Biological Psychology 97 (2014) 49–59

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Reduced frontal activity during response inhibition in individuals with psychopathic traits: An sLORETA study Young Youn Kim ∗ , Yoon Sun Jung Department of Forensic Psychology, Kyonggi University, Suwon, South Korea

a r t i c l e

i n f o

Article history: Received 16 September 2013 Accepted 7 February 2014 Available online 16 February 2014 Keywords: Response inhibition Psychopathic traits Standardized low-resolution electromagnetic tomography NoGo-P3 Reduced frontal function

a b s t r a c t This study investigated the response inhibition in individuals with psychopathic traits. We examined the cortical source localization of the NoGo stimuli in a Go/NoGo task by employing a standardized low-resolution electromagnetic tomography (sLORETA) using EEG. Fifteen psychopathic trait subjects and 15 control subjects performed the Go/NoGo task. The statistical analysis of P3 elicited by the NoGo stimuli indicated that the psychopathic trait group showed significantly reduced NoGo-P3 amplitudes than the control group at the frontocental area. In the Wisconsin Card Sorting Test, the psychopathic trait group showed significantly higher perseverative responses than the control group. Compared to the control group, cortical sources reduction elicited by NoGo-P3 in the psychopathic trait group was found at the left superior frontal gyrus, bilateral anterior cingulate, right precentral gyrus, and the right inferior parietal lobule. These results suggest that individuals with psychopathic traits have difficulties in inhibiting a response with reduced frontal function. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Psychopathy is a syndrome characterized by a constellation of affective, interpersonal, and behavioral/lifestyle features, including impulsivity, lack of empathy or remorse, shallow emotions, sensation-seeking, poor behavioral controls, and a persistent violation of social norms and expectations (Cleckley, 1976; Hare, 2003). Psychopathy has been associated with reduced executive functioning (Blair et al., 2006; Morgan & Lilienfeld, 2000). In previous studies of the performance on the Wisconsin Card Sorting Test (WCST), a widely used test for measuring executive functioning, psychopaths made more errors than normal controls (Gorenstein, 1982; Morgan & Lilienfeld, 2000; Sutker, Moan, & Allain, 1983). However, several researchers did not find significant differences between pasychopathic and nonpsychopathic subjects in the WCST (Devonshire, Howard, & Sellars, 1988; Mol, Van Den Bos, Derks, & Egger, 2009). Ishikawa, Raine, Lencz, Bihrle, and Lacasse (2001) reported that successful psychopaths showed better WCST performance than unsuccessful psychopaths and controls. Blair et al. (2006) reported that individuals with psychopathy showed executive dysfunction on the measure sensitive to orbitofrontal cortex

∗ Corresponding author at: Department of Forensic Psychology, Kyonggi University, 154-42, Gwanggyosan-ro, Yeongtong-gu, Suwon 443-760, South Korea. Tel.: +82 31 249 9197; fax: +82 31 249 9199. E-mail address: [email protected] (Y.Y. Kim). http://dx.doi.org/10.1016/j.biopsycho.2014.02.004 0301-0511/© 2014 Elsevier B.V. All rights reserved.

functioning. However, individuals with psychopathy did not show impairment on measures of executive function linked to the dorsolateral prefrontal cortex or anterior cingulate cortex. Individuals with psychopathic traits had difficulty in inhibiting dominant response sets and also showed a deficient capability in learning to avoid the stimuli that predict punishment (Newman & Kosson, 1986; Turgay, 2004). Newman (1998) proposed that the impulsive and disinhibitory behavior of psychopaths is the result of poor response modulation. Kiehl, Smith, Hare, and Liddle (2000) suggested that the neural processes involved in response inhibition are abnormal in psychopathy. A growing number of studies have reported that psychopathy is associated with a range of neurobiological abnormalities (Oliveira-Souza et al., 2008; Patrick, 2006). The results of a metaanalysis on 43 structural and functional imaging studies showed significantly reduced prefrontal structure and function in antisocial and psychopathic individuals (Yang & Raine, 2009). The Frontal Lobe Dysfunction Theory has been suggested that antisocial behavior in humans might be a consequence of inherited or acquired deficits in the frontal brain areas, particularly in the orbitofrontal cortex (Gorenstein & Newman, 1980). The volume of the prefrontal cortex was reduced in high psychopathy males who had committed crimes (Raine, Lencz, Bihrle, LaCasse, & Colletti, 2000; Yang et al., 2005). A considerable number of studies demonstrated that amygdala dysfunction is associated with callous-unemotional traits and represents a reduced electrodermal response to aversive stimuli in psychopaths (Birbaumer et al., 2005; Marsh et al.,

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2008). It has been argued that the orbitofrontal cortex and amygdala dysfunction in individuals with psychopathic traits disrupts emotion-based decision-making, including moral judgment (Blair, 2007; Kiehl, 2006). Using DT-MRI (Diffusion Tensor Magnetic Resonance Imaging), Sundram et al. (2012) suggested that the abnormal uncinate fasciculus in antisocial individuals indicated fronto-limbic disconnectivity. Marsh et al. (2011) reported that youths with psychopathic traits showed reduced amygdala–orbitofrontal connectivity during moral judgments. Impulsive behavior is potentially harmful to self or to others, as it is one of the core symptoms in psychopathy and has also been linked to response inhibition (Chamberlain & Sahakian, 2007; Kiehl et al., 2000). Response inhibition is the ability to suppress a prepotent response, which can be examined in Go/NoGo tasks (Pandey et al., 2012). The stimuli in Go/NoGo tasks elicit two event-related potential (ERP) components, the N2 and P3 (Kopp, Mattler, Goertz, & Rist, 1996). The N2 is seen as a negative deflection with a maximum over the frontal scalp locations in the NoGo (no button press) compared to the Go trials (button press). It can be observed between 250 and 350 ms after stimulus onset. The P3 is a larger positive deflection at about 300–600 ms post-stimulus with a frontocentral maximum in the NoGo compared to the Go trials (Bokura, Yamaguchi, & Kobayashi, 2001; Eimer, 1993; Gajewski & Falkenstein, 2013). The NoGo-N2 was suggested to be related to conflict detection or a top-down inhibition mechanism suppressing an inappropriate response tendency at a processing stage prior to motor execution (Kim, Kim, Yoo, & Kwon, 2007; Nieuwenhuis, Yeung, van den Wildenberg, & Ridderinkhof, 2003). The NoGo-P3 was assumed to reflect response inhibition in the frontal cortex (Kopp et al., 1996; Ruchsow et al., 2008; Tian & Yao, 2008). Dimoska and Johnstone (2007) reported that reduced response inhibition has been linked to increased levels of impulsivity in healthy volunteers. There were several ERP studies using Go/NoGo tasks in subjects with a psychiatric disorder of impulsivity. Ruchsow et al. (2008) found reduced NoGo-P3 amplitudes in individuals with a borderline personality disorder. Also, a reduction of the NoGo-N2 has been found in subjects with an attention deficit hyperactivity disorder (Pliszka, Liotti, & Woldorff, 2000). Kiehl et al. (2000) reported alterations of N2 and P3 in subjects with schizophrenia and psychopathy. Using a visual Go/NoGo task, Varlamov, Khalifa, Liddle, Duggan, and Howard (2011) found that psychopathic subjects showed significantly reduced amplitude of an early frontal negative ERP component. However, Munro et al. (2007) found the enhanced frontal N2 and P3 effect in response to the NoGo relative to the Go conditions in psychopaths. Gao and Raine (2009) conducted a meta-analysis of 38 ERP studies in psychopathic individuals and found that compared to the nonpsychopathic offenders, psychopathic offenders showed reduced P3 amplitudes in oddball tasks, but not in other tasks. Collectively, the results of the previous ERP studies in psychopaths using Go/NoGo tasks are controversial. Several ERP studies in undergraduates with psychopathic traits were published. Campanella, Vanhoolandt, and Philippot (2005) reported that subjects with psychopathic tendencies presented decreased N300 components in a visual oddball task. Carlson, Thái, and McLarnon (2009) found frontal P3 amplitude reduction, which was inversely related to the Self-Centered Impulsivity factor of the Psychopathic Personality Inventory in a rotated heads task. In contrast, Carlson and Thái (2010) suggested that the Fearless Dominance factor of the Psychopathic Personality Inventory was associated with P3 augmentation in an expectancy AX-continuous performance task. These results support that subjects with psychopathic traits have specific ERP pattern characteristics. Due to its high temporal resolution and convenience, ERP has been widely used for studies of psychopathy. However, ERP offers a rather limited spatial resolution. This limited spatial

resolution can be elevated by the use of high-density electrode arrays. Several current density estimation techniques have been developed to determine the electrophysiological source locations in the subjects. Low-resolution electromagnetic tomography (LORETA) assumes that the voltage will change gradually and selects the distribution of the source magnitudes that is maximally smooth (Pascual-Marqui, Michel, & Lehmann, 1994). Standardized LORETA (sLORETA) (Pascual-Marqui, 2002) uses the normalization by noise power, and recommends to use the pseudo-statistic values as estimates of brain activity, and to apply in statistical non-parametric mapping for the analysis of experimental designs. To our knowledge, there is no study using the cortical source localization for a Go/NoGo task in individuals with psychopathic traits. In healthy subjects, the cortical source localizations of the P3 component in a Go/NoGo task showed activations in the orbitofrontal cortex and medial frontal gyrus (Bokura et al., 2001; Jonkman, Sniedt, & Kemner, 2007; Tian & Yao, 2008). In this study, we aimed to explore the cortical generators of NoGo-P3 in individuals with psychopathic traits. Undergraduate students were divided into a psychopathic trait and control group according to the scores of the Psychopathic Personality InventoryRevised (PPI-R, Lilienfeld & Widows, 2005). We used sLORETA with a high-density 64-channel EEG acquisition system. We used a template 3-dimensional MRI as a realistic head model of the boundary element method (Fuchs, Drenckhahn, Wischmann, & Wagner, 1998) for all subjects. This is the first study to determine the cortical correlates of NoGo-P3 in individuals with psychopathic traits using high-density EEG, within the general framework of the voxel-based statistical parametric mapping of current density images. We examined the ERPs produced by the NoGo and Go stimuli in a Go/NoGo task. The sLORETA analysis was conducted using the ERP results for NoGo and Go conditions. Further, statistical analyses were performed to compare the current density images of each condition from sLORETA analysis within and between groups in order to understand the neural correlates of response inhibition. To examine the executive function, we also used a Wisconsin Card Sorting Test. On the basis of the previous studies, we expected reduced NoGo-P3 amplitudes and reduced frontal activation in individuals with psychopathic traits reflecting the impaired response inhibition processes. As the N2 component is also discussed as an important component of Go/NoGo tasks (Bruin & Wijers, 2002; Falkenstein, Hoormann, & Hohnsbein, 1999), we further added analyses on N2. 2. Materials and methods 2.1. Subjects Fifteen right-handed participants (males 5, females 10) with psychopathic traits (psychopathic trait group) were recruited from 743 undergraduate students from Kyonggi University on the basis of the Psychopathic Personality Inventory-Revised (PPI-R, Lee & Park, 2008; Lilienfeld & Widows, 2005). PPI-R is a useful self-report measure to assess psychopathic personality traits in forensic and clinical samples as well as in nonclinical samples (e.g., student, community). PPI-R contains 154 items which are answered using a 4-point Likert scale. The T-score cut-off scores of 65 are used in clinical practice as markers of scores that are significantly elevated (Lilienfeld & Widows, 2005). In this study, the psychopathic trait group consisted of participants with a PPI-R T-score of 65 or above. Fifteen controls (control group) with a PPI-R T-score of 55 or below were matched by age, educational level, gender, and handedness. Participants had normal or adequately corrected vision. Those subjects, regardless of group, with a history of head injury, medical and neurological disorder, or alcohol and drug abuse were excluded from this study. In order to confirm that the two groups only differ in psychopathic traits, the participants were rated with the Beck Depression Inventory (BDI, Beck & Steer, 1987), Beck Anxiety Inventory (BAI, Beck, Epstein, Brown, & Steer, 1988), Personality Assessment Inventory (PAI, Morey, 1997), Personality diagnostic questionnaire (PDQ, Hyler, 1998), Buss-Perry Aggression Scale (BPA, Buss & Perry, 1992), Barratt Impulsiveness Scale (BIS, Patton, Stanford, & Barratt, 1995), and Narcissistic Personality Inventory (NPI, Raskin & Hall, 1979). To examine the executive function, the Wisconsin Card Sorting Test (WCST, Heaton, Chelune, Talley, Kay, & Curtiss, 1993) was performed. The subject sorted

Y.Y. Kim, Y.S. Jung / Biological Psychology 97 (2014) 49–59 Table 1 Demographic information in the psychopathic trait and control group. Psychopathic trait (n = 15)

Control (n = 15)

Age Education IQ Gender (male/female)

19.9 (1.6) 13.8 (0.8) 105.4 (8.5) 5/10

20.5 (1.9) 13.8 (0.7) 107.3 (6.9) 5/10

BDI BAI PPI-R*** PAI Antisocial features** Aggression*** PDQ History of conduct disorder** Antisocial personality disorder*** BPA** BIS** NPI***

12.3 (5.8) 12.2 (9.7) 67.8 (6.3)

8.3 (6.4) 8.1 (5.3) 51.6 (4.7)

55.9 (11.3) 47.8 (9.0)

42.9 (7.6) 36.7 (6.1)

4.1 (3.0) 3.4 (1.4) 70.1 (17.9) 17.9 (4.3) 24.3 (5.7)

0.9 (1.1) 1.1 (1.0) 53.3 (10.1) 13.3 (2.5) 15.9 (4.8)

Standard deviations in parentheses. BDI: Beck Depression Inventory; BAI: Beck Anxiety Inventory; PPI-R: Psychopathic Personality Inventory-Revised; PAI: Personality Assessment Inventory; PDQ: Personality diagnostic questionnaire; BPA: Buss-Perry Aggression Scale; BIS: Barratt Impulsiveness Scale; NPI: Narcissistic Personality Inventory. ** p < 0.01. *** p < 0.001.

a series of cards on different dimensions such as color, number, and shape. Once the subject had established the currently appropriate rule (e.g., ‘sort successive cards by color’), the experimenter gave a negative feedback. Then the subject was required to change the classification to another dimension. The Korean version of the Wechsler Adult Intelligence Scale was also administered in order to determine the IQ scores of all subjects (Yum, Park, Oh, Kim, & Lee, 1992). Prior to the participation, written informed consent was obtained from all subjects about the nature of the experiment and the participant rights were fully explained. All participants were paid for their participation. Table 1 shows the demographic characteristics in the psychopathic trait and control group. There were no significant differences in age, length of education, IQ, and gender between the psychopathic trait and control group. In terms of BDI and BAI, the psychopathic trait and control group did not show any differences. These results showed no significant group differences in the depression and anxiety levels. There were significant differences in PPI-R [t = −7.96, df = 28, p = .000], PAI-Antisocial features subscale [t = −3.71, df = 28, p = .001], PAI-Aggression subscale [t = −3.96, df = 28, p = .000], PDQ-History of conduct disorder subscale [t = −3.91, df = 28, p = .001], PDQAntisocial personality disorder subscale [t = −5.19, df = 28, p = .000], BPA [t = −3.15, df = 28, p = .004], BIS [t = −3.64, df = 28, p = .001], and NPI [t = −4.35, df = 28, p = .000] between the two groups. The psychopathic trait group showed significantly higher scores than the control group in PPI-R, BPA, BIS, and NPI. Antisocial features and Aggression subscores of PAI were significantly higher in the psychopathic trait group than in the control group. The history of conduct disorder and Antisocial personality disorder subscores of PDQ were significantly higher in the psychopathic trait group than in the control group. These results showed that the psychopathic trait group reported significantly higher scores than the control group in psychopathic traits of antisocial features, impulsivity, and aggression. 2.2. Procedure In a visual Go/NoGo task, the subjects were required to respond fast and correctly by pressing a button on a response box to a visual target stimulus (Go) and inhibit the motor response to another stimulus (NoGo). The stimuli were comprised of circles and squares. The stimuli were presented on a computer monitor for 300 ms followed by a fixation cross for 900 ms. Visual stimuli were presented in foveal vision with a vertical angle of 4.0◦ and a horizontal angle of 4.0◦ . The stimulus requiring a response occurred in 66.7% of trials, thus building up a prepotent response tendency and requiring inhibition in 33.3% of the trials. Two blocks took place in the Go/NoGo task (160 Go trials and 80 NoGo trials). The sequence of trials within each block was pseudorandomized. Prior to the experimental session, a practice block of trials was administered to ensure that the subjects understood the task. The hand position used for participant response was counterbalanced across subjects. The subjects were asked to minimize eye movements and eye blinks. 2.3. EEG recording The subjects’ EEG activity was recorded using a 64-channel Quick-cap system (Neuroscan, Charlotte, USA) with linked mastoid reference in an electrically shielded and soundproofed experimental room. Eye movements and blinks were

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monitored by a horizontal electrooculogram and a vertical electrooculogram (vEOG). Impedance was maintained at 5 k or less. During the experiment, the EEG was continuously recorded with a 0.05–100 Hz analog bandpass and a sampling rate of 1000 Hz/channel. After the completion of data collection, the EEG was segmented into 1000 ms epochs, including a 100ms prestimulus baseline. The baseline was corrected separately for each channel according to the mean amplitude of the EEG over the 100-ms period that preceded stimulus onset. Those EEG epochs that contained amplitudes exceeding ±100 ␮V at any EEG or EOG channel were automatically excluded from the averaging. The EEG epochs were then averaged for each subject and each stimulus condition (correct NoGo, correct Go). The average waveforms were digitally filtered with a bandpass of 0.1–30 Hz. Artifacts or bad electrodes (mean 0.60%) were removed by visual inspection, prior to source localization. 2.4. Source localization The scalp location of each electrode was determined with a Fastrak 3D-digitizer (Polhemus, Colchester, VT, USA). The electrode locations were imported into the Curry V6.0 software (Neuroscan, Charlotte, USA), in which the template MRI and electrode locations were spatially coregistered for the purpose of source localization. Nasion and bipolar preauricular points were used for anatomical coregistration. Independent component analysis (Hyvärinen & Oja, 1997; Onton & Makeig, 2006) was then performed at 50 ms intervals around the peak mean global field power of P3. Sources were constrained to be at least 3 mm inside the liquor/skull boundary and source locations were calculated in the cortex gray matter utilizing the fixed model. We constructed a 3-compartment boundary element method model with about 4000 triangle nodes for the volume conductor (Fuchs et al., 1998). Standard conductivities were 0.33, 0.0042, and 0.33 for the brain, skull, and skin, respectively.sLORETA (Pascual-Marqui, 2002) was performed to obtain the current density images for each subject and each condition. We calculated the current densities with the Talairach atlas (Talairach & Tournoux, 1988), restricted to the cortex with fixed extended sources using a 40 mm patch (Wagner, Kohler, Fuchs, & Kastner, 2000). The residual variances were maintained below 20%. 2.5. Statistical analysis The independent t-test was used for the statistical comparison of the demographic and neuropsychological data between the psychopathic trait and control group. The behavioral data of the reaction time and response accuracy were analyzed by repeated measures analysis of variance (rmANOVA) with the stimulus condition (NoGo, Go) as a within-subject factor and the group (psychopathic trait, control) as a between-subjects factor. For every subject, the averaged ERP for each electrode site was obtained for the stimulus conditions of NoGo and Go. The N2 peak amplitude between 200 and 300 ms poststimulus and the N2 latency were analyzed by rmANOVA respectively, with the electrode site and the stimulus condition as within-subject factors, and the group as a between-subjects factor. The P3 peak amplitude between 300 and 500 ms poststimulus and the P3 latency were analyzed by rmANOVA, respectively, with the electrode site and the stimulus condition as within-subject factors, and the group as a between-subjects factor. The ANOVA was followed with planned comparisons on N2 and P3 amplitudes and latencies between groups. The statistical analysis was performed on 15 electrode sites (Fp1, Fpz, Fp2, F3, Fz, F4, FC3, FCz, FC4, C3, Cz, C4, P3, Pz, P4) and in 6 local cortical regions (prefrontal region: AF3, FP1, FPz, FP2, AF4; frontal region: F1, F3, Fz, F4, F2; frontocentral region: FC1, FC3, FCz, FC4, FC2; central region: C1, C3, Cz, C4, C2; parietal region: P1, P3, Pz, P4, P2; occipital region: CB1, O1, Oz, O2, CB2). Because 15 electrode sites were scattered on the whole scalp, the statistical analysis with 15 electrode sites has limitations in showing region-specific effect. Thus, we analyzed 6 local cortical regions to find where the difference lies. The result section presents the original degrees of freedom and the corrected probability values. For each rmANOVA, a Greenhouse–Geisser correction (Greenhouse & Geisser, 1959) was applied. All effects were estimated at a significance level of .05. Whether any correlations existed between self-reported psychopathic traits and ERP components was evaluated with Pearson’s correlation coefficient r. Bonferroni corrections of probability level were used in addition to the normal p < .05 criterion to adjust for the number of comparisons made. A stepwise multiple regression analysis was used to predict participants’ PPI-R scores from ERP variables and neuropsychological variables. The statistical analysis of the current density images was conducted using SPM8 (Welcome Department of Cognitive Neurology, London, UK; http://www.fil.ion.ucl.ac.uk/spm/) implemented in MATLAB 7.10 (Mathworks, Natick, USA). Before the analysis, the spatial preprocessing of the current density images of each stimulus condition from sLORETA analysis was performed. A voxel-to-voxel affine transformation matrix was made during the coregistration process in order to match the mean current density to the template MRI. Current density images were smoothened by convolving an isotropic Gaussian Kernel with 5 mm full width half-maximum. Spatial normalization was then performed. With the normalized current density images, one-sample t-test was investigated separately with ERP generators elicited by each NoGo condition in each group, which involved global normalization and t-contrasts. Global normalization was

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Table 2 Executive function performance in the psychopathic trait and control group.

WCST Total number of errors** Perseverative responses* Perseverative errors* Nonperseverative errors* Percent perseverative responses* Number of categories achieved

Psychopathic trait (n = 15)

Control (n = 15)

23.9 (13.2) 13.7 (11.3) 12.2 (9.1) 11.7 (5.5) 13.3 (8.1) 5.9 (0.5)

13.3 (4.9) 5.9 (1.7) 5.9 (1.6) 7.5 (3.6) 7.3 (1.7) 6.0 (0.0)

Standard deviations in parentheses. WCST: Wisconsin Card Sorting Test. * p < 0.05. ** p < 0.01.

the psychopathic trait and control group were 97.8% (SD = 2.4) and 98.9% (SD = 2.4), respectively. Statistical analysis of the accuracies revealed the main effects of stimulus condition [F(1,28) = 36.65, p = .000]. The psychopathic trait and control group showed significantly lower accuracies in the NoGo condition than in the Go condition. The reaction at the Go stimulus is the hit response, but the reaction at the NoGo stimulus is an error response (false alarms). Statistical analysis of the reaction times showed the main effects of stimulus condition [F(1,28) = 80.60, p = .000]. Both groups showed significantly faster response times in the error response to the NoGo condition than in the hit response to the Go condition. 3.3. Amplitudes and latencies of N2 and P3

achieved by proportional scaling with a grand mean scaled value of 50. A corrected p-value < .05 based on Familywise (Type I) Error control was considered statistically significant. The alternate hypothesis of the one-sample t-test was that the mean current density would be significantly different from the global mean for a regionally specific generator. Because we set the global mean as one, all voxel values subtracted by one were used for the one-sample t-test. Furthermore, two-sample t-tests were conducted for group comparisons of the normalized P3 current density images for the NoGo condition. When performing the two-sample t-tests, the global effects were estimated by assuming the mean voxel value. The grand mean scaled value was 50, and an analysis of covariance was used for global normalization in each test. Only significant clusters (uncorrected p < .001) containing at least 50 contiguous voxels were estimated. In addition, a paired ttest was performed in the condition, which involved global normalization and tcontrasts between images of stimulus conditions (NoGo, Go). Global normalization was achieved by proportional scaling with a grand mean scaled value of 50. A pvalue < .001 (uncorrected) was considered statistically significant.

3. Results 3.1. Neuropsychological results Table 2 shows the summary of WCST in the psychopathic trait and control group. The psychopathic trait and control group showed significant differences in the total number of errors [t = −2.89, df = 28, p = .007], perseverative responses [t = −2.64, df = 28, p = .013], perseverative errors [t = −2.67, df = 28, p = .013], nonperseverative errors [t = −2.48, df = 28, p = .019], and percent perseverative responses [t = −2.78, df = 28, p = .010] of the WCST. There was no difference between groups in the number of categories achieved on the WCST [t = 1.00, df = 28, p = .326]. The subjects with psychopathic traits showed higher errors and perseverative responses than the controls in the WCST. The PPI-R scores had significant positive correlations with the total number of errors [r = 0.50, p = .005, n = 30], perseverative responses [r = 0.44, p = .014, n = 30], perseverative errors [r = 0.46, p = .011, n = 30], nonperseverative errors [r = 0.47, p = .009, n = 30], and percent perseverative responses [r = 0.44, p = .014, n = 30] on the WCST. 3.2. Behavioral results Table 3 indicates the accuracies and reaction times for the Go/NoGo task in the psychopathic trait and control group. There were no significant differences between both groups in the accuracies and reaction times on the Go/NoGo task. The hit rates of Table 3 Behavioral performance of the Go/NoGo task in the psychopathic trait and control group. Stimulus

NoGo Go

Psychopathic trait (n = 15)

Control (n = 15)

Accuracy (%)

Reaction time (ms)

Accuracy (%)

Reaction time (ms)

91.0 97.8

239 (error) 277 (hit)

90.7 98.9

236 (error) 265 (hit)

Fig. 1 presents the grand-average ERPs elicited by the Go stimuli and the NoGo stimuli on the Go/NoGo task for the psychopathic trait and control group. The NoGo stimuli elicited greater N2 amplitude than the Go stimuli in both groups. The N2 amplitude were analyzed by rmANOVA with the stimulus condition (NoGo, Go) and the electrode site (Fp1, Fpz, Fp2, F3, Fz, F4, FC3, FCz, FC4, C3, Cz, C4, P3, Pz, P4) as within-subject factors and the group (psychopathic trait, control) as a between-subjects factor. The statistical analysis revealed the main effect of stimulus condition for N2 amplitude with the 15 electrode sites [F(1,26) = 25.13, p = .000]. There were no main effects of group and electrode site for N2 amplitude. With regard to N2 latency of the 15 electrode sites, there were no main effects of group, stimulus condition, and electrode site. In the statistical analysis of N2 latency in 6 cortical regions, there were significant group effects in the central region [F(1,26) = 6.35, p = .018] and the parietal region [F(1,26) = 6.43, p = .017]. The psychopathic trait group showed significantly longer N2 latencies than the control group in the central and parietal regions. The NoGo stimuli elicited higher P3 amplitude than the Go stimuli at the prefrontal sites in both groups (Fig. 1). At the frontal sites, the P3 differences between NoGo and Go conditions were reduced in the psychopathic trait group as compared to the control group. At the central sites, the control group showed higher P3 amplitude in the NoGo condition than in the Go condition, whereas the psychopathic trait group did not (Fig. 1). Statistical analysis revealed the main effects of stimulus condition [F(1,26) = 20.17, p = .000] and electrode site [F(14,364) = 16.36, p = .000] for P3 amplitude with the 15 electrode sites. We detected significant group × stimulus condition interaction [F(1,26) = 6.95, p = .014], stimulus condition × electrode site interaction [F(14,364) = 31.10, p = .000], and group × stimulus condition × electrode site interaction [F(14,364) = 3.84, p = .012]. Table 4 shows the statistical analysis of P3 amplitudes elicited by the NoGo and Go stimuli in 6 cortical regions of both groups. For the prefrontal region, there were main effects of stimulus condition [F(1,28) = 55.75, p = .000] and electrode site [F(4,112) = 12.05, p = .000]. There was no significant group effect. There was a significant stimulus condition × electrode site interaction [F(4,112) = 10.32, p = .000]. This result conveyed that the NoGo stimuli elicited higher P3 amplitude than the Go stimuli at the prefrontal region in both groups. For the frontal region, there was a main effect of stimulus condition [F(1,28) = 64.72, p = .000]. There were significant group × stimulus condition interaction [F(1,28) = 9.64, p = .004] and stimulus condition × electrode site interaction [F(4,112) = 9.97, p = .001]. At the frontocentral region, there were main effects of group [F(1,28) = 4.79, p = .038], stimulus condition [F(1,28) = 33.96, p = .000], and electrode site [F(4,112) = 4.40, p = .018] for P3 amplitude. There were significant group × stimulus condition interaction [F(1,28) = 7.84, p = .009] and stimulus condition × electrode site interaction [F(4,112) = 11.13, p = .000]. For the central region, there were main effects of group [F(1,28) = 6.34, p = .018] and stimulus

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Fig. 1. Grand-average event-related potentials elicited by the Go and NoGo stimuli in the psychopathic trait group (n = 15) and the control group (n = 15).

condition [F(1,28) = 8.45, p = .007] for P3 amplitude. There were significant group × stimulus condition interaction [F(1,28) = 6.47, p = .017] and stimulus condition × electrode site interaction [F(4,112) = 4.41, p = .016]. These results indicated that the control group elicited higher P3 amplitude in the NoGo condition than in

the Go condition at the frontocentral and central regions, whereas the psychopathic trait group did not. Significant group effects and group by condition interactions suggested that the psychopathic trait group had reduced NoGo-P3 amplitudes compared to the control group at these regions.

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Table 4 Results of repeated measures ANOVAs with Greenhouse–Geisser correction for amplitude of P3 evoked by the Go and NoGo conditions in 6 cortical regions of the psychopathic trait and control group. Effect

Region df

Group (G) Stimulus condition (C) Electrode site (S) G×C C×S G×S G×C×S

1,28 1,28 4,112 1,28 4,112 4,112 4,112

Prefrontal

Frontal

– 55.75*** 12.05*** – 10.32*** – –

– 64.72*** – 9.64** 9.97** – –

Fronto-central *

4.79 33.96*** 4.40* 7.84** 11.13*** – –

Central *

6.34 8.45** – 6.47* 4.41* – –

Parietal

Occipital

– – 7.26** – – – –

– – – – – – –

–, not significant. * p < 0.05. ** p < 0.01. *** p < 0.001.

At the parietal region, a significant main effect was noted only in electrode site [F(4,112) = 7.26, p = .002] for P3 amplitude. At the occipital region, there were no main effects of group, stimulus condition, and electrode site. With regard to P3 latency of the 15 electrode sites, a significant main effect was noted only in electrode site [F(14,364) = 20.68, p = .000]. In the statistical analysis of P3 latency in 6 cortical regions, a significant group effect was shown in the frontocentral region [F(1,26) = 4.29, p = .048]. These results showed that the psychopathic trait group showed longer P3 latencies than the control group in the frontocentral region. Table 5 presents that the psychopathic trait group manifested lower NoGo-P3 amplitude than the control group at Fz, FCz, and Cz sites, and longer NoGo-P3 latency than the control group at FCz. 3.4. Correlations between ERP components and self-reported psychopathic traits There were significant correlations between P3 elicited by the NoGo condition and self-reported psychopathic traits. The PPI-R scores had significant positive correlations with NoGo-P3 latencies at C3 and C4 sites (C3: r = 0.39, p = .031, n = 30; C4: r = 0.39, p = .039, n = 30). That is, the greater the subjects reported psychopathic personality traits, the longer the NoGo-P3 latency showed at the central sites. However, there was no significant correlation between PPI-R scores and NoGo-P3 amplitudes. The

Table 5 Amplitudes (␮V) and latencies (ms) of P3 evoked by the Go and NoGo stimuli in the psychopathic trait and control group. Amplitude (␮V) NoGo Psychopathic trait (n = 15) Fpz 5.86 (3.12) Fz 7.54 (4.42)* FCz 7.76 (4.78)** Cz 6.24 (4.25)** Pz 5.47 (4.19) Oz 6.81 (3.83) Control (n = 15) Fpz 6.69 (3.22) Fz 11.37 (4.37)* FCz 13.32 (4.38)** Cz 12.88 (4.86)** Pz 8.80 (4.05) Oz 6.18 (3.03)

Go

Table 6 Significant correlations and stepwise regression analysis predicting PPI-R score of psychopathic traits from ERP variables and neuropsychological variables.

Latency (ms)

Variables

NoGo

ERP variables NoGo-P3 latency at C3 site NoGo-P3 latency at C4 site Neuropsychological variables (WCST) Total number of errors Perseverative responses Perseverative errors Nonperseverative errors Percent perseverative responses

Go

3.34 (3.05) 5.57 (4.11) 6.44 (4.00) 6.31 (4.33) 7.48 (3.86) 7.83 (3.67)

410 (104) 384 (91) 384 (92) 379 (91) 352 (56) 365 (53)

479 (127) 367 (70) 365 (72) 343 (18) 322 (22) 336 (34)

3.80 (3.23) 6.20 (3.99) 8.14 (4.60) 9.69 (4.92) 9.08 (4.42) 6.47 (4.31)

376 (100) 342 (15) 338 (21) 340 (30) 337 (31) 383 (55)

439 (129) 347 (27) 347 (28) 331 (28) 316 (21) 326 (38)

Standard deviations in parentheses. * p < 0.05 (between groups). ** p < 0.01 (between groups).

PDQ-Antisocial personality disorder subscores had significant negative correlations with NoGo-P3 amplitudes at FC3, FCz, FC4, and Cz (FC3: r = −0.37, p = .044, n = 30; FCz: r = −0.37, p = .043, n = 30; FC4: r = −0.37, p = .042, n = 30; Cz: r = −0.50, p = .005, n = 30). The greater the subjects reported antisocial personality disorder, the smaller the NoGo-P3 amplitude showed at the frontocentral and central sites. The motor impulsiveness sub-trait of the BIS had significant negative correlations with NoGo-P3 amplitudes at FC4 and Cz, and positive correlations with NoGo-P3 latencies at F3, FC3, and C3 (FC4: r = −0.36, p = .048, n = 30; Cz: r = −0.38, p = .037, n = 30; F3: r = 0.42, p = .020, n = 30; FC3: r = 0.44, p = .015, n = 30; C3: r = 0.38, p = .040, n = 30). The greater the subjects reported motor impulsiveness, the smaller the NoGo-P3 amplitude showed at the frontocentral and central sites, and the longer the NoGo-P3 latency manifested at the frontal, frontocentral, and central sites. In addition, we noted no significant correlations between N2 and self-reported psychopathic traits. To determine which variables might be predictive of psychopathic traits, a stepwise regression was undertaken using the PPI-R score as the criterion variable. Independent variables were entered in descending order of their correlations (criterion to enter = .30) with the dependent variable. ERP variables were NoGo-P3 latency at C3 site and NoGo-P3 latency at C4 site; Neuropsychological variables were the total number of errors, perseverative responses, perseverative errors, nonperseverative errors, and percent perseverative responses on the WCST. Two variables had an adequate

PPI-R score

Variables

ˇ

Total number of errors NoGo-P3 latency at C4 site

.46 .25

r = .39* r = .39* r = .50** r = .44* r = .46* r = .47** r = .44* r

t

p

.53 3.22 .003 .39 2.22 .036 R2 = .25, F(2,26) = 10.34, p = .003

PPI-R: Psychopathic Personality Inventory-Revised; WCST: Wisconsin Card Sorting Test. * p < 0.05. ** p < 0.01.

Y.Y. Kim, Y.S. Jung / Biological Psychology 97 (2014) 49–59

Fig. 2. Statistical parametric maps showing the t-statistic (SPM{t}) for the P3 generator elicited by the NoGo stimuli in the control (a) and psychopathic trait (b) group. L/A, left anterior; R/P, right posterior. Alternative hypothesis for the onesample t-test was that the mean current density would be significantly different from the global mean for a regionally specific ERP source. These images were thresholded at t > 7.22 (p < .05 corrected (Familywise (Type I) Error control), extent k = 50). Sources elicited by NoGo-P3 in the control group appear on the middle frontal gyrus, inferior frontal gyrus, precentral gyrus, medial frontal gyrus, anterior cingulate, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, fusiform gyrus, and parahippocampal gyrus in the left hemisphere and appear on the parahippocampal gyrus and lingual gyrus in the right hemisphere. Sources elicited by NoGo-P3 in the psychopathic trait group appear on the middle frontal gyrus, medial frontal gyrus, anterior cingulate, subcallosal gyrus, and parahippocampal gyrus in the left hemisphere and show on the superior frontal gyrus, medial frontal gyrus, and parahippocampal gyrus in the right hemisphere.

predictive value to enter into the multiple regression equation: the total number of errors on the WCST and NoGo-P3 latency at C4 site (Table 6). These variables predicted 25% of the variance in the psychopathic personality traits. Increases in the total number of errors on the WCST and increases in NoGo-P3 latency at C4 site predicted increases in the psychopathic personality traits that the participant reported. 3.5. Source analysis results The source analysis was performed at 50 ms intervals around the peak mean global field power of P3. Fig. 2 shows the statistical parametric maps showing the t-statistic (SPM{t}) for the P3 generator elicited by the NoGo condition in the control and psychopathic trait group. This figure represents a statistical map of a one-sample t-test thresholded at t > 7.22 (p < .05 corrected (Familywise (Type I) Error control)), with a contiguous 50-voxel extent. Sources elicited by NoGo-P3 in the control group appear on the middle frontal gyrus, inferior frontal gyrus, precentral gyrus, medial frontal gyrus, anterior cingulate, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, fusiform gyrus, and parahippocampal gyrus in the left hemisphere and appear on the parahippocampal gyrus and lingual gyrus in the right hemisphere. Sources elicited by NoGo-P3 in the psychopathic trait group show on the middle frontal gyrus, medial frontal gyrus, anterior cingulate, subcallosal gyrus, and parahippocampal gyrus in the left hemisphere and show on the superior frontal gyrus, medial frontal gyrus, and parahippocampal gyrus in the right hemisphere. Table 7 presents the statistically significant activation of the current density area in comparison between the stimulus conditions within groups and between groups within the stimulus conditions. In the comparison of the NoGo and Go conditions, the control group manifested significant activation on the cuneus, inferior frontal gyrus, precentral gyrus, and inferior frontal gyrus in the left hemisphere [Talairach coordinates −18/−78/20, Brodmann area (BA) 18; Talairach coordinates −49/7/13, BA 44; Talairach coordinates −57/−2/10, BA 6; Talairach coordinates −49/29/3, BA 45]. In the Go minus NoGo comparison of the control group, the current density sources elicited a significant increase on the superior parietal lobule and middle temporal gyrus in the right hemisphere [Talairach coordinates 41/−55/48, BA 7; Talairach coordinates 39/−66/29, BA

55

Fig. 3. Statistical parametric maps for the P3 component of the NoGo stimuli displaying (a) decreased current density in the psychopathic trait group compared to the control group and (b) map of t-statistic (Spm{t}). L/A, left anterior; R/P, right posterior. The significantly deactivated area (p < .001 uncorrected, extent k = 50) in the psychopathic group compared to the control group is shown on the Talairach coordinate. Cortical sources reduction elicited by NoGo-P3 in the psychopathic group was found at the anterior cingulate and superior frontal gyrus in the left hemisphere and found at the precentral gyrus, anterior cingulate, and inferior parietal lobule in the right hemisphere. The right image in (a) displayed the reduced activation region in the psychopathic group on a rendered image.

39]. In the result of paired t-test of the Go minus NoGo comparison, the psychopathic trait group manifested significant activation on the fusiform gyrus and lingual gyrus in the left hemisphere [Talairach coordinates −22/−94/−12, BA 18; Talairach coordinates −5/−93/−6, BA 17]. No significant source difference was detected between the Go and NoGo conditions in the psychopathic trait group. The result of the paired t-test in the psychopathic trait group exhibited no significant activation in the Go minus NoGo comparison. Comparisons between groups within stimulus conditions exhibited statistical significance in only one case. That is, in the comparison of the control and psychopathic trait group at the NoGo condition, the control group showed significant cortical activation than the psychopathic trait group on the superior frontal gyrus, cingulate gyrus, and middle frontal gyrus in the left hemisphere [Talairach coordinates −20/13/48, BA 6; Talairach coordinates −13/−16/38, BA 24; Talairach coordinates −25/16/40, BA 8] and on the cingulate gyrus, precentral gyrus, medial frontal gyrus, and inferior parietal lobule in the right hemisphere [Talairach coordinates 4/−18/37, BA 24; Talairach coordinates 36/1/34, BA 6; Talairach coordinates 6/−14/52, BA 6; Talairach coordinates 46/−46/49, BA 40]. As the result of the two-sample t-test, Fig. 3 illustrates the statistically significant reduction in the current density area observed in the psychopathic trait group, as compared to that observed in the control group, at the NoGo condition. The threshold of significance for the clusters was defined as that containing at least 50 contiguous voxels exceeding a T value of 3.41, which corresponds to an uncorrected significance level of 0.001. Cortical sources reduction elicited by NoGo-P3 in the psychopathic group was found at the anterior cingulate and superior frontal gyrus in the left hemisphere and found at the precentral gyrus, anterior cingulate, and inferior parietal lobule in the right hemisphere. This result suggests that the reduced activation in the frontal lobe was responsible for the reduced frontal function observed in the psychopath in previous fMRI/PET studies (Raine, 2001; Yang & Raine, 2009). 4. Discussion In line with our prediction NoGo-P3 amplitudes individuals with psychopathic traits had reduced NoGo-P3 amplitudes compared to the controls in the frontocentral and central regions. Most interestingly, source analysis results show that the psychopathic trait group exhibited reduced frontal activity during response inhibition. Compared to the control group, a significantly lower

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Table 7 Cortical activations of P3 evoked by the Go and NoGo stimuli in the psychopathic trait and control group. Region of activation Between stimulus conditions within groups NoGo > Go in the control group Cuneus Inferior frontal gyrus Precentral gyrus Inferior frontal gyrus Go > NoGo in the control group Superior parietal lobule Middle temporal gyrus NoGo > Go in the psychopathic trait group Fusiform gyrus Lingual gyrus Go > NoGo in the psychopathic trait group Between groups within stimulus conditions Controls > Psychopathic trait subjects at NoGo condition Superior frontal gyrus Cingulate gyrus Precentral gyrus Cingulate gyrus Middle frontal gyrus Medial frontal gyrus Inferior parietal lobule Psychopathic trait subjects > Controls at NoGo condition Controls > Psychopathic trait subjects at Go condition Psychopathic trait subjects > Controls at Go condition

L/R

Brodmann area

Number of voxels

Talairach x, y, z (mm)

Z-score

L L L L

18 44 6 45

2136 336 312 53

−18, −78, 20 −49, 7, 13 −57, −2, 10 −49, 29, 3

5.96 5.02 4.59 3.56

R R

7 39

81 414

41, −55, 48 39, −66, 29

6.91 7.53

L 18 L 17 [No significant activation]

132 50

−22, −94, −12 −5, −93, −6

4.46 3.75

L 6 R 24 R 6 L 24 L 8 R 6 R 40 [No significant activation] [No significant activation] [No significant activation]

97 114 152 169 84 71 59

−20, 13, 48 4, −18, 37 36, 1, 34 −13, −16, 38 −25, 16, 40 6, −14, 52 46, −46, 49

5.15 5.25 4.31 3.55 5.25 5.15 5.03

current density elicited by NoGo-P3 in the psychopathic trait group was found at the anterior cingulate and superior frontal gyrus in the left hemisphere and at the precentral gyrus, anterior cingulate, and inferior parietal lobule in the right hemisphere. With respect to accuracies and reaction times on the Go/NoGo task, there were no significant differences between the groups. In both groups, we observed lower accuracies and faster reaction times to the NoGo condition than to the Go condition. Therefore, ERP differences between groups were most likely not due to differences in the behavioral data. The fact that both groups did not differ according to the accuracies and reaction times can be explained by the very easy task. Previous studies indicated that similar P3 Go/NoGo effects were found for movement and no-movement conditions (Bruin & Wijers, 2002; Burle, Vidal, & Bonnet, 2004). These results suggested that the P3 does not merely reflect the absence of negative motor potentials in NoGo trials, but that the NoGo-P3 is related to response inhibition. Using ERP and fMRI as the subjects performed non-motor (count) and motor (button press) trials of the Go/NoGo task, Smith, Jamadar, Provost, and Michie (2013) suggested that the P3 NoGo > Go effect in motor tasks is caused not by the movement-related negativity on Go trials, but by the inhibition-related positivity on NoGo trials. Our study found that individuals with psychopathic traits had reduced NoGo-P3 amplitudes compared to the controls in the frontocentral and central regions. Reduced NoGo-P3 amplitudes in the psychopathic trait subjects may reflect impaired response inhibition. Individuals with psychopathic traits showed reduced NoGo-P3 amplitudes and negative correlation with the motor impulsiveness sub-trait of the Barratt Impulsiveness Scale. These results support that reduced NoGo-P3 amplitudes may reflect impaired response inhibition and increased impulsivity. On the basis of the view that the NoGo-P3 is related to response inhibition (Bruin & Wijers, 2002; Burle et al., 2004; Herrmann, Jacob, Unterecker, & Fallgatter, 2003; Smith et al., 2013), our findings support that reduced NoGo-P3 of individuals with psychopathic traits may reflect abnormal neural processes involved in response inhibition. Furthermore, we found a significant negative correlation between the antisocial personality disorder sub-trait and frontocentral NoGo-P3 amplitudes. That is, the lower the amplitude of the frontocentral NoGo-P3, the higher

is the antisocial personality disorder. Racer et al. (2011) found that Antisocial Process Screening Device scores were negatively correlated with ERP measures of an attention task in youth with psychopathic symptoms. These results support that there are cognitive problems in individuals with psychopathic traits as well as in psychopaths. The results of the previous studies in psychopaths using Go/NoGo tasks are inconsistent. Kiehl et al. (2000) suggested that the neural processes involved in response inhibition are abnormal in psychopathy, whereas Munro et al. (2007) concluded that the neural processes involved in response inhibition are not abnormal in psychopathy. Kiehl et al. (2000) found that the control group (n = 13) showed greater frontal negativity (N2) to the NoGo condition than to the Go condition, whereas the psychopaths (n = 13) did not. However, Kiehl et al. (2000) reported that the control group showed more positivity (P3) to the Go condition than to the NoGo condition, whereas the psychopaths showed greater P3 to the NoGo condition than to the Go condition. The P3 of healthy controls shows more positivity in the NoGo compared to the Go trials (Bokura et al., 2001; Eimer, 1993; Gajewski & Falkenstein, 2013). Therefore, NoGo-P3 pattern of psychopaths in the study of Kiehl et al. (2000) is similar to that of healthy controls in the previous studies (Bokura et al., 2001; Eimer, 1993; Gajewski & Falkenstein, 2013). Munro et al. (2007) reported that 15 offenders, including 6 psychopaths, showed greater frontal N2 and P3 to the NoGo condition than to the Go condition. However, the researchers reported that a larger sample size could increase power to find differences between offenders and controls. Our findings showed that psychopathic trait subjects exhibited reduced frontal NoGo-P3 compared to the controls. Our results also support that the neural processes involved in response inhibition are abnormal in individuals with psychopathic traits. We believe that more research is required in order to study ERP characteristics in a sufficient number of psychopaths using Go/NoGo tasks. We found in our ERP study that individuals with psychopathic traits had longer NoGo-N2 latencies in the centroparietal regions and longer NoGo-P3 latencies in the frontocentral regions than the control group. Moreover, NoGo-P3 latencies at the central regions had positive correlations with the scores of Psychopathic Personality Inventory-Revised. The greater the subjects reported

Y.Y. Kim, Y.S. Jung / Biological Psychology 97 (2014) 49–59

psychopathic personality traits, the longer the NoGo-P3 latency showed at the central sites. We consider that longer NoGo-N2 and NoGo-P3 latencies in the psychopathic trait group may reflect difficulties in suppressing a prepotent response. However, the amplitude of N2 components, with more negative values in the NoGo as compared to the Go condition, did not yield any significant group differences. Our results of a reduced NoGo-P3 and normal NoGo-N2 amplitudes in individuals with psychopathic traits support that both components reflect different processes. The NoGo-P3 may reflect response inhibition, whereas the NoGo-N2 has assumed to be associated with response conflict (Kim et al., 2007; Kopp et al., 1996; Nieuwenhuis et al., 2003; Tian & Yao, 2008). Since these electrophysiological data suggest separate processes in both components, we interpret reduced frontal NoGo-P3 amplitudes and longer frontal NoGo-P3 latencies as indications of inhibitory deficits in individuals with psychopathic traits. In addition, our neuropsychological data support this interpretation. The psychopathic trait group showed significantly higher errors and perseverative responses than the control group in the Wisconsin Card Sorting Test. That is, the psychopathic trait group had difficulty in shifting proper and flexible cognitive set according to the feedback. The psychopathic trait group insisted the existing rule set in spite of knowing the error. Patients with frontal cortical damage were notoriously bad at the change stage, which often was explained by the perseveration of the previously appropriate rule (Demakis, 2003). These results support that individuals with psychopathic traits had difficulty in inhibiting dominant response sets and learning proper behavior according to the response feedback. Furthermore, the results from the multiple regression analysis support the conclusion that one must examine the value of responses containing an ERP variable (NoGo-P3 latency at C4 site) and a neuropsychological variable (the total number of errors on the WCST) as predictors of psychopathic traits. However, in this study the ERP variable and the neuropsychological variable predicted only a total 25% of the variance in psychopathic personality traits. In further research, a variety of variables must be examined to find the pivotal factor of psychopathic traits. The analysis of data from a larger sample of people can also increase the reliability of the predictor variables. According to the results shown in Table 7 and Fig. 3, cortical sources reduction elicited by NoGo-P3 in the psychopathic trait group was found at the left superior frontal gyrus, bilateral anterior cingulate, right precentral gyrus, and right inferior parietal lobule, as compared to the control group. These results showed that the cortical sources of NoGo-P3 were distributed mainly over the frontal area. Moreover, cortical sources reduction in the psychopathic trait group mostly elicited in the frontal regions. ERP studies analyzed the neural sources using LORETA in the Go/NoGo task and reported commonly that the NoGo-P3 activity was observed in the frontal cortex (Bokura et al., 2001; Tian & Yao, 2008). Previous fMRI analyses of the Go/NoGo task have shown that successful inhibition trials are associated with increased activation in the predominantly frontal cortex, including the ventral prefrontal cortex, dorsolateral prefrontal cortex, right inferior frontal gyrus, right lateral orbitofrontal cortex, medial orbitofrontal cortex, left inferior frontal gyrus, premotor cortex, anterior cingulate cortex, superior temporal gyrus, superior parietal regions, and inferior parietal lobule (Braver, Barch, Gray, Molfese, & Snyder, 2001; Durston, Thomas, Worden, Yang, & Casey, 2002; Goghari & MacDonald, 2009; Menon, Adleman, White, Glover, & Reiss, 2001; Rubia et al., 2001; Smith et al., 2013; Watanabe et al., 2002). Patients with left inferior frontal gyrus lesions showed significantly higher error rates than the controls in a Go/NoGo task (Swick, Ashley, & Turken, 2008). Using repetitive transcranial magnetic stimulation, Chambers et al. (2006) found that a temporary deactivation of the right inferior frontal gyrus showed impaired response inhibition.

57

These results support that the frontal cortex is vital for mediating response inhibition. Psychopathy and antisocial personality disorder are two constructs with substantial utility in predicting antisocial behavior (Salekin, Rogers, and Sewell, 1996). Antisocial personality disorder diagnostic criteria focus primarily on behavioral deviance, whereas psychopathy includes affective-interpersonal features (Hare, 2003). However, psychopathy and antisocial personality disorder are highly comorbid within criminal offenders (Coid, 2002), raising the possibility that the pathophysiology of the underlying disorders may be the same (Riser & Kosson, 2013; Yang & Raine, 2009). Most psychopathic individuals meet diagnostic criteria for antisocial personality disorder, whereas most individuals with antisocial personality disorder are not psychopathic (Hare, 1996). In the antisocial group, abnormal brain activations during a Go/NoGo task have been described in an fMRI study (Völlm et al., 2010). The antisocial personality disorder group showed reduced activations in the dorsolateral prefrontal cortex in comparison to the healthy controls in the Go/NoGo task. Several fMRI results using Go/NoGo tasks in subjects with other psychiatric disorders, including bipolar disorder, attention-deficit/hyperactivity disorder, and cocaine user, suggested that reduced activation in the frontal region involved in response inhibition may represent the underlying trait abnormalities (Kaufman, Ross, Stein, & Garavan, 2003; Vasic et al., 2013; Townsend et al., 2012). Using sLORETA, Pandey et al. (2012) showed that alcoholics had a significantly lower current density at the source than the control subjects for the NoGo condition at the bilateral anterior prefrontal regions. These results showed commonly reduced frontal activity during the Go/NoGo tasks as well as impairment of response inhibition. Taken together, our sLORETA result, which shows reduced frontal activity in the psychopathic trait group during the Go/NoGo task, supports that individuals with psychopathic traits have difficulties in inhibiting a response. In summary, this is the first research to examine the cortical activation in individuals with psychopathic traits during the Go/NoGo task using sLORETA. As expected, individuals with psychopathic traits demonstrated reduced NoGo-P3 amplitudes than the controls at the frontocentral and central regions. The psychopathic trait group exhibited significantly higher errors and perseverative responses than the control group in the Wisconsin Card Sorting Test. The lower the amplitude of the frontocentral and central NoGo-P3, the higher the antisocial personality disorder. At the frontal regions, the psychopathic trait group had a significantly lower current density at the source than the control group in NoGo-P3. Our results suggest that individuals with psychopathic traits may have impaired response inhibition with reduced frontal function. Acknowledgments This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0002490). We are grateful to Prof. Soo Jung Lee and Prof. Beom Jun Kim of Kyonggi University and Prof. Jun Soo Kwon of Seoul National University College of Medicine for their invaluable technical support. References Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988). An inventory for measuring clinical anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology, 56, 893–897. Beck, A. T., & Steer, R. A. (1987). Beck Depression Inventory manual. San Antonio: The Psychological Corporation. Birbaumer, N., Veit, R., Lotze, M., Erb, M., Hermann, C., Grodd, W., et al. (2005). Deficient fear conditioning in psychopathy. Archives of General Psychiatry, 62, 799–805.

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