Dishonest behavior is a phenomenon that we often encounter in our daily lives. It is used in social situations to achieve goals such as making a good impression, supporting and protecting people we care about, or to influence other individuals (DePaulo et al., 2003; Ennis, Vrij, & Chance, 2008). However, dishonesty is also among the greatest personal and societal challenges of our time. We face harmful dishonest behavior in, among other places, academia, sports and politics. Even the most ordinary dishonest behavior causes serious harm to society. For example, tax evasion costs global economies billions of dollars each year (Cobham & Jansky, 2017). Due to the prevalence and high costs, it is extremely relevant to study which neurocognitive processes determine whether we behave unethically or unethically, and how this behavior can be avoided. Examining these processes has important implications for the study of ethics, psychology, neuroscience, and law, but also has more practical implications such as creating interventions to promote more honest behavior . Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”?Get the original essayDishonesty ResearchNeuroimaging studies have used many different experimental protocols to study dishonest behavior. Most of them are variants of deception differentiation or information concealment paradigms (Giorgio Ganis & Keenan, 2009). Concealed information paradigms rely on recognition cues to differentiate truthful responses from lies. For example, in the Guilty Knowledge Test (GKT) used by Langleben et al. (2002), participants were given a playing card before going to the MRI scanner. They were asked to always deny that they had the card. While in the scanner, participants were shown a series of playing cards and asked whether or not they owned each card. The paradigm is based on the fact that when shown the card they previously received, participants show signs of recognition, even if they lie and deny having it. In contrast, participants who did not receive any of the cards would react the same way to all cards presented, since all cards were equally unfamiliar to them. However, in this paradigm, the dishonest response is confused with recognition memory. On the other hand, differentiating deception paradigms, such as ordered lying paradigms, compare conditions that differ in the response to be made. In these paradigms, participants are asked to answer questions honestly or dishonestly. Comparing these conditions, the unique neural processes engaged in dishonest responses, versus a truthful response, are indicated (Spence et al., 2008). However, because dishonest behavior is a social phenomenon, studies have begun to study it in a more natural way, with (hypothetical) interaction partners. For example, in the trust game paradigm used by Baumgartner, Gianotti, and Knoch (2013), participants were asked to make a promise at the beginning of the experiment indicating the magnitude of the possibility that they could be trusted and that they would share any money that might be entrusted to them. be won. An interaction partner was then informed of this promise and could decide to trust the participant and invest money or not to trust him and maintain ainitial endowment of monetary units for itself. If the interaction partner trusted the participant, the experimenter increased the amount of money invested by the interaction partner. The participant could then decide to be honest and keep their promise or break their promise by not returning money. Creating these types of paradigms allows researchers to study dishonest behavior in a more real-world context. fMRI Research Findings Despite the different experimental protocols used, previous neuroimaging research has consistently shown that the frontal executive system is associated with dishonest behavior (Nobuhito Abe, 2009; Christ, Van Essen, Watson, Brubaker, & McDermott, 2009 ; Giorgi Ganis, Kosslyn, Stose, and Yurgelun-Todd, 2003; In fact, subregions of the frontal executive system have been found to play important roles in various cognitive domains thought to be related to dishonest behavior. For example, the dorsolateral prefrontal cortex (dlPFC) is important for response selection, cognitive control, and monitoring and manipulation within working memory (MacDonald, Cohen, Stenger, & Carter, 2000; Owen et al ., 1999; Rowe, Toni, Josephs, Frackowiak and Passingham, 2000). Additionally, the ventrolateral prefrontal cortex (vlPFC) has been shown to be involved in task switching and response inhibition (Chikazoe, Konishi, Asari, Jimura, & Miyashita, 2007; Dove, Pollmann, Schubert, Wiggins, & Yves Von Cramon, 2000). . Additionally, the anterior cingulate cortex (ACC) has been implicated in processes such as conflict detection and emotion processing (Kerns et al., 2004; Murphy, Nimmo-Smith, & Lawrence, 2003). Since a dishonest act involves the need to inhibit truthful responses (Blandín-Gitlin, Fenn, Masip, & Yoo, 2014), detecting a conflict between competing response tendencies and executing a controlled dishonest response (Walczyk, Harris, Duck, & Mulay, 2014), it is not surprising that these regions can be associated with dishonest behavior. And indeed, the dlPFC, vlPFC, medial frontal cortex, and posterior parietal cortex are activated during the process of inhibiting truthful responses during a dishonest act (ten Brinke, Lee, & Carney, 2015). Furthermore, increased dlPFC activation has been associated with controlling increased working memory load through the simultaneous tendency toward truthful and dishonest responding ( Reuter-Lorenz et al., 2000 ). Conflict detection and emotion processing processes have been found to be linked to activity in the lPFC, anterior insula, and ACC (Bolin, 2004; Christ et al., 2009; F. Andrew Kozel et al., 2005; MacDonald et al., 2000; Nuñez, Casey, Egner, Hare, & Hirsch, 2005; , it is presumed that deep brain structures such as the amygdala and ventral striatum are also involved. During dishonest acts, the cognitive processes of reward seeking and emotional regulation have been associated with the activity of these structures (. Nobuhito Abe, Suzuki, Mori, Itoh, & Fujii, 2007; Baumgartner, Fischbacher, Feierabend, Lutz, & Fehr, 2009). Therefore, it seems reasonable to assert that during an act of dishonest behavior, the prefrontal cortex interacts. with subcortical areas to achieve the intended goal (Nobuhito Abe, 2011). EEG Research Results Until now, most EEG research has studied the spatio-temporal evolution of neuronal activity during responses dishonest using event-related potentials (ERPs). THEP300 component has been widely studied and successfully used for lie detection (Yue, 2014). Many studies have shown that dishonesty is correlated with a decrease in P3 components, attributed to the effect of increased task demands on deception (Hu, Wu, & Fu, 2011; Johnson, Barnhardt, & Zhu, 2003; Miller, Rosenfeld, Soskins, & Jhee, 2002; In addition to the P3 component, Hu et al. (2011) found that deception is associated with an increase in N1 and N2 components. It is suggested that these results reflect increased attention to stimuli, the conflict detection process, and response monitoring processes (Hu et al., 2011). Deception has also been found to be associated with a higher N400 component, reflecting the conflict resolution process (Proverbio et al., 2013). Additionally, increased contingent negative variation (CNV) was found for lies compared to truthful responses (Fang, Liu, & Shen, 2003; S.-Y. Sun, Mai, Liu, Liu, & Luo, 2011). CNV is observed in the preparation of a response and this increased component resulting from lying has been interpreted either as greater motivation needed to lie or as additional motor preparation needed to inhibit the truthful response (Fang et al., 2003 ). Another component, medial frontal negativity (MFN), was found to be more negative after a deceptive response than after a truthful response. This effect has been proposed to reflect response monitoring and conflict detection processes (Johnson, Barnhardt, & Zhu, 2004; Johnson, Henkell, Simon, & Zhu, 2008; Yeung & Cohen, 2006). Johnson et al. (2003) found a reduction in the parietal late positive component (LPC) in deception. They proposed that this effect was due to a dual task of deception. In later studies, they found that positive pre-response potential (PRP) was also reduced during deception compared to truth-telling, which was thought to reflect strategic monitoring/conflict resolution before the answer (Johnson et al., 2004; Johnson, Barnhardt and Zhu, 2005). Next to ERP studies, Kim et al. (2012) examined differences in cortical activation patterns due to different levels of cognitive demands between deceptive and truthful responses. They assessed cortical activity using event-related desynchronization (ERD) in the alpha frequency band. ERD models are influenced by the level of complexity associated with information processing (Fink, Grabner, Neuper, & Neubauer, 2005; Krause et al., 2000). They found that the alpha ERD during a deceptive response was generally larger than the alpha ERD during a truthful response. It appears that increased cognitive effort during deception generated greater alpha ERD. In summary, almost all of these studies are consistent with the cognitive load hypothesis of deception (Vrij, Fisher, Mann, & Leal, 2006), according to which lying involves the intentional suppression of truthful responses and thus activates the frontal executive system ( Christ et al., 2009) and conflict monitoring brain areas (Nobuhito Abe, 2011). Limitations of Research on Dishonesty Despite the numerous studies examining dishonest behavior, the ecological validity of research on moral decision making is lacking. Many studies have used ordered lying paradigms and, therefore, the lying observed in these studies is different from more spontaneous forms of lying because it does not involve the voluntary intention to lie. Furthermore, participants were not as motivated to behave dishonestly during ordered lying experiments as in situations of thereal world, in which dishonesty is more of an impulsive and context-dependent act (Giorgio Ganis & Keenan, 2009). In the absence of voluntary intention and motivation, the complex executive functions associated with dishonesty may not be fully investigated (Sip, Roepstorff, McGregor, & Frith, 2008). Subsequently, studies using ordered lying paradigms have examined cognitive conflict related to deception; prevent the truth from producing lies, but not the moral lie; choosing self-interest and thus sacrificing honesty (Panasiti et al., 2014). As a result, studies have begun to compare different types of lies and found that the neural regions and processes involved depend on the type of lie. Regions such as the ACC, precentral gyrus, and cuneus appear to be involved in spontaneous lying. In contrast, memorized script lies recruit only the right anterior middle frontal gyrus (Giorgi Ganis et al., 2003). Similarly, Yin et al. (2016) found that in addition to patterns shared with ordered lying, there are certain activation patterns sensitive to spontaneous deception. In this regard, simulated dishonesty in laboratory experiments cannot be considered to be the same as dishonesty in real-world situations. In this regard, more recent studies have created new paradigms to study the neural mechanisms of dishonesty in a more natural way. In these new paradigms, participants are tempted to behave dishonestly in exchange for monetary rewards (N. Abe & Greene, 2014; Baumgartner et al., 2009, 2013; Bhatt, Lohrenz, Camerer, & Montague, 2010; Greene & Paxton, 2009). ; Sip et al., 2010, 2012; D. Sun, Lee and Chan, 2015; The advantage of these paradigms is that the participants themselves decide whether to behave unethically or not, which also reflects the moral conflict. However, the results of these studies are mixed and further research is needed. At the same time, when reviewing research on moral decision making, an important distinction must be made between deception and cheating behavior. Deceptive behavior requires a direct interaction partner and occurs in a social setting (Zuckerman, Depaulo, & Rosenthal, 1981). It also requires a considered decision to deceive the interaction partner. In contrast, cheating behavior does not require direct interaction with a partner and is therefore less interactive and less social. Since there is a difference between the concepts of deception and cheating behavior, the underlying neural mechanisms involved may also be different. To date, most neuroimaging research has focused on deception, and almost no research has been conducted on cheating behaviors. This is surprising because the most costly forms of dishonest behavior, such as tax evasion, are characterized as cheating rather than deception. Because the concepts of deception and cheating share neural processes, research on deception can be used to better understand cheating. However, the less interactive form of dishonest behavior should be studied more thoroughly. Therefore, in the present study, individual differences in cheating behavior will be explored using a novel behavioral paradigm. Previous research has shown that individuals differ significantly in the frequency with which they engage in cheating behavior (Gino and Ariely, 2012; Gino and Wiltermuth, 2014). These individual differences may be associated with certain traits and.