disorders, 3,
327–340. doi: 10.1037/a0026987
Lilienfeld, S. O., & Widows, M. R. (2005). Psychopathic Personality
Inventory–revised: Professional manual. Lutz, FL: Psychological
Assessment Resources.
Lopez, R., Poy, R., Patrick, C. J., & Molto, J. (2013). Deficient fear conditioning and self-reported psychopathy: The role of fearless dominance. Psychophysiology, 50, 210–218. doi: 10.1111/j.14698986.2012.01493.x
Lykken, D. T. (1957). A study of anxiety in the sociopathic personality. The
Journal of Abnormal and Social Psychology, 55, 6–10. doi: 10.1037/ h0047232 Marcus, D. K., John, S. L., & Edens, J. F. (2004). A taxometric analysis of psychopathic personality. Journal of Abnormal Psychology, 113, 626–
635. doi: 10.1037/0021-843X.113.4.626
Marsh, A. A., & Blair, R. J. (2008). Deficits in facial affect recognition among antisocial populations: A meta-analysis. Neuroscience and
Biobehavioral Reviews, 32, 454–465. doi: 10.1016/j.neubiorev.
2007.08.003
Marsh, A. A., & Cardinale, E. M. (2012). Psychopathy and fear: Specific impairments in judging behaviors that frighten others. Emotion, 12,
892–898. doi: 10.1037/a0026260
Merigan, W. H., & Maunsell, J. H. (1993). How parallel are the primate visual pathways? Annual Review of Neuroscience, 16, 369–402. doi:
10.1146/annurev.ne.16.030193.002101
Miller, J. D., Lynam, D. R., Widiger, T. A., & Leukefeld, C. (2001).
Personality disorders as extreme variants of common personality dimensions: Can the five factor model adequately represent psychopathy? Journal of Personality, 69, 253–276. doi: 10.1111/14676494.00144
Miller, J. D., & Lynam, D. R. (2012). An examination of the Psychopathic
Personality Inventory’s nomological network: A meta-analytic review.
Personality Disorders, 3, 305–326. doi: 10.1037/a0024567
Mitchell, D. G. V., Avny, S. B., & Blair, R. J. R. (2006). Divergent patterns of aggressive and neurocognitive characteristics in acquired versus developmental psychopathy. Neurocase, 12, 164–178. doi: 10.1080/
13554790600611288
Montagne, B., Van Honk, J., Kessels, R. P. C., Frigerio, E., Burt, M.,
Van Zandvoort, M. J. E., . . . de Hann, E. H. (2005). Reduced efficiency in recognising fear in subjects scoring high on psychopathic personality characteristics. Personality and Individual Differences, 38, 5–11. doi:
10.1016/j.paid.2004.02.008
Morgan, A. B., & Lilienfeld, S. O. (2000). A meta-analytic review of the relation between antisocial behavior and neuropsychological measures of executive function. Clinical Psychology Review, 20, 113–136. doi:
10.1016/S0272-7358(98)00096-8
Munro, G. E. S., Dywan, J., Harris, G. T., McKee, S., Unsal, A., &
Segalowitz, S. J. (2007). ERN varies with degree of psychopathy in an emotion discrimination task. Biological Psychology, 76, 31–42. doi:
10.1016/j.biopsycho.2007.05.004
Nelson, L. D., Patrick, C. J., & Bernat, E. M. (2011). Operationalizing proneness to externalizing psychopathology as a multivariate psychophysiological phenotype. Psychophysiology, 48, 64–72. doi:
10.1111/j.1469-8986.2010.01047.x
Neumann, C. S., & Hare, R. D. (2008). Psychopathic traits in a large community sample: links to violence, alcohol use, and intelligence.
Journal of Consulting and Clinical Psychology, 76, 893–899. doi:
10.1037/0022-006X.76.5.893
Norman, J., & Ehrlich, S. (1987). Spatial frequency filtering and target identification. Vision Research, 27, 87–96. doi: 10.1016/00426989(87)90145-3
Ofan, R. H., Rubin, N., & Amodio, D. M. (2013). Situation-based social anxiety enhances the neural processing of faces: Evidence from an intergroup context. Social Cognitive & Affective Neuroscience. Advance online publication. doi: 10.1093/scan/nst087
Patrick, C. J. (1994). Emotion and psychopathy: Startling new insights.
Psychophysiology, 31, 319–330. doi: 10.1111/j.1469-8986.1994. tb02440.x Patrick, C. J. (2010). Operationalizing the triarchic conceptualization of psychopathy: Preliminary description of brief scales for assessment of boldness, meanness, and disinhibition. Tallahassee, FL: Florida State
University.
P.R. Almeida et al.
Patrick, C. J., Bradley, M. M., & Lang, P. J. (1993). Emotion in the criminal psychopath: Startle reflex modulation. Journal of Abnormal Psychology, 102, 82–92. doi: 10.1037/0021-843X.102.1.82
Patrick, C. J., Edens, J. F., Poythress, N. G., Lilienfeld, S. O., & Benning,
S. D. (2006). Construct validity of the psychopathic personality inventory two-factor model with offenders. Psychological Assessement, 18,
204–208. doi: 10.1037/10403590.18.2.204
Patrick, C. J., Fowles, D. C., & Krueger, R. F. (2009). Triarchic conceptualization of psychopathy: Developmental origins of disinhibition, boldness, and meanness. Development and Psychopathology, 21, 913–938. doi: 10.1017/S0954579409000492
Perlman, S. B., Hudac, C. M., Pegors, T., Minshew, N. J., & Pelphrey, K. A.
(2011). Experimental manipulation of face-evoked activity in the fusiform gyrus of individuals with autism. Social Neuroscience, 6,
22–30. doi: 10.1080/17470911003683185
Pessoa, L., & Adolphs, R. (2010). Emotion processing and the amygdala:
From a “low road” to “many roads” of evaluating biological significance. Nature Reviews Neuroscience, 11, 773–783. doi: 10.1038/ nrn2920 Pham, T. H., & Philippot, P. (2010). Decoding of facial expression of emotion in criminal psychopaths. Journal of Personality Disorders, 24,
445–459. doi: 10.1521/pedi.2010.24.4.445
Pourtois, G., Dan, E. S., Grandjean, D., Sander, D., & Vuilleumier, P.
(2005). Enhanced extrastriate visual response to bandpass spatial frequency filtered fearful faces: Time course and topographic evokedpotentials mapping. Human Brain Mapping, 26, 65–79. doi: 10.1002/ hbm.20130 Poythress, N. G., Lilienfeld, S. O., Skeem, J. L., Douglas, K. S., Edens,
J. F., Epstein, M., & Patrick, C. J. (2010). Using the PCL-R to help estimate the validity of two self-report measures of psychopathy with offenders. Assessment, 17, 206–219. doi: 10.1177/1073191109351715
Rellecke, J., Sommer, W., & Schacht, A. (2013). Emotion effects on the
N170: A question of reference? Brain Topography, 26, 62–71. doi:
10.1007/s10548-012-0261-y
Rigato, S., Farroni, T., & Johnson, M. H. (2010). The shared signal hypothesis and neural responses to expressions and gaze in infants and adults.
Social Cognitive and Affective Neuroscience, 5, 88–97. doi: 10.1093/ scan/nsp037 Rilling, J. K., Glenn, A. L., Jairam, M. R., Pagnoni, G., Goldsmith,
D. R., Elfenbein, H. A., & Lilienfeld, S. O. (2007). Neural correlates of social cooperation and non-cooperation as a function of psychopathy.
Biological Psychiatry, 61, 1260–1271. doi: 10.1016/j.biopsych.
2006.07.021
Ross, S. R., Benning, S. D., & Adams, Z. (2007). Symptoms of executive dysfunction are specific to secondary psychopathy: An examination in criminal offenders and non-institutionalized young adults.
Journal of Personality Disorders, 61, 495–501. doi: 10.1521/ pedi.2007.21.4.384 Rothemund, Y., Ziegler, S., Hermann, C., Gruesser, S. M., Foell, J., Patrick,
C. J., & Flor, H. (2012). Fear conditioning in psychopaths: Eventrelated potentials and peripheral measures. Biological Psychology, 90,
50–59. doi: 10.1016/j.biopsycho.2012.02.011
Rotshtein, P., Richardson, M. P., Winston, J. S., Kiebel, S. J., Vuilleumier,
P., Eimer, M., . . . Dolan, R. J. (2010). Amygdala damage affects eventrelated potentials for fearful faces at specific time windows. Human
Brain Mapping, 31, 1089–1105. doi: 10.1002/hbm.20921
Seals, R. W., Sharp, C., Ha, C., & Michonski, J. D. (2012). The relationship between the youth psychopathic traits inventory and psychopathology in a U.S. community sample of male youth. Journal of Personality Assessment, 94, 232–243. doi: 10.1080/00223891.2011.650303
Sergerie, K., Chochol, C., & Armony, J. L. (2008). The role of the amygdala in emotional processing: A quantitative meta-analysis of functional neuroimaging studies. Neuroscience and Biobehavioral Reviews, 32,
811–830. doi: 10.1016/j.neubiorev.2007.12.002
Skeem, J. L., Polaschek, D. L. L., Patrick, C. J., & Lilienfeld, S. O. (2011).
Psychopathic personality: Bridging the gap between scientific evidence and public policy. Psychological Science in the Public Interest, 12,
95–162. doi: 10.1177/1529100611426706
Somerville, L. H., Kim, H., Johnstone, T., Alexander, A. L., & Whalen, P.
J. (2004). Human amygdala responses during presentation of happy and neutral faces: Correlations with state anxiety. Biological Psychiatry, 55,
897–903. doi: 10.1016/j.biopsych.2004.01.007
Sommer, M., Sodian, B., Dohnel, K., Schwerdtner, J., Meinhardt, J., &
Hajak, G. (2010). In psychopathic patients emotion attribution modu-
N170 and facial emotion in psychopathy lates activity in outcome-related brain areas. Psychiatry Research, 182,
88–95. doi: 10.1016/j.pscychresns.2010.01.007
Tamietto, M., & De Gelder, B. (2010). Neural bases of the non-conscious perception of emotional signals. Nature Reviews Neuroscience, 11, 697–
709. doi: 10.1038/nrn2889
Taylor, M. J., Itier, R. J., Allison, T., & Edmonds, G. E. (2001). Direction of gaze effects on early face processing: Eyes-only versus full faces.
Cognitive Brain Research, 10, 333–340. doi: 10.1016/S09266410(00)00051-3
Tieger, T., & Ganz, L. (1979). Recognition of faces in the presence of two-dimensional sinusoidal masks. Perception & Psychophysics, 26,
163–167. doi: 10.3758/BF03208310
Tiihonen, J., Hodgins, S., & Vaurio, O. (2000). Amygdaloid volume loss in psychopathy [Abstract]. Society for Neuroscience, 2017.
Tottenham, N., Hare, T. A., & Casey, B. J. (2009). A developmental perspective on human amygdala function. In P. J. Whalen & E. A. Phelphs
(Eds.), The human amygdala (pp. 107–117). New York, NY: Guilford
Press.
Vanman, E. J., Mejia, V. Y., Dawson, M. E., Schell, A. M., & Raine, A.
(2003). Modification of the startle reflex in a community sample: Do one or two dimensions of psychopathy underlie emotional processing?
Personality and Individual Differences, 35, 2007–2021. doi: 10.1016/
S0191-8869(03)00052-7
Veit, R., Flor, H., Erb, M., Hermann, C., Lotze, M., Grodd, W., &
Birbaumer, N. (2002). Brain circuits involved in emotional learning in antisocial behavior and social phobia in humans. Neuroscience Letters,
328, 233–236. doi: 10.1016/S0304-3940(02)00519-0
Viding, E., Simmonds, E., Petrides, K. V., & Frederickson, N. (2009). The contribution of callous-unemotional traits and conduct problems to bullying in early adolescence. Journal of Child and Psychology Psychiatry,
50, 471–481. doi: 10.1111/j.1469-7610.2008.02012.x
657
Vlamings, P. H. J. M., Goffaux, V., & Kemner, C. (2009). Is the early modulation of brain activity by fearful facial expressions primarily mediated by coarse low spatial frequency information? Journal of
Vision, 9, 1–13. doi: 10.1167/9.5.12
Vuilleumier, P., Armony, J. L., Driver, J., & Dolan, R. J. (2003). Distinct spatial frequency sensitivities for processing faces and emotional expressions. Nature Neuroscience, 6, 624–631. doi: 10.1038/nn1057
Vuilleumier, P., Richardson, M. P., Armony, J. L., Driver, J., & Dolan, R. J.
(2004). Distant influences of amygdala lesion on visual cortical activation during emotional face processing. Nature Neuroscience, 7, 1271–
1278. doi: 10.1038/nn1341
Woodworth, M., & Porter, S. (2002). In cold blood: Characteristics of criminal homicides as a function of psychopathy. Journal of Abnormal
Psychology, 111, 436–445. doi: 10.1037//0021-843X.111.3.436
Yang, Y., Raine, A., Colletti, P., Toga, A. W., & Narr, K. L. (2010).
Morphological alterations in the prefrontal cortex and the amygdala in unsuccessful psychopaths. Journal of Abnormal Psychology, 119, 546–
554. doi: 10.1002/ar.1092410212
(Received June 26, 2013; Accepted February 10, 2014)
Supporting Information
Additional Supporting Information may be found in the online version of this article at the publisher’s web-site:
Appendix S1: Single trial habituation analysis
