Dishonest behavior is a phenomenon 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 those we care about, or to influence other individuals (DePaulo et al., 2003; Ennis, Vrij, & Chance, 2008). However, dishonesty also belongs to some of the greatest personal and social challenges of our time. We encounter harmful dishonest behavior in academia, sports and politics among others. Even the most ordinary forms of dishonest behavior cause serious damage to society. For example, tax avoidance costs global economies billions of dollars each year (Cobham & Jansky, 2017). Due to the high prevalence and high costs, it is extremely important to investigate which neurocognitive processes determine whether we behave unethically or not and how this behavior can be prevented. 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 Shouldn't Be Banned"? Get an Original EssayResearch Investigating DishonestyNeuroimaging studies have used many different experimental protocols to investigate dishonest behavior. Most of them are variations of deception differentiation or covert information paradigms (Giorgio Ganis & Keenan, 2009). Hidden information paradigms rely on signatures to distinguish between truthful answers and lies. For example, in the Guilty Knowledge Test (GKT) used by Langleben et al. (2002) participants were given a playing card before entering the MR scanner. They were asked to always deny possessing 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 previously received card, participants show signs of recognition, even if they lie and deny having it. In contrast, participants who were not given any of the cards would respond the same way to all cards shown, since all cards were equally unknown to them. In this paradigm, however, dishonest responding is confused with recognition memory. On the other hand, the differentiation of deception paradigms, such as instructed lying paradigms, compares conditions that differ in the response that must be given. In these paradigms, participants are tricked into answering questions truthfully or dishonestly. Comparing these conditions indicates the unique neural processes involved in dishonest responding, compared to truthful responding (Spence et al., 2008). However, since dishonest behavior is a social phenomenon, studies have started to investigate 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 had to make a promise at the beginning of the experiment indicating how great the possibility was of being able to trust and sharing the money that could be earned . An interaction partner was then informed of this promise and was able to decide whether to trust the participant and invest money or not to trust him and keep an initial endowment of monetary units for himself. If the interaction partner trusted the participant, the experimenter collected the amount of money invested by the interaction partner. The participant might then decide to be honestand keep the promise or decide to break the promise by not returning the money. Creating these types of paradigms allows researchers to investigate dishonest behavior in a more real-world context. fMRI Research Results 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, Thompson, & Yurgelun-Todd, 2003; Gombos, 2006; Hughes et al., 2005; As a matter of fact, subregions of the frontal executive system have been found to play an important role in a variety of cognitive domains that are thought to be relevant to dishonest behavior. For example, the dorsolateral prefrontal cortex (dlPFC) is important for response selection, cognitive control, monitoring, and manipulation within working memory (MacDonald, Cohen, Stenger, & Carter, 2000; Owen et al., 1999; Rowe, Toni, Josephs, Frackowiak, & Passingham, 2000). Furthermore, the ventrolateral prefrontal cortex (vlPFC) has been found to be implicated in task switching and response inhibition (Chikazoe, Konishi, Asari, Jimura, & Miyashita, 2007; Dove, Pollmann, Schubert, Wiggins, & Yves Von Cramon, 2000). . Furthermore, the anterior cingulate cortex (ACC) has been implicated in processes such as conflict detection and emotional processing ( Kerns et al., 2004 ; Murphy, Nimmo-Smith, & Lawrence, 2003 ). Since a dishonest act involves the need to inhibit truthful responses (BlandГyn-Gitlin, Fenn, Masip, & Yoo, 2014), the identification of a conflict between competing response tendencies, and the execution of a controlled dishonest response (Walczyk, Harris, Duck, & Mulay, 2014), it is not surprising that these regions may be associated with dishonest behavior. And indeed, 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, greater activation of the dlPFC has been associated with the control of increased working memory load through the tendency to simultaneously receive a truthful response and a dishonest response ( Reuter-Lorenz et al., 2000 ). Conflict detection and emotional processing processes have been found to correlate with 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, Egner, Hare, & Hirsch, 2005; deep brain structures such as the amygdala and ventral striatum. During dishonest acts, cognitive processes of reward seeking and emotional regulation have been associated with activity in these structures (Nobuhito Abe, Suzuki, Mori, Itoh, & Fujii, 2007; Baumgartner , Fischbacher, Feierabend, Lutz, & Fehr, 2009). Therefore, it seems reasonable to state that during an act of dishonest behavior, the prefrontal cortex interacts with the subcortical areas to achieve the intended goal (Nobuhito Abe, 2011). on EEG So far, most EEG research has investigated the spatiotemporal pattern of neural activity during dishonest responses using event-related potentials (ERPs). The P300 component has been extensively studied and successfully used for lie detection (Yue, 2014). Numerous studies have shown that dishonesty is related to the decrease in P3 components, which is assigned to the effect of increased task demandsin deception (Hu, Wu, & Fu, 2011; Johnson, Barnhardt, & Zhu, 2003; Miller, Rosenfeld, Soskins, & Jhee, 2002; Proverbio, Vanutelli, & Adorni, 2013; Alongside the P3 component, Hu et al. (2011 ) found that deception is associated with an increase in N1 and N2 components suggests that these findings reflect increased attention to stimuli, conflict detection, and response monitoring processes (Hu et al., 2011).Deception was also found to be associated with a higher N400 component, reflecting the conflict resolution process (Proverbio et al., 2013). Furthermore, a greater contingent negative variation (CNV) was found. for lies compared to truthful responses (Fang, Liu, & Shen, 2003; S.-Y. Sun, Mai, Liu, Liu, & Luo, 2011). it has been interpreted either as a greater motivation necessary to lie or as an additional motor preparation necessary to inhibit the truthful response (Fang et al., 2003). Another component, medial frontal negativity (MFN), was 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 reduced late positive parietal component (LPC) in deception. They proposed that this effect was due to the dual-task nature of deception. In subsequent studies, they found that positive pre-response potential (PRP) was also reduced during deception compared to truth-telling and this was thought to reflect strategic monitoring/conflict resolution prior to responding (Johnson et al., 2004; Johnson, Barnhardt, & Zhu, 2005). Alongside 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 deceptive responding was overall larger than the alpha ERD during truthful responding. It appears that increased cognitive effort during deception generated a larger alpha ERD. In summary, almost all of these studies are in line with the cognitive load hypothesis of deception (Vrij, Fisher, Mann, & Leal, 2006), according to which lying involves the intentional suppression of truthful responses and therefore activates the executive system frontal (Cristo et al., 2009) and conflict monitoring in brain areas (Nobuhito Abe, 2011). Limitations of Research Investigating Dishonesty Despite numerous studies investigating dishonest behavior, ecological validity is lacking in research on moral decision making. Many studies have used instructed lying paradigms and consequently the lying observed in these studies is different from more spontaneous forms of lying in that it does not involve a voluntary intention to lie. Furthermore, participants are not as motivated to behave dishonestly in instructed lying experiments compared to real-world situations, where 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). Next, the studies they useinstructed lying paradigms have examined cognitive conflict related to deception; inhibit the truth to produce lies, but not moral ones; choosing self-interest and therefore sacrificing honesty (Panasiti et al., 2014). As a result, studies began 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 scenario lies recruit only the right anterior middle frontal gyrus (Giorgi Ganis et al., 2003). Similarly, Yin, et al. (2016) found that in addition to the patterns shared with instructed lying, there are some activation patterns sensitive to spontaneous deception. In this regard, simulated dishonesty in laboratory experiments cannot be considered equivalent to dishonesty in laboratory experiments 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, & Chan, 2015; advantage of these paradigms is that participants themselves decide whether to behave unethically or not, which also captures moral conflict. However, the results of these studies are mixed and further research is needed. At the same time, when examining research on moral decision making, an important distinction should be made between deception and cheating behavior. Deceptive behavior requires an interaction partner direct and occurs in a social context (Zuckerman, Depaulo, & Rosenthal, 1981). It also requires a thoughtful decision to deceive the interaction partner. In contrast, cheating behavior does not require direct interaction with the 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. So far, most neuroimaging research has focused on deception, and almost no research has been conducted on cheating behavior. This is surprising, because more costly forms of dishonest behavior, such as tax avoidance, are labeled as fraud rather than deception. Because the constructs of deception and cheating share neural processes, research on deception can be used for insights into cheating, however, the less interactive form of dishonest behavior should be studied in more depth. Current Study Therefore, in the present study individual differences in cheating behavior will be analyzed and explored using a new behavioral paradigm. Previous research has shown that individuals differ substantially in the frequency with which they engage in cheating behaviors (Gino & Ariely, 2012; Gino & Wiltermuth, 2014). These individual differences may be associated with certain personality traits and characteristics. It has been proposed that greedy individuals may require stronger self-control processes when resisting the temptation to cheat, whereas less greedy individuals may not even be tempted to cheat (N. Abe & Greene, 2014). Furthermore, Gino and Ariely (2012) proposed that a creative personality promotes justifying behavior, which often leads to unethical behavior. Additionally, it has been proposed that narcissists are more susceptible to unethical behavior. This is suggested.