An Automatic Lie Detection Model Using EEG Signals Based on the Combination of Type 2 Fuzzy Sets and Deep Graph Convolutional Networks.

In recent decades, many different governmental and nongovernmental organizations have used lie detection for various purposes, including ensuring the honesty of criminal confessions. As a result, this diagnosis is evaluated with a polygraph machine. However, the polygraph instrument has limitations and needs to be more reliable. This study introduces a new model for detecting lies using electroencephalogram (EEG) signals. An EEG database of 20 study participants was created to accomplish this goal. This study also used a six-layer graph convolutional network and type 2 fuzzy (TF-2) sets for feature selection/extraction and automatic classification. The classification results show that the proposed deep model effectively distinguishes between truths and lies. As a result, even in a noisy environment (SNR = 0 dB), the classification accuracy remains above 90%. The proposed strategy outperforms current research and algorithms. Its superior performance makes it suitable for a wide range of practical applications.

Detecting lies in investigative interviews through the analysis of response latencies and error rates to unexpected questions.

In this study, we propose an approach to detect deception during investigative interviews by integrating response latency and error analysis with the unexpected question technique. Sixty participants were assigned to an honest (n = 30) or deceptive group (n = 30). The deceptive group was instructed to memorize the false biographical details of a fictitious identity. Throughout the interviews, participants were presented with a randomized sequence of control, expected, and unexpected open-ended questions about identity. Responses were audio recorded for detailed examination. Our findings indicate that deceptive participants showed markedly longer latencies and higher error rates when answering expected (requiring deception) and unexpected questions (for which premeditated deception was not possible). Longer response latencies were also observed in participants attempting deception when answering control questions (which necessitated truthful answers). Moreover, a within-subject analysis highlighted that responding to unexpected questions significantly impaired individuals' performance compared to answering control and expected questions. Leveraging machine-learning algorithms, our approach attained a classification accuracy of 98% in distinguishing deceptive and honest participants. Additionally, a classification analysis on single response levels was conducted. Our findings underscore the effectiveness of merging response latency metrics and error rates with unexpected questioning as a robust method for identity deception detection in investigative interviews. We also discuss significant implications for enhancing interview strategies.

Psychology and the lie detector industry: A fifty-year perspective.

Fifty years ago, in a trenchant analysis that challenged applied lie detection theory and science, David Lykken (1974) brought polygraphic interrogation methods to the attention of academia with the hope that these techniques would come under the purview of psychology and psychophysiology. In this perspective, I examine how this application of psychophysiology has evolved over the last half century and how its status has changed for 1) the comparison (control) question test (CQT), used in forensic applications; 2) polygraph screening tests, used to evaluate examinee integrity; and 3) the concealed information technique (CIT), used to assess recognition memory of crime details. The criticisms of the CQT and screening tests advanced by Lykken have been amplified and focused by the academic community over the last half century. However, this has had little effect on how these methods are practiced and has not curtailed their use. Although most private sector employee screening tests are now prohibited, personnel screening of government employees has increased, and screening tests of sex offenders are now commonplace. Even though the CIT has captured the interest of psychophysiologists as a scientifically defensible technique, its field use is negligible. A primary purpose of polygraphic interrogations continues to be the extraction of admissions and confessions. The lack of change in the polygraph testing status quo stems in large part from unwavering government support for the use of these methods. As a result, polygraph theory and research support continues to rest on shaky ground while practice continues unfettered by valid criticism.

Detecting deception with artificial intelligence: promises and perils.

Rapid advancements in artificial intelligence (AI) have driven interest in its potential application for lie detection. Unfortunately, the current approaches have primarily focused on technical aspects at the expense of a solid methodological and theoretical foundation. We discuss the implications thereof and offer recommendations for the development and regulation of AI-based deception detection.

Unveiling the efficacy of the feedback concealed information test in collaborative crime detection.

Collaborative crime poses severe social hazards. In collaborative crime scenarios, previous studies have indicated that perpetrators' collaborative encoding can impair the detection efficiency of P300-based complex trial protocols due to the collaborative encoding deficit. The feedback concealed information test (fCIT), a unique variation of the concealed information test, provides participants with feedback on how well they conceal information from memory. The fCIT, which has proven to be highly efficient, detects concealed information using recognition P300 along with feedback-related event-related potentials, and reflects the subject's motivation to conceal. However, no studies have examined the fCIT's effectiveness in identifying collaborative criminals. We propose that the fCIT's efficiency persists in cases of collaborative crime and test this hypothesis using a sample of 48 participants. The participants in the collaborative groups were instructed to have hushed conversations about theft to simulate the collaborative crime process. Subsequently, they completed the fCIT. The findings indicate a significant decline in recognition P300's detection efficiency when participants committed crimes collaboratively. Nevertheless, the detection efficiency of feedback P300 and feedback-related negativity remained high. This study's outcomes illustrate the capacity of the fCIT to detect perpetrators involved in collaborative crime.

LieWaves: dataset for lie detection based on EEG signals and wavelets.

This study introduces an electroencephalography (EEG)-based dataset to analyze lie detection. Various analyses or detections can be performed using EEG signals. Lie detection using EEG data has recently become a significant topic. In every aspect of life, people find the need to tell lies to each other. While lies told daily may not have significant societal impacts, lie detection becomes crucial in legal, security, job interviews, or situations that could affect the community. This study aims to obtain EEG signals for lie detection, create a dataset, and analyze this dataset using signal processing techniques and deep learning methods. EEG signals were acquired from 27 individuals using a wearable EEG device called Emotiv Insight with 5 channels (AF3, T7, Pz, T8, AF4). Each person took part in two trials: one where they were honest and another where they were deceitful. During each experiment, participants evaluated beads they saw before the experiment and stole from them in front of a video clip. This study consisted of four stages. In the first stage, the LieWaves dataset was created with the EEG data obtained during these experiments. In the second stage, preprocessing was carried out. In this stage, the automatic and tunable artifact removal (ATAR) algorithm was applied to remove the artifacts from the EEG signals. Later, the overlapping sliding window (OSW) method was used for data augmentation. In the third stage, feature extraction was performed. To achieve this, EEG signals were analyzed by combining discrete wavelet transform (DWT) and fast Fourier transform (FFT) including statistical methods (SM). In the last stage, each obtained feature vector was classified separately using Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and CNNLSTM hybrid algorithms. At the study's conclusion, the most accurate result, achieving a 99.88% accuracy score, was produced using the LSTM and DWT techniques. With this study, a new data set was introduced to the literature, and it was aimed to eliminate the deficiencies in this field with this data set. Evaluation results obtained from the data set have shown that this data set can be effective in this field.

Exposing Suspects to Their Sketches in Repeated Interviews to Elicit Information and Veracity Cues / Exponiendo en entrevistas repetidas a los sospechosos a sus esquemas para obtener información e indicios de veracidad

Background/Aim: has shown that sketching while narrating facilitates the elicitation of information and verbal veracity cues in single interviews. We examined if these effects are retained when suspects are shown their sketch after one week in a repeated interview. Method: Participants (N = 173) completed a mock mission and then told the truth or lied about it in an immediate interview (interview 1). Participants either verbally reported the mission (Free recall condition) or sketched it while describing what they were sketching (sketch condition). After one week, all participants were asked for a free recall without sketching (interview 2). Half of the participants in the Sketch condition had access to their sketch while they verbally reported the event whereas the remaining half did not access the sketch. Results: Truth tellers provided more information than lie tellers in both interviews, and sketching elicited more information than a free recall but only in Interview 1. Participants who had access to their sketch in interview 2 repeated more information than those who did not have access, but accessing the sketch did not have an effect on veracity cues. Conclusions: Thus, sketching enhanced the elicitation of information in Interview 1 and access to the sketch in interview 2 seemed helpful for recalling previously reported information. (AU)

Antecedentes/objetivo: La investigación ha revelado que el uso de esquemas mientras se lleva a cabo una narración facilita la obtención de información y de indicios verbales de veracidad en una entrevista. Analizamos si estos efectos se mantienen cuando se somete a los sospechosos a su esquema de los hechos en entrevistas repetidas (una semana después). Método: Los participantes (N = 173) completaron una misión simulada y luego contaban la verdad o mentían sobre la misma en una entrevista realizada de modo inmediato (entrevista 1). Los participantes o bien referían verbalmente la misión (condición de recuerdo libre) o la esquematizaban (condición de esquematización). Después de una semana se pidió a todos los participantes un recuerdo libre sin esquematizar (entrevista 2). La mitad de los participantes de la condición de esquematización podían acceder a su esquema mientras referían verbalmente el suceso y la otra mitad no tenía acceso al esquema. Resultados: Los que contaban la verdad daban más información que los que mentían en ambas entrevistas y el esquema facilitaba más información que el recuerdo libre aunque tan solo en la entrevista 1. Aquellos participantes que tenían acceso a su esquema en la entrevista 2 repetían más información que quienes no tenían acceso, aunque el acceso no tenía efecto alguno en indicios de veracidad. Conclusiones: En conclusión, los esquemas incrementaron la obtención de información en la entrevista 1 y el acceso al esquema en la entrevista 2 resultó útil para recordar la información relatada previamente. (AU)

Combining the Devil's advocate approach and verifiability approach to assess veracity in opinion statements / Combinando los enfoques de abogado del diablo y verificabilidad para evaluar la veracidad de declaraciones basadas en opiniones

Aim: We examined the ability to detect lying about opinions with the Devil's Advocate Approach and Verifiability Approach. Method: Interviewees were first asked an opinion eliciting question to argue in favour of their alleged personal view. This was followed by a devil's advocate question to argue against their alleged personal view. Since reasons that support rather than oppose an opinion are more readily available in people's minds, we expected truth tellers' responses to the opinion eliciting question to include more information and to sound more plausible, immediate, direct, and clear than their responses to the devil's advocate question. In lie tellers these patterns were expected to be less pronounced. Interviewees were also asked to report sources that could be checked to verify their opinion. We expected truth tellers to report more verifiable sources than lie tellers. A total of 150 participants expressed their true or false opinions about a societal issue. Results: Supporting the hypothesis, the differences in plausibility, immediacy, directness, and clarity were more pronounced in truth tellers than in lie tellers (answers to eliciting opinion question sounded more plausible, immediate, direct, and clear than answers to the devil's advocate question). Verifiable sources yielded no effect. Conclusions: The Devil's Advocate Approach is a useful tool to detect lies about opinions. (AU)

Objetivos: El artículo analiza la capacidad para detectar el engaño en declaraciones de testigos basadas en opiniones con el enfoque del “abogado del diablo” y el de la verificabilidad. Método: A un grupo de entrevistados se le pidió que argumentaran a favor de su opinión personal. A un segundo grupo se le requirió que, haciendo de abogado del diablo, argumentaran en contra de su punto de vista personal. Dado que los argumentos favorables a la opinión personal son mentalmente más accesibles que los contrarios, esperábamos que las respuestas honestas de los testigos incluyeran más argumentos y resultaran más plausibles, inmediatas, directas y claras que las respuestas haciendo de abogado del diablo. Por su parte, en la condición de respuestas falsas esperábamos que estos patrones fueran menos pronunciados. Además, se solicitó a los entrevistados que informaran de los medios en los que podría verificarse su opinión. Esperábamos que los testigos de la condición de verdad aportaran más fuentes verificables que los de la condición de mentira. Participaron en el estudio un total de 150 sujetos que manifestaron su opinión verdadera o falsa sobre un tema de relevancia social. Resultados: Los resultados confirmaron la hipótesis planteada: los testigos honestos prestaron declaraciones más plausibles, inmediatas, directas y claras que los falsos (las respuestas de los entrevistados que argumentaron a favor de su opinión personal resultaron más plausibles, inmediatas, directas, y claras que las respuestas haciendo de abogado del diablo). Sin embargo, no se observaron efectos del factor testigo en las fuentes de verificación. Conclusiones: El enfoque de abogado del diablo es una herramienta útil para la detección de opiniones falsas. (AU)

Examining levels of processing using verbal & pictorial stimuli with the complex trial protocol in a mock theft scenario.

The Complex Trial Protocol (CTP) is an EEG-based Concealed Information Test (CIT). Depth of processing influences memorability where deeper processing increases recollection. The CTP's performance as a function of shallow versus deep levels of processing has not been explored. Two experiments were conducted, one with verbal stimuli and the other with their pictorial referents. In both experiments, participants were randomly assigned to three groups, Innocent Control (Control) condition, Guilty Immediate Shallow Processing (Shallow) condition, and Guilty Immediate Deep Processing (Deep) condition. Shallow and Deep participants from both experiments underwent the same mock theft scenario and all three groups were later exposed to either a verbal (N = 41) or pictorial (N = 43) stimulus on a computer monitor. In the word study, no differences in CIT effect were found between any of the groups. Areas under the curve (AUCs) did not differ from chance (.624 and .679 for Shallow and Deep groups respectively). In the image study, the CIT effect for the Shallow and Deep groups differed from the Control one. The AUCs (.755 and .943 for the Shallow and Deep groups respectively) differed significantly from each other. Levels of Processing (LOP) did not appear to have any bearing on CTP performance when words were used as probes but did have an effect when images were used. The findings may hint at some of the limitations of the CTP and fail to replicate similar experiments, especially when words are used as probes, from the late Peter Rosenfeld's laboratory.

Individual differences in self-reported lie detection abilities.

Previous literature on lie detection abilities bears an interesting paradox. On the group level, people detect others' lies at guessing level. However, when asked to evaluate their own abilities, people report being able to detect lies (i.e., self-reported lie detection). Understanding this paradox is important because decisions which rely on credibility assessment and deception detection can have serious implications (e.g., trust in others, legal issues). In two online studies, we tested whether individual differences account for variance in self-reported lie detection abilities. We assessed personality traits (Big-Six personality traits, Dark Triad), empathy, emotional intelligence, cultural values, trust level, social desirability, and belief in one's own lie detection abilities. In both studies, mean self-reported lie detection abilities were above chance level. Then, lower out-group trust and higher social desirability levels predicted higher self-reported lie detection abilities. These results suggest that social trust and norms shape our beliefs about our own lie detection abilities.

Building a second-opinion tool for classical polygraph.

Classical polygraph screenings are routinely used by critical businesses such as banking, law enforcement agencies, and federal governments. A major concern of scientific communities is that screenings are prone to errors. However, screening errors are not only due to the method, but also due to human (polygraph examiner) error. Here we show application of machine learning (ML) to detect examiner errors. From an ML perspective, we trained an error detection model in the absence of labeled errors. From a practical perspective, we devised and tested successfully a second-opinion tool to find human errors in examiners' conclusions, thus reducing subjectivity of polygraph screenings. We report novel features that uplift the model's accuracy, and experimental results on whether people lie differently on different topics. We anticipate our results to be a step towards rethinking classical polygraph practices.

The use-the-best heuristic facilitates deception detection.

Decades of research have shown that people are poor at detecting deception. Understandably, people struggle with integrating the many putative cues to deception into an accurate veracity judgement. Heuristics simplify difficult decisions by ignoring most of the information and relying instead only on the most diagnostic cues. Here we conducted nine studies in which people evaluated honest and deceptive handwritten statements, video transcripts, videotaped interviews or live interviews. Participants performed at the chance level when they made intuitive judgements, free to use any possible cue. But when instructed to rely only on the best available cue (detailedness), they were consistently able to discriminate lies from truths. Our findings challenge the notion that people lack the potential to detect deception. The simplicity and accuracy of the use-the-best heuristic provides a promising new avenue for deception research.

Selective memory detection: Context-dependent stimulus significance in the concealed information test.

Previous studies have posited that the significance of a crime-relevant item in a question produces differential physiological responses in the Concealed Information Test (CIT). However, this term is equivocal and needs to be clarified in order to strengthen the theoretical underpinnings of the CIT. The present study examined the hypothesis that differential responding depends on the examinee's understanding of which item in a question is relevant to a given context. Participants performed a mock theft task, in which they were instructed to steal one item from each of two different locations. An identical CIT question asking about each stolen item was presented under different location contexts while skin conductance response, heart rate, and respiratory activity were recorded. Results indicated that only the relevant item specified by the context of the instruction elicited reliable differential physiological responses. This finding implies that differential responding in the CIT is flexible and context-dependent, and that specifying the subject of a given question is important for detecting crime-relevant memories in practical criminal investigations.

Orienting versus inhibition: The theory behind the ocular-based Concealed Information Test.

When trying to conceal one's knowledge, various ocular changes occur. However, which cognitive mechanisms drive these changes? Do orienting or inhibition-two processes previously associated with autonomic changes-play a role? To answer this question, we used a Concealed Information Test (CIT) in which participants were either motivated to conceal (orienting + inhibition) or reveal (orienting only) their knowledge. While pupil size increased in both motivational conditions, the fixation and blink CIT effects were confined to the conceal condition. These results were mirrored in autonomic changes, with skin conductance increasing in both conditions while heart rate decreased solely under motivation to conceal. Thus, different cognitive mechanisms seem to drive ocular responses. Pupil size appears to be linked to the orienting of attention (akin to skin conductance changes), while fixations and blinks rather seem to reflect arousal inhibition (comparable to heart rate changes). This knowledge strengthens CIT theory and illuminates the relationship between ocular and autonomic activity.

A new theoretical perspective on concealed information detection.

The concealed information test (CIT) was designed to detect concealed knowledge. It does so by measuring differential physiological and behavioral responses to concealed, compared to control, items - i.e., the CIT effect. Although the CIT has gained extensive empirical support in laboratory studies, scientific validity requires also a theoretical understanding of the method's underlying mechanisms. In this article, we present a new theoretical perspective. Specifically, we elaborate and clarify several features of Orienting Response (OR) theory, which has been the dominant theory in this domain. Importantly, we suggest for the first time that the voluntary (rather than the involuntary) OR modulates the CIT effect. Second, we argue that motivational-emotional accounts of the CIT effect are consistent with OR theory and cannot be considered as alternative approaches. Finally, we discuss some more recent developments which highlight the idea that different physiological measures reflect different underlying mechanisms - an idea dubbed as response fractionation.

Only true and fabricated baseline statements combined might improve lie, but not truth, detection.

OBJECTIVES: We tested the effect of true and fabricated baseline statements from the same sender on veracity judgments. HYPOTHESES: We predicted that presenting a combination of true and fabricated baseline statements would improve truth and lie detection accuracy, while presenting a true baseline would improve only truth detection, and presenting a fabricated baseline would only improve lie detection compared with presenting no baseline statement. METHOD: In a 4 × 2 within-subjects design, 142 student participants (Mage = 23.47 years; 118 female) read no baseline statement, a true baseline statement, a fabricated baseline statement, and a combination of a true and a fabricated baseline statement from 29 different senders. Participants then rated the veracity of a true or fabricated target statement from the same 29 senders. RESULTS: Logistic mixed-effects models with senders and participants as random effects showed no significant differences in overall veracity judgment accuracy between the no-baseline (51%) and either the true-baseline (44%) or the fabricated-baseline (49%) conditions. Equivalence tests failed to show the predicted equivalence of these accuracy rates. Separate analyses of truth and lie detection rates confirmed the assumed improvement of lie detection in the combination-of-true-and-fabricated-baseline condition (accuracy = 39%-61%). No other truth or lie detection rate changed significantly except that, unexpectedly, a true baseline reduced truth detection accuracy (64%-49%). CONCLUSIONS: Baseline statements largely did not affect judgment accuracy and, in the case of true baselines, even had a negative impact on truth detection. The rather small positive effect of two baseline statements on lie detection suggests an avenue for further research, especially with expert raters. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Effect of Using Countermeasures in Interpreter-Absent and Interpreter-Present Interviews

Background: In two experiments we examined whether lie tellers, after reading articles about the Model Statement interview tool and/or about the verbal cues complications, common knowledge details and self-handicapping strategies, can successfully use countermeasures by adjusting their statements so that they sound like truth tellers. We also examined whether the presence of an interpreter affect these results. Method: In both experiments, truth tellers discussed a trip they had made; lie tellers fabricated a story. Participants were of Lebanese, Mexican and South-Korean origin. Prior to the interview participants in Experiment 1 did or did not receive information about (i) the working of the Model Statement tool and (ii) three types of verbal detail: complications, common knowledge details and self-handicapping strategies. In Experiment 2 the Model Statement Pre-Information factor was replaced by the presence/absence of an interpreter. Results/Conclusions: We found no evidence that lie tellers adjusted their responses after being informed about the Model Statement and / or the types of detail we examined. (AU)

Antecedentes: Se analiza en dos experimentos si las personas que mienten, una vez han leído artículos sobre la entrevista estándar de obtención de la declaración y auto-depreciación sobre los problemas de los indicios verbales verbales, detalles de conocimiento común y las estrategias de autojustificación pueden utilizar eficazmente contramedidas para ajustar sus declaraciones de modo que parezca que dicen la verdad. También analizamos si influye en estos resultados la presencia de un intérprete. Método: En ambos experimentos, los sujetos que decían la verdad hablaban de un viaje que habían hecho, mientras que los que mentían se inventaban una historia. Los participantes eran de origen libanés, mexicano y surcoreano. Antes de la entrevista los participantes en el experimento 1 no recibían información sobre (i) el funcionamiento de la entrevista estándar de obtención de la declaración y (ii) sobre los tres tipos de detalles verbales: complicaciones, detalles del conocimiento común y estrategias de auto-depreciación. En el experimento 2 se sustituyó el factor información previa sobre la entrevista estándar de obtención de la declaración por la presencia/ausencia de un intérprete. Resultados/Conclusiones: Los resultados nos prestaron apoyo a que los que mienten ajusten sus respuestas tras ser informados sobre la entrevista estándar de obtención de la declaración o los tipos de detalles examinados. (AU)

Power and lie detection.

Social power undermines focus on others and increases reliance on stereotype-consistent information. Thus, power may enhance focus on stereotypical cues to deception, thereby decreasing lie detection accuracy. In three studies, we tested whether having power affects lie detection accuracy. Participants (overall N = 502) were asked to identify truthful and lying candidates (N = 12) during mock job interviews. Study 1 was a field experiment involving employees who held managerial and non-managerial positions (N = 88). In the following laboratory experiments, we manipulated power and asked participants to imagine themselves as managers (Study 2, N = 214) or provided them with control over resources and the ability to reward others (Study 3, N = 200). In Studies 2 and 3, we additionally manipulated the method of lie detection (direct vs. indirect). In contrast to the original hypotheses, we found that power led to increased veracity assessment accuracy. Having power over others enhances the accuracy of one's veracity assessment, although this increase is small and limited to lie detection (Study 1) or direct judgments (Studies 2 & 3). Together, power affects the processing of social information and what aspects of this information are taken into account.

Detection of concealed knowledge via the ERP-based technique Brain Fingerprinting: Real-life and real-crime incidents.

Brain Fingerprinting (BFP) is an electroencephalogram-based system used to detect knowledge, or absence of knowledge of a real-life incident (e.g., a crime) in a person's memory. With the help of BFP, a potential crime suspect can be classified as possessing crime-related information (Information-Present), not possessing crime-related information (Information-Absent), or Indeterminate (BFP unable to classify a subject). In the lab setting, we compare the ground-truth of a subject (i.e., real-life involvement in an incident) against their classification based on BFP testing. We report two studies: replication of BFP with university students (Study 1) and replication of BFP with parolees (Study 2). In Study 1, we tested 31 subjects (24 females, seven males, mean age = 21.3) on either their own or another subject's real-life incident. BFP correctly classified nine Information-Present and 18 Information-Absent subjects, but with one false positive and three exclusions. In Study 2, we tested 17 male parolees (mean age = 47.5) on their own or another parolee's crime incident. BFP correctly classified two Information-Present and six Information-Absent subjects. However, there was also one false positive classification and three Indeterminates. Additionally, we identified three subjects who could not complete the BFP testing and two exclusions. We posit that BFP is not yet at a stage to be considered a robust and accurate crime-detection tool as claimed in former articles. Nevertheless, after addressing the limitations, BFP has considerable potential as an information detection tool in forensic investigations, especially for detecting idiosyncratic crime-relevant knowledge in a perpetrator, in addition to helping to confirm the accuracy of a suspect's claim of innocence.

Effective Connectivity in Cortical Networks During Deception: A Lie Detection Study Based on EEG.

Thus far, when deception behaviors occur, the connectivity patterns and the communication between different brain areas remain largely unclear. In this study, the most important information flows (MIIFs) between different brain cortices during deception were explored. First, the guilty knowledge test protocol was employed, and 64 electrodes' electroencephalogram (EEG) signals were recorded from 30 subjects (15 guilty and 15 innocent). Cortical current density waveforms were then estimated on the 24 regions of interest (ROIs). Next, partial directed coherence (PDC), an effective connectivity (EC) analysis was applied in the cortical waveforms to obtain the brain EC networks for four bands: delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz) and beta (13-30 Hz). Furthermore, using the graph theoretical analysis, the network parameters with significant differences in the EC network were extracted as features to identify the two groups. The high classification accuracy of the four bands demonstrated that the proposed method was suitable for lie detection. In addition, based on the optimal features in the classification mode, the brain "hub" regions were identified, and the MIIFs were significantly different between the guilty and innocent groups. Moreover, the fronto-parietal network was found to be most prominent among all MIIFs at the four bands. Furthermore, combining the neurophysiology significance of the four frequency bands, the roles of all MIIFs were analyzed, which could help us to uncover the underlying cognitive processes and mechanisms of deception.