Disclosing concealed information on the basis of cortical activations

NeuroImage 44 (2009) 1380–1386

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NeuroImage j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / y n i m g

Disclosing concealed information on the basis of cortical activations Izuru Nose a, Jun'ichiro Murai b, Masato Taira c,d,⁎ a

Faculty of Human Science, Bunkyo University, Saitama 343-8511, Japan Department of Human Studies, Bunkyo Gakuin University, Saitama 356-8533, Japan c Advanced Research Institute for the Science and Humanities, Nihon University, Tokyo 102-8251, Japan d Division of Applied System Neuroscience, Advanced Medical Research Center, Nihon University Graduate School of Medical Science, Tokyo 173-8610, Japan b

a r t i c l e

i n f o

Article history: Received 18 February 2008 Revised 1 November 2008 Accepted 5 November 2008 Available online 14 November 2008

a b s t r a c t Concealed information, which is information only known to oneself is sometimes crucial for criminal investigation. In this study, we examined cortical activations related to incidental responses to concealed information. We found that cortical responses to stimuli related to concealed information were different from those to other stimuli; the bilateral ventrolateral prefrontal (VLPF) areas, left inferior frontal gyrus, right middle frontal gyrus and right inferior parietal lobule were activated, and among those activated areas, the right VLPF was found to be crucial. Furthermore, we examined by discriminant analysis which cortical areas contribute to the determination of whether the subjects had concealed information. On the basis of the activity in the right VLPF, we were able to correctly identify 32 of the 38 subjects (84.21%) as who had concealed information. These results suggest that the right VLPF may play a crucial role in the incidental processing of concealed information, and we were able to determine whether a subject had concealed information without the need for deceptive responses. © 2008 Elsevier Inc. All rights reserved.

Introduction Concealed information, which is information only known to oneself is sometimes crucial for criminal investigation. To judge whether a suspect has detailed knowledge of a crime, the polygraph test is often used. In the polygraph test, the suspect is asked a series of questions and autonomic nervous system responses (e.g., skin conductance, respiration, and pulse wave) are measured. For example, a suspect is questioned about the tool that he/she used for committing homicide: “Did you strangle with a necktie?”, “With a towel?”, “With a belt?” This test procedure is called the guilty knowledge test (GKT). If the victim had been strangled with a belt, and if the suspect were the true criminal, the physiological responses to the question about the belt would be more prominent than those for the others. The question about a fact that only the criminal knows is called the critical question. In a typical polygraph test, the suspect is instructed to answer “no” to all the questions, so that he/she must respond deceptively to the critical question. On the other hand, even if the suspect is instructed to answer “yes” or not answer all the questions, it has been reported that similar physiological response patterns are observed (e.g., Kugelmass et al., 1967; Elaad and Ben-Shakhar, 1989; Furedy and Ben-Shakhar, 1991). Therefore, the polygraph test is carried out not to judge whether the suspect is lying (detection of deceptive responses), but to judge whether

the suspect has knowledge about the critical questions (detection of having concealed information). Recently, researchers have investigated brain mechanisms underlying deceptive responses by measuring central nervous system activity using functional MRI (fMRI) or PET (Spence et al., 2001, 2008; Langleben et al., 2002; Ganis et al., 2003; Abe et al., 2006). Researchers of these studies have focused on identifying the cortical areas involved in deceptive responses, and all the subjects participating in these experiments were required to respond deceptively. In this study, we investigated whether we could identify the cortical activation patterns related to incidental processing of concealed information. Stimuli related to and not related to the concealed information were presented randomly, and subjects were not asked whether they had knowledge about the information so that they did not need to respond deceptively. In this situation, if the subjects have the concealed information and are exposed to the information, their relevant memory would be activated incidentally and their cortical activation patterns would differ from those of the subjects who do not have this information. Furthermore, we examined by discriminant analysis which cortical areas contribute to the determination of whether the subjects had concealed information, and we validated the percentage of correct classification by cross-validation methods. Materials and methods

⁎ Corresponding author. Division of Applied System Neuroscience, Nihon University Graduate School of Medical Science, 30-1 Ohyaguchi-Kamicho, Itabashi, Tokyo 173-8610, Japan. Fax: +81 3 3972 8292. E-mail address: [email protected] (M. Taira). 1053-8119/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2008.11.002

Subjects Forty right-handed normal volunteers participated in this study. All the subjects had normal or corrected vision, and we confirmed that they

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had no history of psychiatric or neurological illness at the interview. They were randomly assigned to one of two groups. Twenty of the 40 subjects (9 males, 11 females; mean age, 20.15) were assigned to the concealed-information (CI) group, and the remaining 20 subjects (10 males, 10 females; mean age, 21.24) were assigned to the no-concealedinformation (nCI) group. We excluded data of two subjects (one in the CI group, another in the nCI group) from further analysis because of motion-induced artifact on MR images. Finally, nineteen subjects (9 males, 10 females; mean age, 20.26) were assigned to the CI group, and the remaining 19 subjects (9 males, 10 females; mean age, 21.32) were assigned to the nCI group. Written informed consent was obtained from each subject. This project was conducted in accordance with the Declaration of Helsinki and approved by the Ethical Committee of Nihon University School of Medicine. Procedure The subjects in the CI group were instructed to choose one of five playing cards (the four of clubs, C4; the five of clubs, C5; the nine of spades, S9; the two of hearts, H2; and the jack of diamonds, DJ), and to remember it (card test). However, all of the five cards were replaced with C5, and all the subjects of the CI group selected the same card (C5). The subjects in the CI group were told that the experimenter will attempt to detect the chosen card on the basis of their brain activity measured by fMRI while they were performing the modified oddball task (Rosenfeld et al., 1991; Farwell and Donchin, 1991), so they should perform the task calmly so as not to disclose concealed information about the chosen card (C5). They were prohibited from implementing countermeasures, such as body movements or mental arithmetic. They were also informed that further experiments would be conducted if the experimenter was able to identify the card that they selected. Further experiments were not actually conducted. The card test was not carried out on the subjects in the nCI group, and they only participated in the modified oddball task. Brain activity during the modified oddball task was measured by fMRI with an event-related design. After the experiment, all the subjects were debriefed by the experimenter. Tasks In the modified oddball task, six playing cards (C4, C5, S9, H2, DJ, and the eight of diamonds: D8) were randomly presented on a small screen attached to a head coil using an LCD projector (visual angle, 6.50 × 10.13°). In this task, C5 is defined as the critical stimulus, D8 as the target stimulus, C4, S9, H2 and DJ as the standard stimuli. The subjects set their thumb and index fingers on two different buttons, and were instructed to press one of them as quickly and accurately as possible when D8 (target) was presented and press the other button when other cards (i.e., C4, C5, S9, H2 and DJ) were presented. The assignment of the buttons to press was counter-balanced in each group. C5 (critical) was the chosen card for the CI group, but one of the nontarget cards for the nCI group. Each stimulus appeared for 500 ms, and the inter-trial interval was 7 s. This experiment was composed of two sessions, and each card was presented 15 times in one session (total 30 times). The subjects performed 12 practice trials at the beginning of the experiment to reduce the overall variance of reaction times. Imaging All images were acquired with a 1.5 Tesla MR scanner (Siemens Symphony). Functional images were obtained using a T2⁎-weighted gradient-echo EPI sequence (29 near axial slices, TR = 3000 ms, TE= 50 ms, FA = 90°, 64 × 64 pixels, FOV = 192 mm, 4 mm thickness). Additionally, a T1-weighted anatomical image was obtained for each subject (TR= 2200 ms, TE= 3.93 ms, FA = 15°, TI= 1100 ms, 1 mm3 voxel, FOV = 256 mm).

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Data analysis Preprocessing and data analysis were performed using SPM99 software (Wellcome Department of Imaging Neuroscience, London; http://www.fil.ion.ucl.ac.uk/spm/). The first four functional images were discarded to allow for magnetic saturation. A total of 210 images were acquired per session and per subject. The functional images were temporally corrected for acquisition time difference with regard to the middle slice, realigned to the first image to correct for movementrelated effects, coregistered to the anatomical image, normalized to the MNI brain template, and spatially smoothed with an isotropic Gaussian kernel (FWHM = 12 mm). We conducted voxelwise statistical analysis on the basis of the general linear model (GLM). For the statistical model, an event-related design was modeled using the canonical hemodynamic response function and the temporal derivative, and low-frequency drifts were removed using a high-pass filter (128 s). For each subject, we computed contrasts for “target N standard”, “targetN critical”, “critical N standard”, and “critical N target”. In order to exclude the possibility of negative activations, we applied an inclusive mask by the contrast image of “target” (in the former two contrasts) and “critical” (in the latter two contrasts). In this analysis, data from the two sessions were averaged. A random-effect model was used for the group analysis of data from each subject. We also performed direct comparisons of the brain activations in response to D8 (target) and C5 (critical) between the CI group and the nCI group. At first, we assessed the statistical significance at a singlevoxel threshold of p b 0.001 (uncorrected) and activations involving a contiguous cluster of at least 30 voxels were reported. Then, in order to define the minimum cluster size which guaranteed at a threshold of p b 0.05 for multiple comparison, we applied the Monte Carlo simulation 1000 times (AlphaSim, AFNI, http://afni.nimh.nih.gov/) to our data and reassessed those activations (voxel-level p b 0.000036, cluster size= 194, resulting in a family-wise p b 0.05). MNI coordinates indicating the peak activation were converted to Talairach coordinates (Talairach and Tournoux, 1988). We performed the region of interest (ROI) analysis using MarsBaR software (http://marsbar.sourceforge.net). Significantly activated clusters in the contrast of “critical N standard” subtraction analysis for the CI group were selected as ROIs (p b 0.001, uncorrected; no extent threshold). Then, the mean percent signal change of each ROI was calculated for each card stimulus. Furthermore, to classify each subject into either of two groups, we performed the discriminant analysis on the basis of the activations of those ROIs in each subject. The standardized percent signal changes for C5 (critical) were entered as the independent variable and groups were entered as the dependent variable. A stepwise method was used to select ROIs which contribute to the discrimination (significant level to enter = 0.05 and stay = 0.10). Finally, we validated the percentage of correct classification by the cross-validation method, which leaves one subject out from the group analyses for testing. In this analysis, when we classified the subject in the CI group, we redefined ROIs by the data of subjects without that one (“one-out” way). Results Behavioral results The mean reaction times (RTs) and mean numbers of error responses are shown in Table 1. RTs for correct responses between 300 and 1200 ms were analyzed. The mean RTs were subjected to a mixed-design ANOVA with two factors (group and card). There was a significant main effect of the card factor (F5,180 = 61.35, p b 0.001) and interaction of both factors (F5,180 = 4.27, p b 0.01), but no main effect of the group factor (F1,36 = 0.02, n.s.). In the CI and nCI groups, multiple comparisons (Ryan's method, p b 0.05) revealed that the mean RT for D8 (target) was longer than those for the other cards. In the CI group,

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Table 1 Mean reaction times (ms) and mean numbers of error responses for each card stimulus in CI and nCI groups Group

Card stimuli Critical

CI

RT Error

nCI

RT Error

Target

C4

C5

S9

H2

DJ

D8

611.80 (29.63) 0.06 (0.12) 602.54 (26.67) 0.00 (0.00)

647.30 (27.96) 0.17 (0.32) 607.36 (31.21) 0.11 (0.11)

637.72 (27.18) 0.06 (0.12) 623.50 (27.44) 0.05 (0.05)

655.25 (28.21) 0.17 (0.22) 655.95 (24.82) 0.11 (0.11)

636.03 (29.73) 0.22 (0.13) 643.44 (26.58) 0.26 (0.13)

714.44 (26.78) 2.56 (0.70) 740.09 (23.98) 1.84 (0.43)

Standard error of the mean is given in parentheses.

the mean RTs for H2 and C5 (critical) were longer than those for C4. In the nCI group, the mean RT for H2 was longer than those for C4, C5 (critical), and S9, and the RT for DJ was longer than those for C4 and C5

(critical). There were no significant differences in the RTs for all cards between the groups. Although the numbers of error responses for D8 (target) increased in both groups, statistical analysis was not performed because the error responses to all stimuli were too few (0–3 responses) for statistical analysis, except for the target (D8; 0–10 responses). fMRI results The subtraction analysis showed that the target (D8) activated broad cortical areas (Fig. 1a and Supplementary Table 1). The comparison of “target N standard” for the CI and nCI groups yielded similar cortical activation patterns. The inferior frontal gyri (IFG) extending into the anterior insula, anterior cingulate gyri (BA 24), inferior parietal lobules (IPL, BA 40), basal ganglia, and thalami of both hemispheres, and the right superior temporal gyrus (STG, BA 22) were activated in both groups. Although a similar activation pattern was obtained from the comparison of “target N critical” for the nCI group, the comparison of “target N critical” for the CI group showed only a few

Fig. 1. Results of subtraction analysis. (a) Cortical areas showing higher activity in response to the target (D8) than to the standard (C4, S9, H2, and DJ) and the critical (C5). Surface renderings are given for the comparisons of “target N standard” and “target N critical” in the CI and nCI groups. (b) Cortical areas showing higher activity in response to critical stimulus than to standard stimulus in CI group. The activations are shown on the surface-rendered brain (upper panel) and transverse sections (lower panel). (c) We directly compared the cortical activations in response to the critical stimulus between the two groups. Cortical areas showed a higher activity in the CI group than in the nCI group and those showed a higher activity in the nCI group than in the CI group are shown on the transverse sections.

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activated areas. We also performed direct comparisons of cortical activations in response to the target (D8) between the two groups, and did not find any significant differences. The brain activations in response to the critical (C5) are shown in Fig. 1b and Table 2. In the CI group, the result of the comparison of “critical N standard” indicated activations in the bilateral VLPFs (BA 47) including the adjacent anterior insula, the left IFG (BA 44), the right middle frontal gyrus (MFG, BA 9), and the right IPL (BA 40). We reassessed the statistical significance of those activations at a threshold of p b 0.05 (corrected) by a Monte Carlo procedure and found a significant activation in the right VLPF. The comparison of “critical (C5) N standard (C4, S9, H2, and DJ)” for the nCI group and the comparison of “critical (C5) N target (D8)” for both groups showed no suprathreshold clusters. We also performed direct comparisons of the brain activations in response to the critical (C5) between the two groups (Table 2 and Fig.1c). The bilateral VLPFs (BA 47) showed a higher activity in the CI group than in the nCI group. Further analysis by a Monte Carlo procedure showed that the right VLPF was statistically significant at threshold of p b 0.05 (corrected). On the other hand, the bilateral parahippocampal gyri showed the higher activity in the nCI group than the CI group. We performed ROI analysis of five areas that showed a higher activity in response to the critical (C5) than to the standard (C4, S9, H2 and DJ) in the CI group. Fig. 2 shows the mean percent signal changes for each card stimulus in these areas. The mean percent signal changes in each area were analyzed using mixed-design ANOVA, with the group (CI, nCI) and card (C4, C5, S9, H2, DJ, and D8) as factors. There was a significant main effect of the card factor (left VLPF: F5,180 = 10.35, p b 0.001; right VLPF: F5,180 = 12.67, p b 0.001; left IFG: F5,180 = 8.71, p b 0.001; right MFG: F5,180 = 2.77, p b 0.05; right IPL: F5,180 = 4.76, p b 0.001) and interaction of both factors (left VLPF: F5,180 = 3.49, p b 0.01; right VLPF: F5,180 = 5.68, p b 0.001; left IFG: F5,180 = 6.21, p b 0.001; right MFG: F5,180 = 3.12, p b 0.05; right IPL: F5,180 = 2.00, p b 0.10). In comparison between the CI and nCI groups, the percent signal changes for C5 (critical) in the CI group were larger than those in the nCI group in the five areas, except for the right MFG (p b 0.05). Furthermore, Table 3 shows the results of multiple comparisons (Ryan's method) among stimuli in each area. The percent signal changes for C5 (critical) were significantly larger than that for the standard cards in those five areas. Note that, in the right VLPF and in the left IFG of the CI group, the percent signal changes for C5 (critical) were significantly larger than that for the all four standard Table 2 Results of direct comparisons of cortical activations in response to critical stimulus (C5) Contrast

CI Group Critical N Standard

Area (Brodmann)

Critical N Target

L. VLPF (BA 47) R. VLPF (BA47) L. IFG (BA 44) R. MFG (BA 9) R. IPL (BA 40) No activated areas

nCI group Critical N Standard Critical N Target

No activated areas No activated areas

Comparison between groups Critical: CI N nCI L. VLPF (BA47) R. VLPF (BA47) Critical: nCI N CI

L. parahippocampal G. R. parahippocampal G.

Talairach coordinates (mm)

Z value

Cluster size in voxels

x

y

z

− 34 44 − 46 50 57

21 21 12 23 −43

−8 −4 5 28 26

3.71 3.69 3.26 3.42 3.36

148 472⁎ 72 66 63

−48 50 32 − 28 28

16 20 16 −30 −14

3 3 0 −14 −14

3.81 3.95 3.34 3.74 3.34

102 348⁎ 53 48 62

Note: L. = left, R. = right, VLPF = ventrolateral prefrontal area, IFG = inferior frontal gyrus, MFG = middle frontal gyrus, IPL = inferior parietal lobule, G. = Gyrus. ⁎: statistical significance at a family-wise threshold of p b 0.05 (corrected using a Monte Carlo procedure).

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cards. However, this was not observed in the nCI group. On the other hand, the percent signal changes for D8 (target) were significantly larger than that for the standard cards in four of five areas in the CI group, and in the two areas in the nCI group. From these results, these five areas may specifically respond to the critical (C5, concealed information) in the CI group. The response to DJ was larger than that to C4 in two areas [the right VLPF (BA 47) and left IFG (BA 44)] in the CI group (See Discussion). In these five areas, we examined by discriminant analysis which areas contribute to the discrimination of whether the subject had concealed information. Results of variable selection by the stepwise technique revealed that activation in the right VLPF contributed to the discrimination (Wilks' Lambda = 0.49, p b 0.001). We conducted discriminant analysis with the standardized percent signal changes for the critical (C5) in this area as the independent variable and groups as the dependent variable. As a result, the canonical coefficient for the right VLPF was 0.72 (Eigen value = 1.06, Wilks' Lambda 0.49, p b 0.001) (Fig. 3). We validated the number of subjects and percentages classified into each group by the cross-validation method, which leaves one subject out from the group analyses for testing (Table 4). The percentages of correct classification were 84.21% of 19 subjects in the CI group and 84.21% of 19 subjects of the nCI group (total percentage: 84.21%). Discussion In this study, we examined whether we are able to identify the cortical activation patterns related to the incidental processing of concealed information without the need for the subject's deceptive responses. From an applied perspective, skin conductance recordings could be simpler and much cheaper way to detect the concealed knowledge; however, fMRI enables us to investigate underlying neural mechanisms and give the theoretical background of the mental processes of deception. We found that the bilateral VLPFs (BA 47), the left IFG (BA 44), the right MFG (BA 9), and the right IPL (BA 40) were activated during the processing of the critical stimulus (C5) that had an important implication in the guilty knowledge test. We also assessed the statistical significance of those activation areas at a threshold of p b 0.05 (corrected) by a Monte Carlo procedure and confirmed a significance of the activation in the right VLPF. Furthermore, we verified whether these cortical activation patterns are useful for judging whether a person had concealed information. Among these areas, the response of the right VLPF contributed mostly to the correct classification of the subjects to their assigned groups. We were able to correctly classify 84.21% of the 38 subjects into their assigned group on the basis of the activity in this area. Thus, the right VLPF may play a crucial role in the incidental processing of concealed information. The subjects of CI groups were instructed to perform the task calmly so as not to disclose concealed information, and they were prohibited from implementing countermeasures, such as body movements or mental arithmetic. We confirmed that they did not cause intentional movements on the basis of the results of head motion analysis, and that they did not engaged in any distracting efforts on the basis of their introspections after the experiment. Additionally, we found no salient delays in the overall mean RTs, which show their engagement of diversion strategies. Therefore, we considered that all the subjects of CI group complied with our instructions. Behavioral results The RT for the target (D8) was longer than those for the other stimuli and the number of error responses in the target trials increased in both groups. Because of the rare occurrences of the target stimulus (D8), it was more difficult to respond to this stimulus than to the other stimuli. The subjects of the nCI group responded

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Fig. 2. Mean percent signal changes in response to each card stimulus in five ROIs. Light grey, white, and dark grey bars indicate percent signal changes in response to the standard (C4, S9, H2 and DJ), critical (C5), and target stimuli (D8), respectively. The ROIs were defined as the significantly activated clusters as determined by contrasting “critical N standard” in the CI group. Error bars are standard errors of the mean. VLPF, ventrolateral prefrontal area; IFG, inferior frontal gyrus; MFG, middle frontal gyrus; IPL, inferior parietal lobule.

more slowly to red cards (H2 and DJ) than to black cards (C4, C5, and S9) because the similarity in color (red H2, DJ, and D8) made the judgment difficult. In some previous studies using the deception detection paradigm (Spence et al., 2001; Nuñez et al., 2005), it was reported that the subjects' RTs for deceptive responses were longer than those for truthful responses. However, we were not able to find a significant increase in RT for the critical (C5), and there were no statistically significant differences in RT for the critical (C5) between the CI and nCI groups. This may be due to our task situation, in which the subjects did not need to respond deceptively. fMRI results Responses to critical stimuli In the comparison of “critical N standard” for the CI group, we found that the bilateral VLPFs (BA 47) extending into the anterior insula, the left IFG (BA 44), the right MFG (BA 9), and the right IPL (BA 40) were activated. The subjects of the nCI group did not show areas significantly activated in response to the critical (C5). Thus, these cortical areas are may involved in the automatic neural processing of the critical (C5) that has an important implication in the guilty knowledge test.

We then performed ROI analysis and calculated the mean percent signal changes in response to each stimulus in these areas. Indeed, in the CI group, the percent signal changes in response to the critical (C5) were significantly large in all the analyzed areas, but not in the nCI group. However, the percent signal changes in response to the target (D8) were also large in the bilateral VLPFs (BA47) for both groups, and in the left IFG (BA 44) and the right IPL (BA 40) for the CI group. These results suggest that cortical areas involved in the processing of the critical (C5) are also involved in the processing of the target (D8). Thus, the subjects of the CI group may automatically detect the critical (C5), as well as the target (D8), as a meaningful stimulus. Activations of the right VLPF during deceptive responses were also observed in previous fMRI studies (Spence et al., 2001, 2008; Lee et al., 2002; Kozel et al., 2004a,b; Phan et al., 2005; Gamer et al., 2007). Spence et al. (2001, 2004) speculated that activity in VLPF reflects the suppression of prepotent truthful responses for deceptive responses. In our experiment, however, the subjects were not required to respond deceptively and truthful responses were not prepotent. On the other hand, other previous neuroimaging studies demonstrated that this area is involved in the recognition of unpleasant facial expressions (Sprengelmeyer et al., 1998), punishment and loss of reward (O'Doherty et al., 2001), and arousal of negative emotions

I. Nose et al. / NeuroImage 44 (2009) 1380–1386 Table 3 Results of multiple comparisons of percent signal changes in response to each card stimulus (p b 0.05) Area (Brodmann)

Group

Left VLPF (BA 47)

CI

Right VLPF (BA 47)

nCI CI

Left IFG (BA 44)

nCI CI

Right MFG (BA 9) Right IPL (BA 40)

nCI CI nCI CI nCI

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Table 4 Cross-validated number (N) of the subjects and percentage (%) classified into each group Predicted group

Results C5 N C4 D8 N C4 D8 N C4 C5 N C4 D8 N C4 DJ N C4 D8 N C4 C5 N C4 D8 N C4 DJ N C4 Not significant C5 N C4 Not significant C5 N D8 N Not significant

S9 S9 S9 S9 S9

H2 H2 H2 H2 H2

S9 S9 S9

Group DJ DJ

C5

H2 H2 H2

DJ DJ

C5

H2

DJ

CI nCI

N % N %

Total

CI

nCI

16 84.21 3 15.79

3 15.79 16 84.21

19 100 19 100

Note: Thirty one (84.21%) of the 38 subjects were correctly classified.

S9 S9 S9

Note: VLPF = ventrolateral prefrontal area, IFG = inferior frontal gyrus, MFG = middle frontal gyrus, IPL = inferior parietal lobule.

(Brody et al., 2001; Le'vesque et al., 2003). Hooker and Knight (2006) suggested that VLPF facilitates goal-oriented behavior by inhibiting the effect of emotional information. In this experiment, the subjects of the CI group were instructed to perform the task calmly so as not to disclose concealed information. Thus, VLPF might be involved in inhibition of processing of emotionally significant stimuli (concealed information). Inhibition of processing of concealed information is thought to be one of the multiple components for successful deception. For example, Sodian and Frith, (1992) reported that children with autism are unable to inhibit concealed information, so they fail to tell a lie. Another explanation for the activation of this area is that it is related to autonomic nervous system responses. This activated area partially includes the anterior insula, which was found to be related to galvanic skin conductance responses (Critchley et al., 2000; Gamer et al., 2007). We need to carry out further studies using the simultaneous recording of central and autonomic nervous system activities to examine the relationship between these activities. The percent signal change in the right MFG increased only in response to the critical (C5) in the CI group; however, this area does not largely contribute to the correct classification of the subjects into their assigned groups. Although the cortical activity in response to the critical (C5) was larger than those in response to all of the standard stimuli in VLPF, it was only larger than those in response to two standard stimuli (C4 and S9) in this area. Moreover, the responses to

Fig. 3. Results of discriminant analysis of the right VLPF data. The dots represent standardized percent signal changes of each subject in response to the critical (C5) in the right VLPF. The dotted line is the criterion for the discrimination (Canonical coefficient, 0.72; Eigen value, 1.06; Wilks' Lambda, 0.49, p b 0.001).

the critical stimulus in the CI and nCI groups were not significantly different. Thus, the activation of this area is not useful for determining whether the subject conceals information. Increased activities in response to DJ were observed in the right VLPF (BA 47) and left IFG (BA 44) in the CI group but not in the nCI group. In the CI group, responses of other areas to DJ also tend to be large. Thus, there was a possibility that DJ has some intrinsic salience for the CI group. Activation of the anterior cingulate gyrus, which was reported in previous studies (Spence et al., 2001; Langleben et al., 2002; Ganis et al., 2003; Kozel et al., 2005; Abe et al., 2006; Mohamed et al., 2006), was not found in this study. Langleben et al. (2002) used the guilty knowledge paradigm using playing cards, and reported that the anterior cingulate gyrus was activated when the subject responded deceptively. The task used in their experiment was similar to that used in the present study, except for the deceptive responses. The activities in the anterior cingulate gyrus are likely to be involved in functions related to deceptive responses, such as conflict between truthful responses and deceptive responses, or inhibition of truthful responses (Langleben et al., 2002). We also analyzed cortical areas which showed decreased activity during processing of concealed information, and found that some cortical area such as the left precentral gyrus, the bilateral precuneus, and the right cerebellum, showed negative activations. We did not use these areas in discriminant analysis because of the difficulties in interpreting the negative activations. Responses to target stimuli The target (D8) activated several cortical areas more than the standard (C4, S9, H2, and DJ). The commonly activated areas of both groups were the bilateral IFGs, anterior cingulate gyri (BA 24), IPLs (BA 40), basal ganglia, thalami, and the right STG (BA 22). IPLs were consistently activated in previous fMRI studies using the oddball tasks regardless of the stimulation and response modalities (McCarthy et al., 1997; Menon et al., 1997; Yoshiura et al., 1999; Linden et al., 1999; Stevens et al., 2000; Ardekani et al., 2002). This area may play an important role in target detection. The comparison of “target N critical” also yielded a similar activation pattern in the nCI group; however, we found only a few activated areas in the CI group because of an increased activity in response to the critical (C5). These imply that the critical (C5) may incidentally activate specific cortical areas even though the subjects were not required to respond deceptively. Additionally, the percent signal changes for all stimuli in the CI group were larger than those in the nCI group in four of five areas. It is likely that having the concealed information also affected their arousal levels or motivational states, which enhanced general cortical activation. Group classification based on cortical activities We evaluated the activity patterns of five ROIs of each subject and attempted to judge whether the subject belonged to the CI group or the nCI group. Our results revealed that activations in the right VLPF contributed to the correct classification of the subjects into their assigned groups, and the percentages of correct classification based on the activations in this area were 84.21% of 19 subjects in the CI group

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and 84.21% of 19 subjects in the nCI group (total percentage: 84.21%). Regarding the polygraph test, Ben-Shakhar and Furedy (1990) reviewed the results of GKT experiments and reported that 83.9% of the guilty subjects and 94.2% of the innocent subjects (total percentage: 89.1%) were correctly classified. Elaad (1998) also reviewed the results of mock crime GKT studies of the polygraph test, and estimated the accuracy rates of judgment as 80.6% for guilty subjects and 95.9% for innocent subjects (total percentage: 88.25%). As compared with these reports, the percentages of correct classification based on the activity pattern of the right VLPF in this study seemed to be slightly low. Acknowledgments This work was supported by a matching fund subsidy from MEXT: Academic Frontier Project for Private Universities, “Brain Mechanisms for Cognition, Memory and Behavior” at Nihon University, and also by a grant for the Joint Research Program of Bunkyo Gakuin University. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.neuroimage.2008.11.002. References Abe, N., Suzuki, M., Tsukiura, T., Mori, E., Yamaguchi, K., Itoh, M., Fujii, T., 2006. Dissociable roles of prefrontal and anterior cingulate cortices in deception. Cereb. Cortex 16, 192–199. Ardekani, B.A., Choi, S.J., Hossein-Zadeh, G.A., Porjesz, B., Tanabe, J.L., Lim, K.O., Bilder, R., Helpern, J.A., Begleiter, H., 2002. Functional magnetic resonance imaging of brain activity in the visual oddball task. Brain Res. Cogn. Brain Res. 14, 347–356. Ben-Shakhar, G., Furedy, J.J., 1990. Theories and applications in the detection of deception: A psychophysiological and international perspective. Springer, New York. Brody, A.L., Barsom, M.W., Bota, R.G., Saxena, S., 2001. Prefrontal- subcortical and limbic circuit mediation of major depressive disorder. Semin. Clin. Neuropsychiatry 6, 102–112. Critchley, H.D., Elliott, R., Mathias, C.J., Dolan, R.J., 2000. Neural activity relating to generation and representation of galvanic skin conductance responses: a functional magnetic resonance imaging study. J. Neurosci. 20, 3033–3040. Elaad, E., 1998. The challenge of the concealed knowledge polygraph test. Expert Evid. 6, 161–187. Elaad, E., Ben-Shakhar, G., 1989. Effects of motivation and verbal response type on psychophysiological detection of information. Psychophysiology 26, 442–451. Farwell, L.A., Donchin, E., 1991. The truth will out: Interrogative polygraphy (“lie detection”) with event-related brain potentials. Psychophysiology 28, 531–547. Furedy, J.J., Ben-Shakhar, G., 1991. The role of deception, intension to deceive, and motivation to avoid detection in the psychophysiological detection of guilty knowledge. Psychophysiology 28, 163–171. Gamer, M., Bauermann, T., Stoeter, P., Vossel, G., 2007. Covariations among fMRI, skin conductance, and behavioral data during processing of concealed information. Hum. Brain Mapp. 28, 1287–1301. Ganis, G., Kosslyn, S.M., Stose, S., Thompson, W.L., Yurgelun-Todd, D.A., 2003. Neural correlates of different types of deception: an fMRI investigation. Cereb. Cortex 13, 830–836. Hooker, C.I., Knight, R.T., 2006. The role of lateral orbitofrontal cortex in the inhibitory control of emotion. In: Zald, D.H., Rauch, S.L. (Eds.), The orbitofrontal cortex. Oxford University Press, Oxford, pp. 307–324.

Kozel, F.A., Padgett, T.M., George, M.S., 2004a. A replication study of the neural correlates of deception. Behav. Neurosci. 118, 852–856. Kozel, F.A., Revell, L.J., Lorberbaum, J.P., Shastri, A., Elhai, J.D., Horner, M.D., Smith, A., Nahas, Z., Bohning, D.E., George, M.S., 2004b. A pilot study of functional magnetic resonance imaging brain correlates of deception in healthy young men. J. Neuropsychiatry Clin. Neurosci. 16, 295–305. Kozel, F.A., Johnson, K.A., Mu, Q., Grenesko, E.L., Laken, S.J., George, M.S., 2005. Detecting deception using functional magnetic resonance imaging. Biol. Psychiatry 58, 605–613. Kugelmass, S., Lieblich, I., Bergman, Z., 1967. The role of “lying” in psychophysiological detection. Psychophysiology 3, 312–315. Langleben, D.D., Schroeder, L., Maldjian, J.A., Gur, R.C., McDonald, S., Ragland, J.D., O'Brien, C.P., Childress, A.R., 2002. Brain activity during simulated deception: an event-related functional magnetic resonance study. NeuroImage 15, 727–732. Le'vesque, J., Eug, ene, F., Joanette, Y., Paquette, V., Mensour, B., Beaudoin, G., Leroux, J-M., Bourgouin, P., Beauregard, M., 2003. Neural circuitry underlying voluntary suppression of sadness. Biol. Psychiatry 53, 502–510. Lee, T.M., Liu, H.L., Tan, L.H., Chan, C.C., Mahankali, S., Feng, C.M., Hou, J., Fox, P.T., Gao, J.H., 2002. Lie detection by functional magnetic resonance imaging. Hum. Brain Mapp. 15, 157–164. Linden, D.E.J., Prvulovic, D., Formisano, E., Völlinger, M., Zanella, F.E., Goebel, R., Dierks, T., 1999. The functional neuroanatomy of target detection: an fMRI study of visual and auditory oddball tasks. Cereb. Cortex 9, 815–823. McCarthy, G., Luby, M., Gore, J., Goldman-Rakic, P., 1997. Infrequent events transiently activate human prefrontal and parietal cortex as measured by functional MRI. J. Neurophysiol. 77, 1630–1634. Menon, V., Ford, J.M., Lim, K.O., Glover, G.H., Pfefferbaum, A., 1997. Combined eventrelated fMRI and EEG evidence for temporal-parietal cortex activation during target detection. NeuroReport 8, 3029–3037. Mohamed, F.B., Faro, S.H., Gordon, N.J., Platek, S.M., Ahmad, H., Williams, J.M., 2006. Brain mapping of deception and truth telling about an ecologically valid situation: functional MR imaging and polygraph investigation — initial experience. Radiology 238, 679–688. Nuñez, J.M., Casey, B.J., Egner, T., Hare, T., Hirsch, J., 2005. Intentional false responding shares neural substrates with response conflict and cognitive control. Neuroimage 25, 267–277. O'Doherty, J., Kringelbach, M.L., Rolls, E.T., Hornak, J., Andrews, C., 2001. Abstract reward and punishment representations in the human orbitofrontal cortex. Nat. Neurosci. 4, 95–102. Phan, K.L., Magalhaes, A., Ziemlewicz, T.J., Fitzgerald, D.A., Green, C., Smith, W., 2005. Neural correlates of telling lies: a functional magnetic resonance imaging study at 4 Tesla. Acad. Radiol. 12, 164–172. Rosenfeld, J.P., Angell, A., Johnson, M., Qian, J., 1991. An ERP-based, control-question lie detector analog: algorithms for discriminating effects within individuals' average waveforms. Psychophysiology 28, 319–335. Sodian, B., Frith, U., 1992. Deception and sabotage in autistic, retarded and normal children. J. Child Psychol. Psychiatry 33, 591–605. Spence, S.A., Farrow, T.F., Herford, A.E., Wilkinson, I.D., Zheng, Y., Woodruff, P.W., 2001. Behavioral and functional anatomical correlates of deception in humans. NeuroReport 12, 2849–2853. Spence, S.A., Hunter, M.D., Farrow, T.F., Green, R.D., Leung, D.H., Hughes, C.J., Ganesan, V., 2004. A cognitive neurobiological account of deception: evidence from functional neuroimaging. Philos. Trans. R. Soc. Lond., B. Biol. Sci. 359, 1755–1762. Spence, S.A., Kaylor-Hughes, C., Farrow, T.F.D., Wilkinson, I.D., 2008. Speaking of secrets and lies: the contribution of ventrolateral prefrontal cortex to vocal deception. NeuroImage 40, 1411–1418. Sprengelmeyer, R., Rausch, M., Eysel, U.T., Przuntek, H., 1998. Neural structures associated with recognition of facial expressions of basic emotions. Proc. Biol. Sci. 265, 1927–1931. Stevens, A.A., Skudlarski, P., Gatenby, J.C., Gore, J.C., 2000. Event-related fMRI of auditory and visual oddball tasks. Magn. Reson. Imaging 18, 495–502. Talairach, J., Tournoux, P., 1988. Co-Planar Stereotaxic Atlas of the Human Brain. Thieme, Stuttgart. Yoshiura, T., Zhong, J., Shibata, D.K., Kwok, W.E., Shrier, D.A., Numaguchi, Y., 1999. Functional MRI study of auditory and visual oddball tasks. NeuroReport 10, 1683–1688.