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In addition, they must monitor their own behaviour during the conversation so that they do not give away their lies via nonverbal cues, whilst monitoring the reactions of the lie detector so that they can adapt their response strategy if their current strategy raises suspicion ( 3) However, in daily life conversations it is often seen as inappropriate, strange or impolite if the listener asks further questions Conversation partners will probably not appreciate utterances such as Could you elaborate on that , Could you back this up with evidence , Could you repeat what you just said and may object to it Also, it would bene t the lie detector if he or she examined the speaker s movements because they may reveal signs of deceit, but this would be considered inappropriate in daily life situations.

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Conversation rules dictate that a listener looks the speaker into the eyes, yet the eyes generally do not reveal reliable information about deception ( 3) Therefore, the two conversational rules of (i) not asking further questions and (ii) looking someone into the eyes hamper lie detection and make it a dif cult task (8) Good Liars The nal reason that makes lie detection dif cult is that some people are very good liars Surprisingly, there is little research regarding what makes someone a good liar, but I believe that three criteria are relevant (see also Vrij, Granhag, & Mann, in press) Good liars are those people: (i) whose natural behaviour disarms suspicion; (ii) who do not nd it cognitively dif cult to lie; and (iii) who do not experience emotions such as fear, guilt, or duping delight when they are lying (s 3, 5 and 6).

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Accuracy of judgments of deception when an interview is watched, heard, and read Personnel Psychology, 21, 23 30 Mak, E G, Y, & Lee, T M C (2006) Detection of feigned memory impairments using a Chinese word task Psychological Reports, 98, 779 788 Malcolm, S R, & Keenan, J P (2003) My right I: Deception detection and hemispheric differences in self-awareness Social Behavior and Personality, 31, 767 772 Malcolm, S R, & Keenan, J P (2005) Hemispheric asymmetry and deception detection Laterality, 10, 103 110..

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in the studies conducted to date, participants found it mentally more dif cult to lie than to tell the truth. Despite some similarities in the ndings between the different studies there were considerable differences. In each study a somewhat different brain activity pattern emerged as an indicator of deceit, which indicates that a pattern uniquely related to deception does not exist in the brain (Abe et al., 2006). This is further emphasised by Ganis et al. s (2003) study that revealed that telling spontaneous lies resulted in different brain structure and area activity than telling rehearsed lies. Moreover, issues such as whether someone feels strongly about the issue under investigation and the stakes of getting caught, in uence brain structure and area activity (Ganis et al., 2003). In other words, their study found that people s brain activity when lying depends on the situation (so-called intrapersonal differences, see previous chapters). Kozel and colleagues (2004a,b) further reported that in the same lie detection experiment different individuals showed somewhat different brain activity patterns (so-called interpersonal differences, see previous chapters). In three studies it was reported the extent to which truths and lies could be correctly classi ed on the basis of brain structure and area activity (Davatzikos et al., 2005; Kozel et al., 2005; Langleben et al., 2005). The accuracy rates ranged from 78% (Langleben et al., 2005) to 93% (Kozel et al., 2005). Both Langleben and Kozel have subsequently applied to patent their fMRI-based lie detection instrument and are seeking to commercialise it (Happel, 2005). Researchers from the Langleben group have also announced that brain imaging is ready to detect terrorists (Wild, 2005).

I think that these three criteria include eight characteristics: (i).

where checking the last inequality is an elementary computation. A similar argument applies to P(h( ) < u ). This proves (2.21) and nishes the proof of the theorem. Let us now turn to the second general inequality. Theorem 2.9. Assume that the process X satis es the same hypotheses as in Theorem 2.8. Then: 1. E (|MT |) < . 2. For every u > 0, the inequality

Allison, P. D. (1990). Change scores as dependent variables in regression analysis. Survey Methodology, 20, 93 114. Angrist, J. D. (2004). American education research changes tack. Oxford Review of Economic Policy, 20, 198 212. Bonate, P. L. (2000). Analysis of Pretest Posttest Designs. Boca Raton: Chapman & Hall/CRC.

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