High trait anxiety is associated with increased sensitivity to self-face: an event-related potential study

High trait anxiety is associated with increased sensitivity to self-face: an event-related potential 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 Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed.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. 27 October 2025 V1 Latest version Share on High trait anxiety is associated with increased sensitivity to self-face: an event-related potential study Authors : Rui-ting Zhang 0000-0002-8293-4979 , Yao-han Cai , Wenjie Li , and Jie Chen [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176157215.50810040/v1 104 views 72 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Trait anxiety is a vulnerable factor for psychiatric disorders. Evidence suggests that trait anxiety is associated with cognitive bias toward negative stimuli. However, whether the trait anxiety would affect the self-face recognition remains unclear. This study aimed to investigate behavioral and neural mechanisms of self-face recognition in individuals with high trait anxiety. Twenty-six individuals with high trait anxiety (HTA) and 26 individuals with low trait anxiety (LTA) were recruited via screening with the Chinese version of the State-Trait Anxiety Inventory-Trait (STAI-T). Event-related potentials (ERPs) were recorded while participants completed an implicit face orientation identification task. Results showed that, across all participants, the N170 amplitude was larger for stranger-faces than self-faces or friend-faces, and the N2 amplitude was more negative for friend-faces and stranger-faces than self-faces. Moreover, self-faces elicited larger P3 amplitudes than friend-faces and stranger-faces in the HTA, whereas in LTA, self-faces and friend-faces evoked comparable P3 amplitudes, both larger than stranger-faces. The HTA showed comparable behavioral performance in relative to the LTA. These findings suggest trait anxiety modulates the late, rather than early, stages of self-face recognition. The P3 component may serve as a sensitive neural marker for early detection of anxiety-related disorders, supporting the transdiagnostic relevance of self-impairments in psychiatric risk research. High trait anxiety is associated with increased sensitivity to self-face: an event-related potential study Rui-ting Zhang 1,2,3# , Yao-han Cai 1# , Wenjie Li 1 , Jie Chen 1,2,3 * School of Educational Science, Hunan Normal University, Changsha, China Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, China 3. Institute of Interdisciplinary Studies, Hunan Normal University #These authors contributed equally to the study *Corresponding authors: Jie Chen, [email protected] School of Educational Science, Hunan Normal University, Changsha 410081, China. Abstract Trait anxiety is a vulnerable factor for psychiatric disorders. Evidence suggests that trait anxiety is associated with cognitive bias toward negative stimuli. However, whether the trait anxiety would affect the self-face recognition remains unclear. This study aimed to investigate behavioral and neural mechanisms of self-face recognition in individuals with high trait anxiety. Twenty-six individuals with high trait anxiety (HTA) and 26 individuals with low trait anxiety (LTA) were recruited via screening with the Chinese version of the State-Trait Anxiety Inventory-Trait (STAI-T). Event-related potentials (ERPs) were recorded while participants completed an implicit face orientation identification task. Results showed that, across all participants, the N170 amplitude was larger for stranger-faces than self-faces or friend-faces, and the N2 amplitude was more negative for friend-faces and stranger-faces than self-faces. Moreover, self-faces elicited larger P3 amplitudes than friend-faces and stranger-faces in the HTA, whereas in LTA, self-faces and friend-faces evoked comparable P3 amplitudes, both larger than stranger-faces. The HTA showed comparable behavioral performance in relative to the LTA. These findings suggest trait anxiety modulates the late, rather than early, stages of self-face recognition. The P3 component may serve as a sensitive neural marker for early detection of anxiety-related disorders, supporting the transdiagnostic relevance of self-impairments in psychiatric risk research. Keywords: trait anxiety, self-face recognition, P3, N170, N2 Introduction Trait anxiety is a stable personality trait which was characterized as showing excessive worry and fear in a variety of situations (Hein et al., 2023). Trait anxiety can impair daily performance and understanding its cognitive roots may benefit the strategies to improve social functioning. More importantly, trait anxiety has been considered as a vulnerable factor of psychiatric disorder, studying its’ cognitive signatures can help develop more precise diagnostic tools to identify at-risk individuals. Accumulated studies have explored the cognitive features of trait anxiety, such as attention (Qiao, Pan, Hoid, van Winkel, & Li, 2022), aversive reversal learning (Zika, Wiech, Reinecke, Browning, & Schuck, 2023), and decision making (Xu et al., 2013). However, only few studies focused on the maladaptive self-processing in trait anxiety. Indeed, individuals with trait anxiety demonstrated maladaptive self-processing, and this maladaptation may contribute the development of clinical anxiety disorders (Nordahl, Hjemdal, Hagen, Nordahl, & Wells, 2019; Shimura et al., 2017). Investigating the abnormal self-processing in individuals with trait anxiety would benefit the early identification and prevention of clinical psychiatric disorders. Self-face recognition refers to the ability to recognize one’s own face and distinguish the self from others (Sugiura, 2015). Self-face recognition is profoundly important to human beings, as it underpins our sense of self, enables social interaction, and contributes to cognitive and psychological development (Sugiura, 2015). Impaired self-face recognition may affect the typical development of human being, and it was found that impairments in self-face recognition was associated with various kinds of mental disorders (Gallup & Platek, 2021; Kita et al., 2011; Liu et al., 2022). Individuals with first-episode major depressive disorder showed reduced activations in prefrontal cortex, fusiform gyrus, and insula during self-face recognition (Fan et al., 2023), and similar patterns were found in depressed adolescents (Quevedo et al., 2018; Quevedo et al., 2016), suggesting that maladaptive functions in neural areas that support emotional processing may contribute to the dysfunctional self-face recognition in depressive patients. Moreover, schizophrenia patients demonstrated higher error rates when identifying self-face compared with controls, and their impaired self-face recognition performance was related to the severity of hallucinations (Kircher, Seiferth, Plewnia, Baar, & Schwabe, 2007). However, increased brain activations were observed in individuals with anxiety disorders when they viewing their own faces. For instance, Pujol et al. (2013) found that individuals with social anxiety disorders showed significant greater activations in the primary visual cortex during self-face recognition in relative to controls. Moreover, Kim, Yoon, Shin, Lee, and Kim (2016) reported that individuals with social anxiety disorders demonstrated increased inferior frontal activity when evaluating the attractively transformed self-faces, suggesting they may have difficulties and thus need more effort to recognize self-face. As such, impaired self-face recognition was associated with various kinds of mental disorders, which may hold potential as the marker for further understanding of psychiatric psychopathology from a transdiagnostic perspective. However, it remains unclear whether individuals with trait anxiety have distinct patterns in processing self-face recognition. Previous literature has documented that individuals with trait anxiety showed altered self-relevant processing (Chen et al., 2023; Saunders, 2013). It was found that individuals with trait anxiety had troubles in forgetting self-descriptive negative traits, but showed intact performance for neutral traits (Saunders, 2013). Moreover, a recent ERP study found that individuals with high trait anxiety were more sensitive to self-relevant stimuli, as they distinguished self-relevant stimuli (e.g., “self”) and non-self-relevant stimuli (e.g., “friends” and “stranger”) at the earlier N1 and P2 stages, and this effect was not observed in individuals with low trait anxiety (Chen et al., 2023). In light of previous literature, we hypothesized that individuals with trait anxiety would be more sensitive in self-face recognition, in relative to controls. Since the self-face recognition is sensitive to temporal processing, a methodology that reveals the time course might provide more detailed insight into the underlying mechanism of the relationship between trait anxiety and self-face recognition. Event-related potential (ERPs) is a temporally sensitive technique that has the advantage of millisecond time resolution and is particularly suited to evaluate the temporal features of face recognition (Alzueta, Kessel, & Capilla, 2021; Kotlewska, Panek, Nowicka, & Asanowicz, 2023). Previous studies have reported that the N170/VPP, N2, and P3 were key components of self-face recognition(Bentin, Sagiv, Mecklinger, Friederici, & von Cramon, 2002). Earlier studies found that N170 at the occipital-temporal sites and VPP at the fronto-central sites were important ERP component in response to face processing (Jemel et al., 2003; Joyce & Rossion, 2005), as larger N170/VPP amplitude was elicited for viewing faces than houses (Gao, Conte, Richards, Xie, & Hanayik, 2019). Recently, some studies have reported that the N170/VPP were also sensitive to self-face processing (Geng, Zhang, Li, Tao, & Xu, 2012; Keyes, Brady, Reilly, & Foxe, 2010). The N2 amplitude is considered as an ERP component to indicate self-related processing, and has been used to measure the advantage of self-relevant information, such as one’s own name (Chen et al., 2011) and own face (Keyes et al., 2010). Besides, previous studies have found that larger P3 amplitude was associated self-face than others face (Cygan, Nowicka, & Nowicka, 2022). Moreover, it was reported that the P3 amplitude decreased as the self-relevance of the stimulus decreases (Zhu et al., 2018). As can be seen, the N170/VPP, N2, and P3 were crucial components of the self-relevant processing. Importantly, although no alterations was detected in terms of N170, previous literature has demonstrated that individuals with trait anxiety showed altered N2 and P3 during multiple cognitive processing such as inhibition (Xia, Mo, Wang, Zhang, & Zhang, 2020) and visual processing (Faerman, Ehgoetz Martens, Meehan, & Staines, 2025). Therefore, it is possible that individuals with trait anxiety would show distinct N2 and P3 which may contribute to their maladaptive self-face recognition. The present study aimed to investigated the behavior performance and the behind neural mechanisms of self-face recognition in individuals with trait anxiety, using implicit self-face recognition paradigm and event-related potentials (ERP). Since individuals with trait anxiety was sensitive to self-relevant stimuli (Chen et al., 2023), we hypothesized that individuals with trait anxiety would show hyper-sensitive to self-face recognition. Moreover, as some of previous studies revealed that individuals with trait anxiety distinguished self-relevant stimuli at earlier stages (e.g., N1 and P2), while some other studies demonstrated that individuals with trait anxiety showed altered cognitive processing at later stages (e.g., N2, P3), we hypothesized that individuals with trait anxiety would show detectable changed ERP components during self-face recognition. 2. Methods 2.1 Participants The experiment was a 2 (Group: high trait anxiety vs. low trait anxiety) × 3 (Stimulus: self vs. friends vs. strangers) within-between mixed design. A power analysis conducted by G-power indicated that 22 participants for each group was required to detect a medium effect size ( η p 2 = 0.06; effect size f = 0.25) with 95% power and an alpha level of 0.05. A total of 1200 young adults were enrolled in our pre-screened and completed the Chinese version of the State Trait Anxiety Inventory-Trait (STAI-T). Participants who scored above the 25 th percentage of the STAI-T or below the 25 th percentage of the STAI-T were invited into the high trait anxiety (HTA) group and low trait anxiety (LTA) group, respectively. Fifty-eight participants were willing to join in our study. Six of them were excluded due to the low quality of EEG data (e.g., excessive artifacts). The final sample included 26 participants with HTA (10 males; mean age = 20.35 ± 1.74; mean STAI-T score = 50.08 ± 5.22) and 26 participants with LTA (7 males; mean age = 20.31 ± 1.62; mean STAI-T score = 30.46 ± 3.22). All of them were right-handed, had normal or corrected to normal vision, and had no brain injury and no neurological or psychiatric disorders. Our study was approved by the ethics committee of our university, and informed consent was obtained at the beginning of the study. 2.2 Materials Before the formal experiment, participants were required to bring a same-sex friend or roommate who they had lived together for more than one year to the lab. Moreover, another two participants (1 male and 1 female) who were unknown to all participants, were also invited to join in our study. Research assistant took photos for each volunteer (e.g., participant, participants’ same-sex friend, and two “strangers”). For each person, ten photos were taken from different angles, five facing left, five facing right, from 30 to 70 degrees. Ten photos of each participant were used as self-face stimuli, ten photos of participants’ friend were used as friend-face stimuli, and ten photos of unfamiliar participants were used as stranger-face stimuli. During the photo shoot, all participants were asked to keep their expression neutral, and not to laugh or frown. Finally, all face images were corrected for brightness and contrast, and the resolution was converted into a uniform 240 *330 pixel. Each image stimulus was displayed on a 17-inch color display and presented at a viewing distance of 60 cm from 2.13° × 2.17°(width * height). 2.3 Procedure All participants were tested individually in a quiet environment. Participants were required to determine the orientation of each face and ignore the identification of each face. The implicit face orientation identification paradigm has three conditions (e.g., self-face, friend-face, or stranger-face) and each condition has 60 trials. Therefore, there were 180 trials in total. The procedure of each trial was presented in Figure 1a. For each trial, it started with a fixation for 500 ms, following by a blank screen randomly lasting for 600-1000 ms. After that, face stimuli (e.g., self-face, friend-face, stranger-face) were presented for 200 ms, and then an interval was presented for 1000ms during which participants had to perform a “right” or “left” response by pressing “A” or “L” key with the left or right index finger. Finally, the blank screen of 1000 ms was shown at the end of each trial to help participants to return to the baseline level after each judgement. Participants were given a break to prevent their fatigue after randomly presenting half of the trials. Figure 1. Illustration of the face orientation identification task. A: The flowchart of a single trail; B: the example trial of self-face; C: the example trial of friend-face; D: the example trial of stranger-face. 2.4 EEG recordings and data analysis The EEG was recorded from 64 tin electrodes installed in the elastic cap, using the international positioning standard of 10-20 system and Neuroscan ERP Series Technology. The continuous sampling rate was 500 Hz/channel. The central parietal lobe electrode-CPz and the medial frontal grounding electrode were taken as the online reference, and the inter-electrode impedance was remained below 5kΩ during online recording. 2.5 Data processing and analysis For behavioral data analysis, the percentage of correct face categorization (ACC) and response time (RT) were used as dependent variables to indicate the ability of self-face recognition. Only trials with correct responses were included to calculate the RT. Repeated measures analysis of variance (ANOVA) with Group (HTA/LTA: between-subject factor) and Face types (self vs. friend vs. stranger: within-subject factor) were performed for ACC and RT, separately. EEG data analysis was performed by the EEGLAB (Version 14.1.1; Delorme & Makeig, 2004) and ERPLAB (Version 6.1.4; Lopezcalderon & Luck, 2014) in MATLAB R2014a. All the data were referenced on the basis of activity on bilateral mastoid offline. The EEG data were filtered by using a bandpass of 0.1-30 Hz, with a gentle slope of 12dB/octave. By evaluating the spatial and temporal characteristics of each component, independent component analysis (ICA) was used to remove eye-blinks, saccades, and other consistent artifacts (Mognon et al., 2011). The time window for EEG data was 1000ms (200ms pre-stimulus, 800ms post-stimulus). Time window and 200ms baseline-corrected were both accorded to the onset of the face stimulus. Simple voltage deflection exceeding ±80 μV were excluded from further analysis, and subjects were excluded if they have more than 25% artifact trials. EEG waveforms were then sorted with respect to condition and grand-averaged to create ERPs for each participant. According to the topographic maps and grand-average ERP wave (Luck, 2014; Luck & Gaspelin, 2017), the averaged amplitudes of the N170 (170-230ms) component were measured at occipito-parietal region (P7/8,PO7/8), the VPP (170-230ms) and N2 (270-320ms) were measured at the frontal and fronto-central regions (F3/z/4,FC3/z/4), and the P3 (360ms-460ms) were measured at central (C3/z/4), central-parietal (CP3/z/4) and parietal (P3/z/4) electrodes. Repeated measures analysis of variance (ANOVA) with Group (HTA/LTA: between-subject factor) and Face types (self vs. friend vs. stranger: within-subject factor) were performed for the amplitude of N170, VPP, N2, and P3, respectively. The data analysis was performed in the SPSS 25.0 and degrees of freedom of the F-ratio were corrected according the Greenhouse-Geisser method. False discovery rate (FDR) correction was applied for post-hoc multiple comparisons. 3. Results 3.1 Behavioral performance No significant main effect of Face type (ACC: F(1.53, 76.26) = 0.22, p = 0.743, η p 2 = 0.004; RT: F(2, 100) = 0.43, p = 0.654, η p 2 = 0.008), Group effect(ACC: F(1, 50) = 0.26, p = 0.612, η p 2 = 0.005; RT: F(1, 50) η p 2 < 0.001) nor interaction effect of Group × Face type (ACC: F(1.53, 76.26) = 3.37, p = 0.052, η p 2 = 0.063; RT: F(2, 100) = 1.69, p = 0.189, η p 2 = 0.033) were observed for ACC and RT. Table 1. The descriptive information of ACC and RT under different conditions. Mean SD Mean SD Stranger-face HTA 0.97 0.04 216.62 81.36 LTA 0.99 0.02 210.40 60.75 Self-face HTA 0.97 0.06 213.66 70.00 LTA 0.98 0.02 216.94 67.28 Friend-face HTA 0.98 0.02 211.72 68.29 LTA 0.96 0.08 213.83 57.67 Note: ACC: accuracy; RT: reaction time; HTA: high trait anxiety; LTA: low trait anxiety. 3.2 ERP performance N170/VPP components. ANOVA over N170 amplitude showed a significant main effect of Face type [F(2, 100) = 4.99, p = 0.009, η p 2 = 0.091], as stranger-face (-0.532 μV) elicited larger negative N170 amplitude than self-face (-0.198 μV, p = 0.024) and friend-face (-0.132 μV, p = 0.004). However, the N170 amplitude induced by the self-face did not significantly differ from the N170 amplitude elicited by friend-face ( p = 0.612). No significant Group effect or interaction effects were observed on the N170 amplitudes ( ps > 0.19). ANOVA over VPP amplitude revealed a significant main effect of Face type [F(2, 100) = 3.08, p = 0.05, η p 2 = 0.058], as friend-face (4.677 μV) elicited larger VPP amplitude than stranger-face (4.138 μV, p = 0.027). However, the VPP amplitude elicited by the self-face (4.469 μV) did not significantly differ from the VPP amplitude evoked by friend-face (4.677 μV, p = 0.321) or stranger-face (4.138 μV, p = 0.126). No significant Group effect, or interaction effect were found for the VPP amplitudes ( ps > 0.406). Figure 2. Grand averaged ERP waveforms from the right posterior area including P8 and PO8, grand averaged ERP waveforms from the left posterior area including P7 and PO7. N2 amplitude. ANOVA over N2 amplitude revealed a significant main effect of Face type [F(2, 100) = 11.53, p < 0.001, η p 2 = 0.187], as friend-face (0.076 μV, p = 0.001) and stranger-face(-0.162 μV, p < 0.001) elicited more negative N2 waves than did self-face (1.077 μV). However, no N2 difference was observed between the friend-face and stranger-face ( p = 0.31). In addition, no group effect or interaction effect were observed for the N2 amplitude ( ps > 0.377). P3 amplitude. ANOVA over P3 amplitude indicated a significant main effect of Face type [F(2, 100) = 18.27, p < 0.001, η p 2 = 0.268], as larger P3 amplitudes was induced by self-face (5.757 μV) than by the friend-face (4.926 μV, p = 0.008), and P3 amplitude elicited by friend-face was larger than the P3 amplitude elicited by stranger-face (4.046 μV, p = 0.002). Moreover, a significant interaction effect of Group and Face type was found [F(2, 100) = 3.48, p = 0.036, η p 2 = 0.065]. Further analysis revealed that in the HTA group, larger P3 amplitude was elicited by self-face (6.732 μV), compared with friend-face (5.309 μV; p = 0.002) and stranger-face (4.332 μV; p < 0.001), and moreover, friend-face (5.309 μV) induced larger P3 amplitude than stranger-face (4.332 μV; p = 0.013). In the LTA group, both self-face (4.782 μV, p = 0.012) and friend-face (4.542 μV, p = 0.046) evoked larger P3 amplitude than stranger-face (3.781 μV), while the P3 amplitude elicited by self-face was not significantly differ than that elicited by friend-face ( p = 0.579). The self-face processing bias indexed by the P3 difference between the self-face and stranger-face conditions was larger in HTA than in LTA groups [ t = 2.51, df = 50, p = 0.016, Cohen’ d = 0.71]. We also tried the simple effect analysis from another perspective and results showed that the HTA group demonstrated larger P3 amplitude in response to self-face (6.732 μV), compared with the LTA group (4.782 μV, p = 0.023). However, the HTA group and the LTA group demonstrated comparable P3 amplitude in response to friend-face ( p = 0.368) and stranger-face ( p = 0.466). As such, results of simple effect analysis suggested that the group difference was only observed in self-face condition (e.g., the HTA group showed enhanced P3 amplitude compared to the LTA group) but not found in friend-face or stranger-face condition. Figure 3. Grand averaged ERP waveforms from anterior ROI area including F3, Fz, F4, FC3, FCz and FC4, grand averaged ERP waveforms from posterior ROI area including F3, Fz, F4, FC3, FCz and FC4. The map of terrain difference of grand averaged ERP amplitude of N2 in the anterior ROI area is that of N2 the anterior ROI area induced by self-face minus N2 in the anterior ROI area induced by friend-face, and N2 in the anterior ROI area induced by self-face minus N2 in the anterior ROI area induced by stranger-face. The map of terrain difference of grand averaged ERP amplitude of P3 in the posterior ROI area is that of P3 the posterior ROI area induced by self-face minus P3 in the posterior ROI area induced by friend-face, and P3 in the posterior ROI area induced by self-face minus P3 in the posterior ROI area induced by stranger-face. 4. Discussion The present study aims to identify the distinct pattern of the behavioral performance and neural correlates of self-face recognition in individuals with trait anxiety, using the face orientation identification task together with ERP. It was found that the ability of self-face recognition was behaviorally intact in individuals with HTA, however, in the HTA group, the P3 amplitude induced by self-face was significantly larger than the P3 amplitude induced by friend-face, and this difference was not found in the LTA group. For ERP components, the N170 amplitude induced by the stranger-face was significantly larger than the N170 amplitude evoked by friend-face and self-face. These findings supported previous findings that the amplitude of N170 was differed in self-face processing in relative to other-face processing (Geng et al., 2012; Keyes et al., 2010). For instance, the N170 amplitude was found distinguishable between self- and other-face processing (Keyes et al., 2010). Moreover, Geng et al. (2012) also found that the amplitude of the N170 differentiated the self-face from other-face processing. Therefore, in together with previous findings, these findings indicated that the N170 not merely reflected structural encoding of faces as oppose to non-faces, but was also involved in person-identify discrimination in face recognition. On the other hand, the replication of previous findings also suggested that the paradigm adopted in our study was valid and able to detect the effect of Face type. For the N2 component, the main effect of Face type was significant as friend-face and stranger-face elicited more negative N2 amplitude than did self-face. This result supported previous findings that the N2 amplitude were more negative for processing friend’s face compared with self-face (Guan, Qi, Zhang, & Yang, 2014). Moreover, smaller N2 amplitude was found when processing self-relevant cues in relative to others-relevant cues (Keyes et al., 2010; Woźniak, Kourtis, & Knoblich, 2018). suggesting that the N2 amplitude was also a sensitive ERP component in distinguishing self-face stimuli from others-face stimuli. In addition, the N2 reflects the processing of response inhibition (Hoyniak & Petersen, 2019) and smaller N2 amplitude may indicate better attention performance (Dennis & Chen, 2009). In light of previous literature, people tended to pay more attention and devoted less cognitive effort to self-relevant information compared with other information (Humphreys & Sui, 2016), the reduced N2 amplitude in response to self-face may suggest that self-face, as a self-relevant information, captured attention easier than friend’s face and stranger-face, which further supported the argument for the self-bias in cognitive processing. Given that there were no group effect or interaction effect were observed in terms of N170 and N2, it is possible that the group difference has not been shown at early stage of self-face recognition. For the P3 component, it was found that the P3 amplitude evoked by the self-face was significantly larger than did friend-face and stranger-face. Moreover, the P3 amplitude evoked by the friend-face was significantly larger than did stranger-face, revealing that the P3 component was more sensitive to self and familiar face in relative to unfamiliar faces. This finding was also in accordance to previous literature which delineated that the P3 component indicated the effect of self-referential processing (Cygan et al., 2022; Zhu et al., 2018). More importantly, an interaction effect of Face type and Group was identified. Further analysis revealed that, only in the HTA group, the self-face elicited larger P3 amplitude than did the friend’s face, while the self-face and friend-face evoked similar amplitude of P3 component in the LTA group. However, the pattern that stranger-face elicited significantly smaller P3 amplitude than did the self-face and friend-face were observed in both groups. These findings suggested that the trait anxiety affect the late stages, instead of early stages, of self-face recognition, by shaping, or increasing, the sensitivity in distinguishing self-faces from friend’s face. Our results were in line with previous literature which reported that individuals with high trait anxiety have a processing bias to self-relevant stimuli (Chen et al., 2023). However, in Chen et al. (2023)’s study, the Chinese word of “self”, “friend” and “others” was adopted as stimuli and they found that individuals with high trait anxiety distinguished self-relevant and non-self-relevant stimuli at an earlier stage, as indicated by altered N1 and P2 amplitude. Whereas in our study, self-face, friend-face, and stranger-face were used as stimuli and the alteration was observed in later stages (e.g., P3 amplitude). Taken together, these findings revealed that the trait anxiety do affect the processing of self-relevant information, and the affection might be varied depending on the type of stimuli. Given that the P3 amplitude reflected attention allocated to the targeted stimuli(Tetik, Gica, Bestepe, Buyukavsar, & Gulec, 2022), the increased P3 amplitude may indicate more attention sources were involved during self-face recognition (Pei, Xiao, Pan, Li, & Jin, 2023). For instance, previous studies found that individuals with high social anxiety showed greater P3 amplitude than controls when processing threatening faces, and this findings were interpreted as individuals with social anxiety may have attentional bias toward processing negative faces (Moser, Huppert, Duval, & Simons, 2008). Similarly, the heightened P3 amplitude observed in the HTA may suggest that individuals with trait anxiety need to pay more attention to the in the processing of self-face. It should be noted that, although individuals in the HTA demonstrated altered P3 amplitude during the late stages, their behavioral performance remained intact. This incongruence between neural signals and behavioral performance could be interpreted as a compensatory mechanism(Eysenck, Derakshan, Santos, & Calvo, 2007). Eysenck et al. (2007) proposed the assumption that anxious individuals could adopt compensatory strategies (e.g., enhancing effort, using processing resources) to maintain the effectiveness, although the processing efficiency was impaired as they exerting greater effort but only achieved comparable performance(Eysenck et al., 2007). This assumption was supported by empirical evidence as individuals with high trait anxiety demonstrated larger N2 amplitude for conflict detection but showed intact behavioral performance(Yu et al., 2018). Moreover, a recent study also reported that trait anxiety score was significantly associated with increased P3 amplitude during attention but not correlated with behavioral performance (Faerman et al., 2025), suggesting that individuals with trait anxiety tend to show comparable behavioral performance because of compensatory increases in neural effort (Eysenck et al., 2007; Faerman et al., 2025). Therefore, in our study, the HTA group may need more cognitive effort (e.g., attention) in distinguishing self and other face to keep their intact behavioral performance. In other words, individuals with high trait anxiety may have subtle impairments in the process of self-face recognition, which cannot be observed at behavioral level, but can be detected in terms of P3 amplitude. As such, the P3 amplitude may be a sensitive biological marker for the early detection of anxiety disorders. Indeed, the P3 has been regarded as a well-established endophenotypes for psychosis, as altered P3 amplitude was found in unaffected relatives of patients and individuals at clinical high risk (Wang, Zartaloudi, Linden, & Bramon, 2022). Taken together, our results suggested that the self-referential processing was also changed in individuals with trait anxiety, and these results provided further empirical evidence for the research domain criteria (RDoC) framework that self-impairments were transdiagnostically existed in different types of psychiatric disorders (Insel et al., 2010; Sui & Gu, 2017). There were several limitations need to be addressed in our study. First, we only recruited individuals with trait anxiety, instead of clinical anxiety patients, wherefore they may persist intact performance and thus we were unable to detect the group difference. Future study would include both clinical and subclinical participants and to investigate how the self-face recognition ability changed with the development of anxiety. The second limitation was that we only used ERP to evaluate the neural basis, which may be limited to measuring neural activation from spatial perspective. Future research could combine the ERP together with functional MRI to systematically investigate the neural mechanism of self-face recognition in individuals with anxiety. To conclude, our study found that N170/VPP, N2 and P3 were sensitive to self-face processing. More importantly, it was observed that P3 amplitude was modulated by the level of trait anxiety, suggesting that trait anxiety may affect the late stages of self-face recognition and increase the sensitivity in distinguishing self-faces from friend’s face. 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