Deception affects inter-brain EEG and autonomic synchronization within a dyad: a hyperscanning study

Deception affects inter-brain EEG and autonomic synchronization within a dyad: a hyperscanning study | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 20 March 2025 V1 Latest version Share on Deception affects inter-brain EEG and autonomic synchronization within a dyad: a hyperscanning study Authors : Giorgio Veneziani , Federica Luciani , Emanuele Giraldi , Virginia Campedelli , and Carlo Lai 0000-0002-7638-0375 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174248910.02143113/v1 529 views 273 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Research on deception focused on the neurophysiological assessment of the deceiver, showing activation of specific brain areas and increased autonomic activity. However, deception is an interpersonal process where both the deceiver and the deceived interact in a constant process of evaluation that requires demanding cognitive resources. The present study aimed to investigate inter-brain synchronization (IBS) and heartbeats synchrony between an interviewer intent on detecting deception and an interviewee during a deception (Deception Group; “DG”) or truth-telling (Non-Deception Group; “NDG”) task using an ecological mock crime experiment. The results showed that DG exhibited higher IBS before the interview in the theta band and during the interview in the alpha band while displaying decreased heartbeats synchrony across all experimental phases compared to NDG. The greater IBS in DG involved particularly the left temporal area of the interviewee. These findings highlight the relevance of studying deception according to a two-person neuroscience perspective, suggesting that while neural processes are synchronized before and during a deceptive interaction, autonomic processes follow different activation patterns. Integrating the hyperscanning techniques with existing lie-detection methods could enhance the identification of neurophysiological markers of deception. Deception affects inter-brain EEG and autonomic synchronization within a dyad: a hyperscanning study Giorgio Veneziani a , Federica Luciani a , Emanuele Giraldi a , Virginia Campedelli a , Carlo Lai a* a Department of Dynamic and Clinical Psychology, and Health Studies, Faculty of Medicine and Psychology, Sapienza University of Rome, Via degli Apuli, 1, Rome 00185, Italy. Author note Giorgio Veneziani https://orcid.org/0000-0001-6223-5460 E-mail: [email protected] Federica Luciani https://orcid.org/0000-0002-1721-5214 E-mail: [email protected] Emanuele Giraldi https://orcid.org/0009-0000-7895-5411 E-mail: [email protected] Virginia Campedelli https://orcid.org/0000-0002-1630-2308 E-mail: [email protected] Carlo Lai https://orcid.org/0000-0002-7638-0375 E-mail: [email protected] * Corresponding Author Carlo Lai, Ph.D., Full Professor, Department of Dynamic and Clinical Psychology, and Health Studies, Sapienza University of Rome, Via degli Apuli, 1, Rome 00185, Italy. Email: [email protected] Abstract Research on deception focused on the neurophysiological assessment of the deceiver, showing activation of specific brain areas and increased autonomic activity. However, deception is an interpersonal process where both the deceiver and the deceived interact in a constant process of evaluation that requires demanding cognitive resources. The present study aimed to investigate inter-brain synchronization (IBS) and heartbeats synchrony between an interviewer intent on detecting deception and an interviewee during a deception (Deception Group; “DG”) or truth-telling (Non-Deception Group; “NDG”) task using an ecological mock crime experiment. The results showed that DG exhibited higher IBS before the interview in the theta band and during the interview in the alpha band while displaying decreased heartbeats synchrony across all experimental phases compared to NDG. The greater IBS in DG involved particularly the left temporal area of the interviewee. These findings highlight the relevance of studying deception according to a two-person neuroscience perspective, suggesting that while neural processes are synchronized before and during a deceptive interaction, autonomic processes follow different activation patterns. Integrating the hyperscanning techniques with existing lie-detection methods could enhance the identification of neurophysiological markers of deception. Keywords : Deception; EEG; Hyperscanning; Interbrain synchronization; Heartbeats. Impact statement Hyperscanning is an innovative technique for studying the neurophysiological correlates of social interactions. The results showed that the group where the interviewee deceived about a backpack’s contents exhibited higher inter-brain synchronization with an interviewer aimed at detecting deception, before and during a deception task, while displaying decreased heartbeats synchrony across all experimental phases, compared to the non-deceptive group. The findings highlight the importance of a two-person neuroscience perspective in identifying neurophysiological markers of deception. 1. Introduction Deception is a process in which a deceiver convinces others to accept a belief or interpretation, conveying false information (Buller & Burgoon, 1996; Jagannath et al., 2022; Vrij et al., 2004; Zhang et al., 2017). The act of deceiving consists of verbal and nonverbal efforts, where deceivers tend to feel an increase in general arousal, emotion, and cognitive load and a tendency to manage their image to maintain credibility (Buller & Burgoon, 1996; Ekman, 1985; Srour & Py, 2023; Vrij et al., 2008; Zuckerman et al., 1981). The higher cognitive demands associated with deception, compared with telling the truth, have been highlighted by previous research, showing that deception can lead to experiencing negative affect, probably due to violating social norms (Buller & Burgoon, 1996; Srour & Py, 2023; Zuckerman et al., 1981). Considering its relevant role in human development and social behavior, deception has received considerable interest in recent years from the literature (Alempaki et al., 2019; Chen et al., 2020; Zhang et al., 2017). As a complex social interaction, deception involves several brain areas related to executive functions (Sip et al., 2008; Wagner-Altendorf et al., 2020). Previous studies showed increased activity in brain areas involved in high cognitive processes, such as mentalizing, behavioral inhibition, and decision-making, during deception tasks (Lin et al., 2021; Zhang et al., 2017; Phan et al., 2005). In particular, the involvement of the prefrontal cortex was suggested in the intentional falsification processes (Abe, 2009; Kozel et al., 2005; Spence et al., 2004), whereas the activations of the inferior frontal gyrus and the caudate were associated with expected reward and risk avoidance (Sip et al., 2008). Several studies using event-related potential advised the efficiency of electroencephalogram (EEG) in identifying detection (Abootalebi et al., 2009; Jagannath et al., 2022; Suchotzki et al., 2015). However, the brain connectivity patterns and mechanisms underlying deception were less investigated (Chang et al., 2019; Gao et al., 2022; Kohan et al., 2020; Liu et al., 2019), despite phase oscillatory activity seemed to be an efficacious neural correlate of many high cognitive processes involved in deception (Gao et al., 2022; Varela et al., 2001). Moreover, autonomic system activations, particularly at the cardiovascular level, were found to be effective physiological signals for recognizing deceptive situations (Ambach & Gamer, 2018; Duran et al., 2018; Gamer, 2011). In this regard, deceptive behavior was shown to be associated with increased heart rate, which could reflect a higher physiological arousal and cognitive load in generating deceptive information (Ambach & Gamer, 2018). Furthermore, previous studies found that increased cardiovascular activity may indicate the level of stress in immoral situations (Gu et al., 2013; Valins, 1996). Accordingly, deception seems to involve both cognitive and emotion-related response patterns, making the combination of neural and autonomic measurements a useful and effective approach to improve the accuracy of detecting deception (Ambach & Gamer, 2018; Cook & Mitschow, 2019). In addition, it is important to consider that deception is an interpersonal process in which both deception and its detection are associated with the individuals’ arousal, negative affects, cognitive tension, and attempt to control (Buller & Burgoon, 1996; Burgoon & Buller, 2015). In this regard, despite numerous individual-focused brain imaging studies being conducted, it could be useful to examine deception considering the dynamic interaction between individuals face-to-face (Pinti et al., 2021; Zhang et al., 2017). Indeed, face-to-face interactions sustained the evolution of sociality itself (Jahng et al., 2017), and several nonverbal cues, such as tone of voice and eye contact, have a pivotal role in deciphering others’ intentions and mental states (Emery, 2000; Kuzmanovic et al., 2009). Interestingly, nonverbal cues seemed to be associated with activations of brain areas related to social cognition (Senju & Johnson, 2009), supporting their relevance in understanding social intentions (Zhang et al., 2017). In this context, deceivers have to produce an appropriate deceptive message, controlling their behavior, avoiding cues of deception (such as changes in the tone of voice and speech rhythm), and appearing natural (Pinti et al., 2021; Zuckerman et al., 1981). At the same time, the individual trying to recognize deception can identify relevant nonverbal cues in the behavior and interpret them to determine whether the other person is deceiving or telling the truth (Pinti et al., 2021). Studies using the hyperscanning technique seem to show interesting new perspectives in understanding the neural correlates involved in social interactions (Astolfi et al., 2010; Carollo & Esposito, 2024; Czeszumski et al., 2020; Montague et al., 2002; Kinreich et al., 2017). This technique involves simultaneously measuring the neural activities of multiple individuals during interactive tasks (Schilbach et al., 2013). Previous hyperscanning studies highlighted that specific brain areas and frequency bands were associated with several interpersonal dynamics (Dikker et al., 2017; Zhou et al., 2021), such as collaboration (Antonenko et al., 2019) and competition (Liu et al., 2019). Research within this theoretical framework considers the two brains as a single system, evaluating the associations between regions of two or more brains (Koike et al., 2015) through inter-brain synchronization (IBS) (Sänger et al., 2012). When individuals engage in coordinated tasks or experience stimuli simultaneously, their neural activity may become synchronized in specific frequency bands (Balconi & Vanutelli, 2018). Recent studies found that interpersonal factors, such as the role taken in social interactions (Müller et al., 2013) or the quality of relationships (Chen et al., 2024), were associated with different degrees of IBS. Several indices have been developed to quantify the degree of neural synchronization (Burgess, 2013). The correlation of signals, using coherence measures or correlation measures for circular distributions (e.g., the circular correlation coefficient) (Jammalamadaka, 2001; Zhang, 2018), and the phase synchronization of neural oscillations are the most used methods for assessing inter-brain EEG synchrony. Specifically, the phase locking value (PLV) is currently the most frequently used index in dual-brain EEG studies (Lachaux et al., 1999; Turk et al., 2022), measuring whether the signals of two individuals are phase-locked over time within a specific frequency band (Dasdemir et al., 2017; Hu et al., 2018; Liu et al., 2021). Several studies showed that specific interpersonal processes were associated with IBS in different frequencies (Barraza et al., 2020; Mu et al., 2017; Sinha et al., 2016). In particular, shared behavioral rhythms and social stimuli was found to be associated with higher IBS in the theta band (4-7 Hz) (Barraza et al., 2020; Wang et al., 2020), suggesting its potential role as a marker of social cognition and emotional engagement (Balconi & Vanutelli, 2018). Theta and alpha (8-12 Hz) IBS seem particularly sensitive to human contact, with greater theta and alpha IBS observed in human-human interactions compared to human-computer interactions (Pan et al., 2016). Moreover, several studies associated affective attentional mechanisms with the alpha rhythm (Uusberg et al., 2013), hypothesizing that it could play a relevant function in maintaining attention to environmental stimuli and, potentially, in emotional salience (Zouaoui et al., 2023). Interestingly, socio-emotional interactions between two individuals were also associated with the synchrony of their heart rates (Vanutelli et al., 2017; Helm et al., 2012; Reindl et al., 2022), suggesting that synchronization can occur at both the neural and autonomic levels during these interactions. In particular, it was found that heart rate synchrony increased during cooperative tasks (Mitkidis et al., 2015; Vanutelli et al., 2017) and during interactions aimed at eliciting a shared emotional arousal in romantic partners (Helm et al., 2012), while decreasing in competitive contexts (Romero-Martínez et al., 2019). Moreover, previous studies showed that heart rate synchrony varied according to emotional closeness, finding increased levels of synchrony associated with the degree of emotional bonding between pairs of participants and in those who had a close working relationship or lived together in a bonding relationship (McCraty, 2004, 2017; Konvalinka et al., 2011). Recent fNIRS studies applied the hyperscanning technique to the study of spontaneous deception, showing gender differences in IBS (Chen et al., 2020) and increased IBS in the left posterior superior temporal sulcus during deceptive acts compared to honest ones (Zhang et al., 2017). At the same time, these studies used a card-gambling paradigm (Zhang et al., 2017) and a sender-receiver paradigm based on a game-theoretic modeling task (Chen et al., 2020) in which both experimental conditions left it up to the participants to decide when to deceive. The main limitations of these studies were that the laboratory-based experimental tasks differed from naturalistic real-life situations in which deceptive acts occur and that the deception and truth-telling conditions were not experimentally manipulated. In addition, to date, no study in the literature has investigated both neural and autonomic synchrony during deception, which could provide a better understanding of the neurophysiological processes underlying deception. Therefore, the present study aimed to investigate EEG IBS and heartbeats synchronization between an interviewer intent on detecting deception and an interviewee during a deception or truth-telling task using an ecological mock crime experiment. In particular, differences in neural and heartbeats synchronization (interviewer-interviewee) were evaluated between a group in which the interviewee deceived (Deception Group, “DG”) and a group in which the interviewee did not deceive (Non-Deception Group, “NDG”). The hypothesis was that DG would show increased neural synchronization and decreased heartbeats synchronization compared to NDG. 2. Materials and methods 2.1. Participants Thirty healthy right-handed individuals with normal or corrected-to-normal vision (16 females; M age = 25.2 years, SD age = 3.7 years; range = 20-34 years) were included in the present study. All participants self-reported that they did not take medication and did not have past or present neuropsychiatric, neurological disorders, and health problems (such as head injuries). All participants were informed about the purpose and procedure of the experiment and gave their written informed consent prior to participation. The present study was conducted in accordance with the Declaration of Helsinki (1964) and was reviewed and approved by the Ethics Committee of the Department of Dynamic and Clinical Psychology, and Health Studies, Sapienza University (protocol number: 0000589). 2.2 Group assignment Participants were randomly assigned to the Deception Group (DG; n = 15; 7 females; M age = 26.2 years, SD age = 3.9 years; range = 22-34 years) or the Non-Deception Group (NDG; n = 15; 9 females; M age = 24.1 years, SD age = 3.1 years; range = 20-32 years). In the DG, participants were instructed to lie about the contents of a backpack (as described in the next paragraph), while in the NDG, participants were instructed to tell the truth about its contents during an interview they will undergo with an interviewer. 2.3. Backpack An experimenter provided each participant with an empty backpack to pack specific items. Participants in both groups (DG and NDG) filled their backpacks with items habitually possessed by visitors to the Department (“non-restricted”) (personal computer, sunglasses, t-shirt, box of painkillers, and USB flash drive) and items of uncommon use and considered dangerous (“restricted”) (bottle of alcohol, hammer, knife, lighter fluid, and legal cannabis). 2.4. Interview The interview was designed to obtain verbal responses regarding the content of the participants’ backpacks. In particular, a structured interview (Table S1, Supplementary materials), adapted from Mapala and colleagues (2017), consisting of 30 yes/no questions in random order written on a paper, was used. Ten questions evaluated the presence of non-restricted items (e.g., sunglasses, notebook, etc.), ten evaluated the presence of restricted items (e.g., alcohol, hammer, etc.), and ten were unexpected questions about general information (e.g., “ Do you think there is traffic today ?”; “ Is today your birthday ?”). The interview was conducted by a recruited interviewer (male; 26 years old; PhD student) who signed the informed consent and was instructed to identify whether the interviewee lied or did not lie about the backpack’s content. The interview room was set up with two chairs placed two meters apart with a table in the middle, on which the structured interview was placed, facing the interviewer. The study recruited only one interviewer to control for the potential influence different interviewers could exert on the IBS, considering the high intersubjective variability to which EEG data are subject (Saha & Baumert, 2020). 2.5. Procedure The research was conducted at the Department of Dynamic and Clinical Psychology and Health Studies at Sapienza University of Rome. The interviewer arrived about five minutes before the participant and was accompanied by an experimenter to the interview room. The participant, once arrived, signed the informed consent and was randomly assigned to the DG or NDG (Figure 1). Subsequently, the participant filled the backpack with items provided and was told to lie (DG) or tell the truth (NDG) about its content during the interview she/he will undergo. Afterwards, the participant was accompanied to the interview room, where joined the interviewer and where both were fitted with the EEG and heartbeats acquisition system. To maintain the unfamiliarity between the interviewer and the participant, they were seated beside each other with a dividing panel and were guided not to speak (Djalovski et al., 2021). Once the sensors were set up, the experimenter removed the dividing panel and, before leaving the room, asked the dyad to maintain eye contact for a short period of time, limiting body movements as much as possible. The hyperscanning EEG and heartbeats acquisition phases between the interviewer and the participant then started. After 128 seconds of direct gaze (First Direct Gaze), the experimenter reentered the room and instructed the interview phase (Interview), which involved administering the structured interview, asking the interviewer and the participant to speak slowly and maintain eye contact with each other. During this phase, the interviewer only moved his eyes to read each question and then repeated it while staring at the participant. At the end of the interview, after about three minutes, the experimenter re-entered the room, giving instructions for the last phase, in which the interviewer and the participant were asked to make eye contact (Second Direct Gaze). At the end of this phase, which lasted 128 seconds, the experimenter re-entered the room and asked the participant to leave. The participant was then taken to another room to complete the demographic and psychological questionnaires. Meanwhile, the experimenter asked the interviewer to provide his judgment on whether or not the participant had lied regarding the items in the backpack. Encephalan-EEGR software (Medikom MTD, Russia) was used to control the timing and to video record all the experimental phases. Figure 1 . Schematic description of the experimental procedure. The first phase of the procedure consisted of randomly assigning participants to either the DG or the NDG. Subsequently, participants filled the backpack with the items provided and were instructed to lie (DG) or tell the truth (NDG) about its contents. Afterwards, the hyperscanning EEG and heartbeats acquisition phases began between the interviewer and the participant. Initially, each dyad was asked to make eye contact before the interview for 128 seconds (First Direct Gaze). Then, the interviewer administered the structured interview to the participant (Interview; mean duration 192 seconds). Finally, after the interview, each dyad was asked to make eye contact for 128 seconds (Second Direct Gaze). Participants were administered demographic and psychological questionnaires at the end of the experimental procedure. Note . “DG” = Deception Group; “NDG” = Non-Deception Group. 2.6. Questionnaires Information about gender, age, civil and professional status, education level, and motivation to participate in the study was collected. In addition, the Personality Inventory for DSM-5-Brief Form (PID-5-BF) (Fossati et al., 2013) was used in the present study to assess personality dimensions as characterized by DSM-5. Indeed, considering that previous research showed how different personality traits modulated neural activities (James et al., 2015), the present study used the questionnaire to check for differences between the DG and NDG in maladaptive personality traits. The PID-5-BF was developed by extracting 25 items from the original PID-5, representing 21 of the 25 trait facets. Items are rated on a 0–3 Likert-type scale, with higher scores representing more significant dysfunction. Each of the five higher-order domains is represented by five items (Negative Affect: items 8, 9, 10, 11, and 15; Detachment: items 4, 13, 14, 16, and 18; Antagonism: items 17, 19, 20, 22, and 25; Disinhibition: items 1, 2, 3, 5, and 6; and Psychoticism: items 7, 12, 21, 23, and 24). 2.7. EEG and heartbeats acquisition and preprocessing The Encephalan Main Syncro EEG system consists of two units with synchronous acquisition and video recording of the participants’ neural activities (Medikom MTD, Russia). The system comprehended two caps with 19 electrodes arranged according to the international 10/20 system (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2), the neutral (N) and the two references electrodes (A1 and A2). The caps were aligned to nasion, inion, and left and right pre-auricular points. Two electrooculograms (EOG) and one electromyogram (EMG) were used to record the ocular and muscular artifacts. In addition, one electrocardiogram (ECG) was used to acquire the cardiac artifacts and the number of heartbeats. The impedances were maintained below five kΩ. The signals were online filtered between 0.5 and 70 Hz, and the sampling frequency was 250 Hz. Similar to Petukhov and colleagues (Petukhov et al., 2020), an automatic algorithm implemented in Encephalan-EEGR software was used to suppress blinking, eye motions, facial muscles, and cardiac activity. Specifically, to detect EOG artifacts, the algorithm searches for each EEG channel the portions of the signal with an amplitude greater than 10 µV (5 µV/count for EMG) or deviates from an average “sigma” value of ±80 µV. Specifically, the software calculates the standard deviation (SD) of the signal and excludes outliers, i.e., values such that the difference between the value minus the mean value is higher than 1.5 SD. Next, it calculates the standard deviation of the remaining values following the exclusion of outliers and calculates a threshold “Th” defined by Th = sigma*SD 2 , where SD 2 is calculated by Equation 1: \begin{equation} \begin{matrix}SD_{2}=\sqrt{\frac{1}{N-1}\sum_{V\in L}\left(v-\overline{v}\right)^{2}}\#\left(1\right)\\ \end{matrix}\nonumber \\ \end{equation} In the equation, v is the value considered, and v̅ is the mean value of the time portion. V is the set of values of the time portion. L is the subset of values of V following the exclusion of outliers, equal to V if no outliers are present. N is the number of values in the selected temporal portion. The artifact starts when the value ( v ) is greater than 10 µV for EOG (5 µV/count for EMG), and simultaneously, the difference between the value and the mean value is higher than Th. Once the artifact is identified, using a linear regression algorithm, the software removes the EOG artifact (X) from the individual EEG channels (Y), according to the algorithm shown in Equation 2: \begin{equation} \begin{matrix}Y^{{}^{\prime}}=Y-mX\#\left(2\right)\\ \end{matrix}\nonumber \\ \end{equation} Where Y’ is the EEG signal cleaned of the artifact. Y is the raw EEG signal affected by the artifact, and m is the similarity coefficient between EOG/EMG and EEG. Lastly, X is the EOG/EMG signal acquired from the EOG and the EMG. Regarding cardiac artifacts on EEG signals, the ECG electrode will identify ECG artifacts that appear on the EEG signal in the form of graphical elements similar to those on the QRST complex. In such cases, the algorithm suppresses ECG artifacts using the same calculation for the suppression of EOG/EMG artifacts. Subsequently, the EEG data of each experimental phase (First Direct Gaze, Interview, and Second Direct Gaze) related to a dyad were exported to Python for further preprocessing using the open-source library Hyperscanning Python Pipeline (HyPyP) (Ayrolles et al., 2021). Specifically, 1-second epochs (Leong et al., 2017; Liu et al., 2021) were created and were further cleaned using a HyPyP function adapted from Autoreject (Ayrolles et al., 2021; Jas et al., 2017). The function uses an algorithm with Bayesian optimization as the threshold method and interpolates the bad sensors per participant, rejecting the epochs containing transient spikes in isolated EEG electrodes and artifacts affecting several channels. The autoreject function uses the “union” strategy that maintains only electrodes and epochs considered “good” for the two participants, immediately rejecting the epochs considered “bad” for subject one and for subject two. The rejected epochs for each phase are shown in Table S2 (Supplementary materials). 2.8. EEG hyperscanning analyses HyPyP was used to analyze inter-brain activities (Ayrolles et al., 2021). Coherently with a previous hyperscanning study, the analytic signals were computed by applying infinite impulse response (IIR) filtering and the Hilbert transform (Schwartz et al., 2024). To evaluate the inter-brain synchrony, the following frequency bands were considered: Theta (4-7 Hz) and Alpha (8-12 Hz). The phase locking value (PLV) for each frequency was calculated and averaged across the epochs of a specific experimental phase. The PLV measures inter-brain synchrony by detecting the rhythmicity between the recorded EEG signals of two brains. This is a standard technique for analyzing the instantaneous phase of two signals in EEG hyperscanning studies and measuring the intra-trial consistency of the phase difference between electrodes (Burgess, 2013). Specifically, the PLV measured in the present study is calculated by: \begin{equation} \begin{matrix}\text{PLV}_{t}=\frac{1}{T}\left|\sum_{n=1}^{T}e^{i(\phi_{\left(t,\ \ n\right)}\ -\ \psi_{\left(t,\ n\right)}}\right|\#\left(3\right)\\ \end{matrix}\nonumber \\ \end{equation} In Equation 3, T is the number of time samples within the considered window, e is Euler’s number, i is the complex operator, ϕ ( t , n ) corresponds to the phase on observation n at time t in channel ϕ, and ψ ( t , n ) corresponds to the phase on observation n at time t in channel ψ . The PLV t could vary between 0 (no phase locking over time) and 1 (perfect phase locking over time). 2.9. Statistical analysis After the descriptive analyses, independent t-tests were performed to evaluate the differences in age, education, and maladaptive personality traits between the DG and NDG using JASP software (v. 0.18.3) (JASP team, 2024). HyPyP was used to perform cluster-level statistics provided by independent t-tests to compare PLV values along the scalp between the DG and NDG for each experimental phase (Ayrolles et al., 2021). Considering that the interviewer conducted the interview repeatedly, each time interacting with new interviewees, an additional cluster-level statistic (independent t-test) was performed between the first and last five interviews conducted within each group (DG and NDG) to account for the interviewer’s habituation to the task. The present study, to address the problem of multiple comparisons (MCP), which is considered a major limitation in EEG studies (Piai et al., 2015), corrected the results using the nonparametric cluster-based permutation test (Maris & Oostenveld, 2007), which clusters neighboring quantities with the same effect. Only results from clustered electrode pairs that exceeded the cluster level threshold (p < 0.05) were interpreted, as done in previous EEG hyperscanning studies (Dikker et al., 2021; Veneziani et al., 2024; Wang et al., 2024; Welke & Vessel, 2022). A bootstrap resampling and permutation method was used for cluster statistics (N = 5000). Cohen’s d was calculated to assess the effect sizes, according to previous EEG hyperscanning studies (Balconi & Angioletti, 2023, 2024; Veneziani et al., 2024). The number of heartbeats acquired through the interviewee’s ECG electrode was subtracted from the number of heartbeats of the interviewer (Δ interviewee - interviewer) in the DG and NDG for each of the three different phases of the procedure. Independent t-tests were performed to assess the differences between DG and NDG on the Δ interviewee – interviewer heartbeats using JASP software (v. 0.18.3) (JASP team, 2024). Lastly, to assess differences in the number of interviewees’ heartbeats between the groups, independent sample t-tests were conducted on the number of interviewees’ heartbeats between the DG vs. NDG during the First Direct Gaze, the Interview, and the Second Direct Gaze phases. 3. Results Independent t-tests performed to evaluate the differences in age, education, motivation, and maladaptive personality traits between the DG and the NDG showed no significant differences (Table 1). Table 1 . Differences between the Deception Group and Non-Deception Group on demographics and personality dimensions. Mean, standard deviations (SD), and independent t-tests of age, years of education, motivation, and the Personality Inventory for DSM-5 - Brief Form (PID-5-BF), between the Deception and the Non-Deception groups. Mean SD Mean SD t df p-value Age 26.20 3.95 24.13 3.14 1.59 28 0.12 Education (years) 16.00 1.46 15.47 1.68 0.93 28 0.36 Motivation 5.73 1.28 5.87 1.19 -0.30 28 0.77 Negative Affect 1.37 0.58 1.09 0.54 1.36 28 0.19 Detachment 0.81 0.61 0.62 0.54 0.88 28 0.38 Antagonism 0.67 0.46 0.63 0.35 0.27 28 0.79 Disinhibition 0.81 0.58 0.76 0.61 0.24 28 0.81 Psychoticism 0.92 0.55 0.93 0.84 -0.05 28 0.96 PID-5-BF total score 0.92 0.41 0.81 0.44 0.70 28 0.49 3.1 Inter-brain synchronization Cluster-based analysis over the frequency bands of interest revealed a significant cluster in the Theta band, mainly involving left frontal electrodes of the interviewer and highlighting increased IBS for DG compared to NDG before the interview (Figure 2, “First Direct Gaze”). Moreover, a significant cluster in the Alpha band during the interview (Figure 2, “Interview”) showed an increase of IBS for DG compared to NDG involving mainly right temporo-parietal electrodes of the interviewer. The greater differences between the IBSs of the two groups (darker lines) involved the left temporal electrode of the interviewees during both First Direct Gaze in the theta band and Interview in the alpha band. Figure 2. Significant inter-brain synchronization (IBS) differences in the Theta band during the First Direct Gaze and Alpha band during the Interview between dyads (interviewer-interviewed) of the Deception Group (DG) and the Non-Deception Group (NDG). Note . Red lines represent positive t values (DG IBS > NDG IBS). A darker line indicates a greater difference in the IBS between DG and NDG. On the right, only for the significant clusters, the specific electrodes’ PLVs of the DG (in blue) and the NDG (in orange) are reported. Regarding effect sizes, for the DG vs. NDG comparisons in the First Direct Gaze, Cohen’s d indicated a range between large and very large effect sizes (1.15 < Cohen’s d < 1.55; mean = 1.31). Similarly, during the Interview, Cohen’s d indicated a range between large and very large effect sizes (1.13 < Cohen’s d < 1.58; mean = 1.25). Cluster-based analyses (independent t-test) conducted to assess possible differences in IBS between the first and last five interviews showed no significant cluster in both DG and NDG. 3.2. Heartbeats results Regarding heartbeats activations, significant differences were found between DG and NDG, where a higher Δ interviewee – interviewer in heartbeats was shown in DG compared to NDG during the First Direct Gaze, the Interview, and the Second Direct Gaze (Table 2). Table 2 . Comparisons (independent t-tests) between DG (Deception Group) and NDG (Non-Deception Group) on Δ interviewee - interviewer heartbeats during the three phases of the experimental procedure DG NDG Mean SD Mean SD t df p-value First Direct Gaze (1 st phase: 128s) 22.3 17.4 -11 33.1 3.45 28 0.002 Interview (2 nd phase: average: 192s) 51.3 38.3 -0.67 43.4 3.39 28 0.002 Second Direct Gaze (3 rd phase: 128s) 21.5 20.3 0.87 19.6 2.84 28 0.008 The participants’ heartbeats of the DG, compared to those of the NDG, did not differ during the First Direct Gaze (M DG =159.0±16.6, M NDG =153.1±25.8; t(28)=0.740, p=0.465), the Interview (M DG =270.1±41.1, M NDG =236.5±53.3; t(28)=1.928, p=0.064), and the Second Direct Gaze (M DG =162.9±23.3, M NDG =156.5±21.0; t(28)= 0.791, p=0.436). 4. Discussion The present study aimed to evaluate the differences in IBS and heartbeats synchrony (interviewer-interviewee) between a group in which the interviewee deceived (Deception Group, “DG”) and a group in which the interviewee did not deceive (Non-Deception Group, “NDG”). The main results showed that DG exhibited higher IBS before the interview in a theta band (4-7 Hz) cluster and during the interview in an alpha band (8-12 Hz) cluster, while displaying decreased heartbeats synchrony across all three experimental phases (First Direct Gaze, Interview, and Second Direct Gaze) compared to NDG. These results show that in dyads where one individual deceives and the other tries to detect the deception, their neural activations would be more synchronized and their heartbeats less coordinated than dyads where the individual tells the truth. The higher IBS observed in the DG compared to the NDG is consistent with previous literature showing an increase in IBS during deceptive acts compared to honest ones (Zhang et al., 2017). Lying and its detection seem to foster in both interlocutors a tendency to evaluate socio-emotional cues to analyze their behavior, for example looking into each other’s eyes is a relevant cue for speculating on the internal states of others (Emery, 2000; Kuzmanovic et al., 2009; Mann et al., 2012; Pinti et al., 2021; Vrij et al., 2010). Accordingly, research on the neural basis of deception showed activation of areas associated with mentalization, socio-emotional processing, and cognitive control (Lin et al., 2021; Zhang et al., 2017; Phan et al., 2005). On the one hand, the present study’s findings suggest that these neural processes could be more synchronized in dyads in which one individual lies compared to dyads in which one individual tells the truth (Zhang et al., 2017). On the other hand, the results suggest that autonomic activations (heartbeats) could follow different activation patterns within the dyad during deception. In this regard, previous scientific research showed that increased synchronization of heart rate was associated with greater dyadic trust (Mitkidis et al., 2015), while lower congruence of ECG signals was found in competitive contexts (Romero-Martínez et al., 2019). Several studies highlighted that when individuals are deceptive, they experience increased autonomic activity, which could reflect a higher physiological arousal and cognitive load in generating deceptive information (Ambach & Gamer, 2018). Moreover, autonomic activations seem to be associated with involuntary bodily responses and emotional involvement, while neural activations with high-level cognitive and affective regulation (Balconi & Cassioli, 2022). Accordingly, it could be hypothesized that shared attention and processing of social-emotional states during deceptive acts would be associated with increased IBS, while processes less subject to cognitive control might associate with lower autonomic synchrony. In addition, it is worth noting that the heartbeats of DG interviewees did not differ from those of NDG, suggesting that simultaneous and not just intraindividual assessment of autonomous activities would be an interesting indicator for identifying physiological correlates of deception. In the present study, during deception (Interview phase), the higher IBS in the DG compared to the NDG was found specifically in alpha band activity. It has been suggested that alpha activity has a potential role in maintaining attention to the reactions of others (Zouaoui et al., 2023). Moreover, previous studies found an increase in alpha band IBS during motor coordination tasks (Dumas et al., 2010) and flight phases involving high cooperativity (Astolfi et al., 2010; Toppi et al., 2016). Interestingly, the results of the present study suggest that this increase in IBS may not be related to greater collaboration or coordination per se, but rather to a greater shared attention to the task. Indeed, it was proposed that alpha activity would be related to understanding the mental states, emotions, and behavior of others (Mu et al., 2018). Thus, the enhanced alpha IBS between individuals during mental coordination might also reflect enhanced neural couplings of the brain activity associated with sharing/understanding others’ mental states to coordinate with others mentally (Mu et al., 2018). It is possible to hypothesize that lying processes involve attentional control and attempts to understand others, which are more shared in dyads in which one individual lies than in dyads in which one individual does not lie, emphasizing the high intersubjectivity involved in this process. Interestingly, the present study showed that the theta band IBS increased before the interview (First Direct Gaze phase). In this regard, several studies highlighted the role of theta rhythm in social and emotional processes (Uusberg et al., 2014). It has been proposed that theta activity is associated with empathy processes (Deng et al., 2023), where the increased IBS might reflect a social understanding among interacting individuals (Cui et al., 2012). Consistently, it could be argued that even the intention to deceive another person, without effectively performing the deceptive act, is associated with increased IBS due to the deceiver’s efforts to comprehend the interlocutor’s reactions. Finally, it is important to note that the greater IBS in DG involved specifically the left temporal electrode of the interviewee during both the First Direct Gaze phase in the theta band and the Interview phase in the alpha band. This finding suggests that the left temporal region could play a relevant role not only in deceptive behavior, as highlighted by previous studies (Kohan et al., 2020; Ofen et al., 2016), but also in deception planning, taking into account the reactions and behaviors of the person to be deceived. While the present study provided innovative understandings of the neurophysiological processes underlying deception, some limitations must be highlighted. Firstly, despite the sample size being similar to (Zhou et al., 2021; Balconi & Vanutelli, 2018) or higher (Toppi et al., 2016; Balconi et al., 2023) than previous hyperscanning studies, the small number of participants could have weakened the statistical power of the present study. Considering that several studies showed inter-individual differences in cardiac activity (Olshansky et al., 2023; Quer et al., 2020), the lack of an assessment of heart rate variability must be considered another important limitation. In addition, the measurement of cardiac synchrony between dyad members was operationalized through the difference between heartbeats (Δ). This methodological choice allows for a simple and direct measure of physiological coordination between individuals but does not allow for the investigation of more complex dynamics of co-regulation. Future studies could use synchronization indices based on co-variation or temporal phase for a deeper understanding of dyadic autonomic interactions. Lastly, there is a need to consider that the number of EEG electrodes was limited, and thus the directionality of the neural signals assessed with the hyperscanning technique could not be determined. Future research should strengthen the results of the present study by replicating them on a larger sample and using a higher number of electrodes. Furthermore, future studies could develop and standardize experimental paradigms to study the interpersonal neurobiological basis of deception and, in addition, should include an experimental procedure that measures a baseline of IBS and resting heart rate before any tasks to control the intra-individual variability. 5. Conclusion In conclusion, the present study provided new insight on the interpersonal neural and autonomic basis of deception. The results showed that DG exhibited greater synchrony at the neural level while displaying lower heartbeats synchrony compared to NDG. This discrepancy between neural and autonomic synchrony suggests that deception is a complex process involving cognitive coordination between interlocutors but may lead to differences in their emotional and autonomic states. In addition, the results of the present study suggest that the left temporal region might play a relevant role in deceptive planning and behavior. These findings could have implications for the development of advanced lie-detection techniques. In particular, simultaneous inter-cerebral and heartbeats synchronization analyses could be integrated with other methodologies, such as polygraphs, to better understand the behavior and physiological reactions during interviews or interrogations to assess deception. This could be useful for interpreting behavioral cues during investigative interviews and provide insights to improve interview management techniques, helping investigators detect signs of discomfort and tension associated with lying. Data availability statement The data are available upon request from the corresponding author . The data are not publicly available for privacy reasons: questionnaires and recordings contain information that could compromise participants’ privacy. The EEG analysis codes are publicly available: DOI 10.17605/OSF.IO/D2U3C. Funding statement The study received funding from the PON R&I (research and innovation) programme 2014–2020 under a grant agreement by the Italian Ministry of University and Research (MUR), D.M. n. 1061, 10/08/2021, and from Sapienza, “Progetti per Avvio alla Ricerca - Tipo 1”, protocol number: AR1221816C5BCD51. Conflict of interest disclosure The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethics approval statement The present study was approved by the Ethics Committee of the Department of Dynamic and Clinical Psychology, and Health Studies, Sapienza University (protocol number: 0000589). CRediT authorship contribution statement Conceptualization: GV, CL. Data curation: GV, FL. Formal analysis: GV, CL. Funding acquisition: GV, CL. Investigation: GV, FL. Methodology: GV, CL, EG. 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Keywords deception eeg heartbeats hyperscanning interbrain synchronization Authors Affiliations Giorgio Veneziani Universita degli Studi di Roma La Sapienza Dipartimento di Psicologia Dinamica Clinica e Salute View all articles by this author Federica Luciani Universita degli Studi di Roma La Sapienza Dipartimento di Psicologia Dinamica Clinica e Salute View all articles by this author Emanuele Giraldi Universita degli Studi di Roma La Sapienza Dipartimento di Psicologia Dinamica Clinica e Salute View all articles by this author Virginia Campedelli Universita degli Studi di Roma La Sapienza Dipartimento di Psicologia Dinamica Clinica e Salute View all articles by this author Carlo Lai 0000-0002-7638-0375 [email protected] Universita degli Studi di Roma La Sapienza Dipartimento di Psicologia Dinamica Clinica e Salute View all articles by this author Metrics & Citations Metrics Article Usage 529 views 273 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Giorgio Veneziani, Federica Luciani, Emanuele Giraldi, et al. 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