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. 2026 Jul 31;63(8):e70374. doi: 10.1111/psyp.70374

Dissociated in Anticipation, Common in Feedback: Neuroelectrophysiological Mechanisms of Social‐Motivational Processing in Bivalent Evaluation Fears

Rui Zhang 1, Jinhong Ding 1,✉
PMCID: PMC13428241  PMID: 42538808

ABSTRACT

The Bivalent Evaluation Fear Hypothesis posits that fear of positive evaluation (FPE) and fear of negative evaluation (FNE) are two independent core characteristics of social anxiety. However, whether they rely on dissociable and/or shared neural mechanisms in the processing of social motivation remains unclear. By employing the Social Incentive Delay Task combined with EEG, we found that during the anticipation phase, individuals with high FPE exhibited “generalized over‐engagement toward evaluative situations”—enhanced conflict monitoring (N2) and motivational preparation (CNV) in response to both reward and punishment cues. In contrast, individuals with high FNE displayed “specific threat vigilance with generalized motivational withdrawal”—demonstrating enhanced N2 specifically to punishment cues, along with reduced CNV to both reward and punishment cues, consistent with a profile of defensive motivational inhibition. During the feedback phase, neither group exhibited the positive‐over‐negative feedback effect observed in the control group, with reduced delta and theta oscillations in response to socially accepting feedback, suggesting a possible commonality in deep reward integration. These findings demonstrate that FPE and FNE are associated with distinct neuro‐affective preparatory patterns during anticipation: one characterized by a generalized, vigilant over‐mobilization, and the other by specific threat vigilance coupled with a generalized reduction in motivational engagement. At the same time, the similar delta and theta patterns during feedback may reflect a common difficulty in translating positive social outcomes into adaptive motivational behaviors. This study deepens our understanding of evaluation fears and provides critical neural evidence in support of the Bivalent Evaluation Fear Hypothesis.

Keywords: bivalent evaluation fear, ERP, fear of negative evaluation, fear of positive evaluation, social motivation

Impact

Our study first reveals dual neural signatures of FPE and FNE in social motivational processing: dissociable anticipatory patterns (generalized over‐vigilance and preparation vs. specific threat vigilance with motivational withdrawal) and a convergent feedback pattern (δ/θ attenuation during reward integration). This provides key evidence for the Bivalent Evaluation Fear Hypothesis.

1. Introduction

Fear of Negative Evaluation (FNE) is central to the cognitive‐behavioral model of Social Anxiety Disorder (SAD) (Heimberg et al. 2014) and constitutes a core clinical feature of SAD, as reflected in the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM‐5; American Psychiatric Association 2013). However, recent studies suggest that persistent fears in SAD encompass not only fear of negative evaluation but also fear of positive evaluation (FPE; Rodebaugh et al. 2012; Weeks et al. 2008). FPE refers to the apprehension and distress associated with receiving positive evaluations from others (Weeks and Zoccola 2015).

Two primary theoretical accounts have been proposed to explain FPE. The Delay Theory posits that FPE represents a delayed form of FNE, originating from concerns about being unable to meet heightened expectations following positive evaluations, which ultimately reverts to fear of negative appraisal. In other words, FPE is rooted in FNE, suggesting a causal pathway from FNE to FPE (Rodebaugh et al. 2012). In contrast, the Bivalent Fear of Evaluation Hypothesis proposes that FNE and FPE are related yet distinct constructs within SAD (Weeks and Howell 2012, 2014). Drawing on an evolutionary psychology perspective, this hypothesis posits that individuals tend to perceive social environments as hierarchical structures and seek to maintain stable social standing. Within this framework, FNE arises from the fear of status loss, whereas FPE stems from the fear that status elevation may provoke social conflict or excessive attention (Cook et al. 2019; Reichenberger and Blechert 2018). A robust body of psychometric and experimental evidence supports the distinction between these two constructs (e.g., Zhang et al. 2023; Fredrick and Luebbe 2022; Cook et al. 2022). While FNE is primarily associated with aversive responses to negative social stimuli, FPE has been linked to similar aversive reactions to positive social stimuli (Reichenberger et al. 2015; Weeks et al. 2013).

Neuroimaging research has further elucidated the neural circuits associated with FPE and FNE. For example, Birk et al. (2019) utilized a task‐based fMRI paradigm and found that FNE scores were correlated with activity in the amygdala and insula—a finding subsequently corroborated by Feng et al. (2022). The amygdala and medial prefrontal cortex (mPFC) constitute key nodes of the “fear circuit” (Marek et al. 2013) and are widely regarded as critical to anxiety (Mizzi et al. 2022). Bishop (2007) proposed that threat‐related anxiety responses arising from the amygdala are modulated by top‐down regulation from the mPFC. Consequently, excessive anxiety is associated with amygdala hyperreactivity and frontal hypoactivity. The ventral striatum, a core region of the brain's reward system including social rewards, also exhibits aberrant activation in individuals with SAD (Becker et al. 2017). Meanwhile, the ventromedial prefrontal cortex (vmPFC) is implicated in socio‐cognitive and affective functions, particularly in value‐based reward processing (Hiser and Koenigs 2018). Zhang et al. (2023) reported a positive correlation between FPE and fractional amplitude of low‐frequency fluctuations (fALFF) in the vmPFC, and demonstrated that the association between vmPFC activity and SAD symptoms was fully mediated by FPE. This aligns with earlier work by Qiu et al. (2015), who observed increased ALFF in the vmPFC among individuals with SAD. Furthermore, Tian et al. (2016) found that vmPFC ALFF positively predicted individual differences in trait anxiety. According to Weeks and Howell (2012), whose Bivalent Fear of Evaluation Hypothesis conceptualizes positive evaluation as a social competition threat, elevated vmPFC fALFF may impair the ability to receive and encode socially rewarding feedback, thereby contributing to FPE and subsequently exacerbating SAD symptoms (Zhang et al. 2023). Importantly, diminished positive affect and impaired processing of social rewards are considered key maintaining mechanisms in SAD (Carlton et al. 2023; Richey et al. 2019). These observations are consistent with the broader conceptualization of SAD as involving a compromised motivational system, characterized by reduced approach motivation and heightened avoidance motivation (Cremers et al. 2015; Goodman et al. 2021). Collectively, these findings suggest that FPE and FNE may correspond to dissociable functional impairments within the neural circuitry of motivation.

However, crucial behavioral and cognitive evidence reveals that the processing patterns associated with FPE are far more complex than a mere “hypofunction of the reward system.” Research has found that individuals with high FPE not only struggle to derive pleasure from positive feedback but also exhibit maladaptive responses to negative feedback (Weeks et al. 2010). They tend to broadly avoid various social evaluation situations, regardless of whether the potential evaluation is positive or negative (Weeks and Howell 2014). Similarly, in an experimental study, Sluis and Boschen (2014) found that the effect of social anxiety on attentional avoidance of angry faces was explained by FPE in a sample with moderate to high social anxiety. Higher FPE in undergraduates was associated with increased self‐monitoring through heightened self‐consciousness across public, private, and social anxiety‐specific contexts (Weeks and Howell 2012). Neuroimaging research further provides key insights: individuals with high FPE do not show typical activation of reward circuits in response to positive social evaluation; instead, they exhibit increased activity in brain regions related to interoceptive awareness, such as the posterior insula (Miedl et al. 2016). This suggests that FPE may not reflect insensitivity to “reward” per se but rather a heightened vigilance and discomfort toward the internal physiological arousal states evoked by evaluation situations—particularly arousal induced by positive evaluations. Some scholars propose that another possible reason for FPE is a fear of standing out in any form (Wilson et al. 2023). Given that FPE and FNE are highly correlated constructs, recent research suggests they may reflect a higher‐order fear of the evaluation construct itself (Weeks et al. 2024).

The tensions within the existing evidence raise a fundamental unresolved question: Do FPE and FNE exhibit specific response patterns—with FNE selectively responsive to negative evaluation and FPE to positive evaluation—or do they reflect generalized patterns, whereby FPE drives excessive reactivity to all evaluative stimuli? More importantly, what are the proximal process mechanisms underlying these potentially distinct response profiles? We hypothesize that differences between FPE and FNE arise from fundamentally distinct motivational processes. For FPE, its theoretical core lies in the fear of the “spotlight of evaluation” itself (Weeks et al. 2008). This may result in a generalized vigilance toward the state of being evaluated. Specifically, any cue that clearly signals an impending entry into a socially evaluative situation—whether indicative of reward or punishment—may be marked as a highly salient event by the cognitive system, thereby triggering an alarm signal. In contrast, FNE is characterized by a specific fear of social threat, which likely engenders a state of motivational inhibition marked by vigilance toward punishment cues coupled with downregulated behavioral preparedness to minimize risk. The present study therefore aims to investigate whether FPE and FNE rely on dissociable and/or shared neurophysiological mechanisms during dynamic social motivational processing.

To test these theoretical predictions regarding response patterns—specifically, whether they are generalized versus specific—and the underlying process mechanisms of motivational conflict versus inhibition, we employed electroencephalography within a Social Incentive Delay Task (SID). This paradigm clearly separates the anticipation and feedback phases, making it an ideal tool for investigating motivational dynamics (Ait Oumeziane et al. 2019). Guided by theoretical frameworks of motivation and cognitive control, we focused on key electrophysiological markers during both phases. During the anticipation phase, we analyzed the cue‐N2, cue‐P3, and the contingent negative variation (CNV). The cue‐N2 reflects conflict monitoring between cues and expectations (Zhang et al. 2024; Novak and Foti 2015). The cue‐P3 indexes attentional allocation toward motivationally salient cues (Stim et al. 2023; Pornpattananangkul and Nusslock 2015). The CNV, in turn, is closely linked to anticipatory attention, motivational preparation, and motor mobilization (Catalano et al. 2022; Novak and Foti 2015). In the feedback processing phase, we examined the feedback‐related negativity (FRN) and the feedback‐P3 (FB‐P3), which are sensitive to reward prediction error and attentional engagement with motivationally significant outcomes, respectively (Guo et al. 2023; Zhou et al. 2025; Glazer et al. 2018). We also analyzed frontal theta and delta oscillatory activity during feedback. Theta oscillations are associated with cognitive control and surprise processing (Cavanagh and Shackman 2015), while delta oscillations are involved in deep reward evaluation and detailed outcome integration (Bernat et al. 2015).

Building on the above framework, we hypothesize that during the anticipation phase, individuals with high FPE will exhibit generalized over‐engagement, as reflected in enhanced N2 and CNV amplitudes to both reward and punishment cues, suggesting a conflicted mobilization of resources under motivational conflict. In contrast, individuals with high FNE will show specific threat vigilance accompanied by motivational withdrawal, characterized by enhanced N2 only to punishment cues alongside a reduced CNV, consistent with a pattern of motivational inhibition. During the feedback phase, based on the shared deficit in reward processing across the social anxiety spectrum, both groups are hypothesized to exhibit attenuated deep reward integration in response to positive feedback, as indicated by reduced delta and theta oscillations.

2. Methods

2.1. Participants

Approximately 415 undergraduate and graduate students from universities in Beijing, all of Asian descent, were screened using the Fear of Positive Evaluation Scale (FPES) and the Brief Fear of Negative Evaluation Scale–Straightforward Items (BFNE‐S). Given the moderate correlation between FPE and FNE (r ≈0.4; e.g., Fredrick and Luebbe 2020; Zhang et al. 2023), an extreme‐group design was applied to enhance trait distinction. Following the grouping rationale (scoring in the top 25% on one scale while below the top 25% on the other) of Lipton et al. (2016) but with stricter criteria, participants were classified as follows: the FPE group included those with FPES scores in the top 25% and BFNE‐S scores below the top 50%; the FNE group comprised those with BFNE‐S scores in the top 25% and FPES scores below the top 50%; and the control group consisted of individuals with both FPES and BFNE‐S scores in the bottom 25%. All participants had normal or corrected‐to‐normal vision, no color blindness, and no history of alcohol abuse, substance use, or mental illness. To control for potential confounds, participants with moderate‐to‐severe depression (BDI‐II > 20) were excluded.

A priori power analysis using G*Power 3.1 for a 3 (group) × 3 (incentive type) repeated‐measures ANOVA indicated a minimum sample size of 54, with α = 0.05, power (1 − β) = 0.95, and a medium effect size (f = 0.25). From the eligible pool, 72 right‐handed participants were recruited and evenly assigned to three groups (n = 24 each): the FPE group (7 males; mean age = 22.5, SD = 2.25), the FNE group (5 males; mean age = 21.71, SD = 2.51), and the control group (7 males; mean age = 22.13, SD = 2.56). Written informed consent was obtained from all participants, and the study was approved by the Ethics Committee of the Capital Normal University, CNU‐202412020.

2.2. Self‐Reported Measures

Each participant completed four questionnaires: (1) the Brief Fear of Negative Evaluation Scale–Straightforward Items (BFNE‐S) (Rodebaugh et al. 2011; Wei et al. 2015), an 8‐item measure of fear of negative evaluation (e.g., “I am afraid that others will not approve of me”) scored from 0 (not at all characteristic of me) to 4 (extremely characteristic of me); (2) the Fear of Positive Evaluation Scale (FPES) (Weeks et al. 2008; Zhang et al. 2023), a 10‐item scale assessing distress in response to positive social evaluation (e.g., “I feel uneasy when I receive praise from authority figures”) rated from 0 (not at all true) to 9 (very true); (3) the self‐report Liebowitz Social Anxiety Scale (LSAS‐SR) (Heimberg et al. 1999; He and Zhang 2004), which separately rates fear and avoidance across 24 social situations on a 0–3 scale; and (4) the Beck Depression Inventory‐II (BDI‐II) (Beck and Clark 1997; Wang et al. 2011), a 21‐item measure of depressive symptom severity rated from 0 to 3. Of note, we used a 0–4 response format for the BFNE‐S rather than the original 1–5 format. This adapted metric has been widely used in previous studies (e.g., Fredrick and Luebbe 2022; Zhang et al. 2023). Scores on these measures for three groups are presented in Table 1.

TABLE 1.

Self‐report questionnaire scores (BFNE, FPES, and LSAS) by group (mean and standard deviation).

Items FPE group FNE group Control group FPE v.FNE FPE v.Control FNE v.FPE FNE v.Control
BFNE 17.3 (5.0) 27.0 (2.9) 10.7 (4.7) — — t = 8.20, p < 0.001*** t = 14.51, p < 0.001***
FPES 42.5 (4.3) 19.4 (8.4) 11.2 (5.6) t = 11.99, p < 0.001*** t = 21.65, p < 0.001*** — —
LSAS 57.5 (16.7) 53.0 (22.1) 31.5 (20.1) t = 0.80, p = 0.43 t = 4.87, p < 0.001*** — t = 3.52, p = 0.001***
LSAS‐fear 28.9 (9.0) 27.6 (11.5) 14.8 (10.5) t = 0.43, p = 0.67 t = 5.00, p < 0.001*** — t = 4.03, p < 0.001***
LSAS‐avoidance 28.6 (8.6) 25.4 (11.2) 16.7 (10.3) t = 1.11, p = 0.27 t = 4.33, p < 0.001*** — t = 2.79, p = 0.008**
BDI‐II 6.67 (7.2) 8.88 (7.99) 3.08 (3.98) t = −1.14, p = 0.26 t = 2.10, p = 0.04* — t = 3.37, p = 0.002**
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*

p < 0.05.

**

p < 0.01.

***

p < 0.001.

2.3. Experimental Procedure and Stimuli Materials

Participants performed a modified SID task (Figure 1A). Each trial began with a 1000 ms cue indicating the trial type: a green triangle (potential reward), red triangle (potential punishment), or gray triangle (neutral). After a variable delay (2000–2500 ms), a target square appeared, prompting a speeded button press. Initial target duration was set to 250 ms and was dynamically adjusted using a staircase algorithm to maintain an overall success rate around 50%: duration decreased by 25 ms after a successful hit (i.e., a press made while the target was visible) and increased by 25 ms after a miss (i.e., a press made before or after target presentation) (Ait Oumeziane et al. 2019). Following a 2000‐ms interval, performance feedback was displayed for 1000 ms. In reward trials, hits triggered a positive social image (thumbs‐up and smile) and misses a neutral face. In punishment trials, hits produced a neutral face and misses an angry expression. In neutral trials, only a neutral face was shown regardless of performance. An inter‐trial interval of 1500 ms followed each trial. The task included six blocks (108 trials per condition, 324 trials total) and lasted approximately 45 min, preceded by a practice block.

FIGURE 1.

FIGURE 1

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Experimental design description. (A) an exemplar trial of the social incentive delay (SID) task. (B) Three types of feedback stimuli: praising, angry, and neutral expressions.

Social feedback images—depicting praising, angry, and neutral facial expressions—were AI‐generated using Doubao (ByteDance Ltd., Beijing, China) (Figure 1B). Thirty‐two independent raters evaluated the images on liking and wanting (0‐to‐9 point scales) and on valence and arousal (1‐to‐9 point scales). “Wanting” was defined as the rater's desire to receive that type of social feedback in the future (e.g., “How much would you want to receive this expression from others?”), reflecting the incentive salience of the cue (Zhang et al. 2020). Ratings showed that the praising expression was rated highest on liking, wanting, and valence, followed by the neutral and then the angry expression. For arousal, both praising and angry expressions were rated higher than neutral, with no significant difference between them (see Table S1). In post‐rating debriefing, over 88% of raters reported no suspicion that the images were AI‐generated.

2.4. EEG Recording and Analysis

The online recording of EEG data was performed using the Neuroscan 64‐channel EEG acquisition devices, according to the international 10–20 system. Scalp EEG signals were recorded using an Ag/AgCl electrode cap. Four external electrodes were used to record vertical electrooculogram (VEOG) and horizontal electrooculogram (HEOG). The ground electrode (Grand) was positioned at the midpoint between the FPz and Fz electrodes, while the online reference electrode was placed on the left mastoid. The impedance between each electrode and the scalp was maintained below 5 kΩ. Online data acquisition utilized a bandpass filter of 0.05–100 Hz and a sampling rate of 500 Hz. EEG data preprocessing was performed using MATLAB (R2024b, MathWorks Inc.) with the EEGLAB software 2025 version toolbox. The bandpass filter was set between 0.1 and 30 Hz. Artificially corrected eye movement and eye drift components (Delorme et al. 2007) were obtained using independent component analysis (ICA). The cue‐evoked ERP epochs lasted from −200 to 3000 ms while the feedback‐evoked epochs lasted from −200 to 1000 ms (Zhang et al. 2020; Wei et al. 2021). Epochs with amplitudes exceeding ±100 μV were excluded. Finally, trials under the same conditions were averaged for each participant. The number of artifact‐free trials per condition and group is reported in Table S2.

Time windows and ROIs for ERP components were defined based on established literature as well as the grand‐average waveforms and topographical maps (Figures 2 and 3). We focused on the cue‐phase N2 (cue‐N2), P3 (cue‐P3), and CNV components, as well as the feedback‐phase FRN and P3 (FB‐P3) components. The cue‐N2 component, a fronto‐central negative potential occurring 200–300 ms post‐cue, reflects conflict monitoring and cognitive control between the actual value of the cue and pre‐formed expectations (Folstein and Van Petten 2008; Lo 2018). Its mean amplitude was measured over the fronto‐central region (Fz, FCz, Cz) within a 270–340 ms time window post‐cue onset. The cue‐P3 component, typically peaking at 350–500 ms over centro‐parietal electrodes, reflects attentional allocation to the cue (Zhang et al. 2020). Its mean amplitude was averaged over centro‐parietal electrodes (P1, Pz, P2, and P4) within a 350–450‐ms time window post‐cue. The CNV component, a slow negative wave over fronto‐central electrodes following cue onset, reflects attentional and motor preparation for the target stimulus elicited by the cue (Chronaki et al. 2017). Its mean amplitude was extracted over fronto‐central electrodes (FCz and Cz) within a 2800–3000‐ms time window post‐cue (Wei et al. 2021). The FRN component, a fronto‐central negative potential occurring 200–300 ms post‐feedback, originates in the anterior cingulate cortex and reflects outcome valence evaluation (Glazer et al. 2018). Its mean amplitude was averaged over fronto‐central electrodes (Fz, FCz, and Cz) within a 200–250‐ms time window post‐feedback. The amplitude and peak latency of the FB‐P3 component, which reflects outcome evaluation (Glazer et al. 2018; San Martín 2012), were defined over centro‐parietal electrodes (Pz, P2, P4, P6) within a 350–450‐ms time window post‐feedback.

FIGURE 2.

FIGURE 2

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Anticipatory ERPs: Cue‐N2, Cue‐P3, and CNV. Grand‐average waveforms and topographies for FPE, FNE, and Control groups under reward (R), punishment (P), and neutral (N) conditions. Shaded areas on the waveforms indicate the analyzed time windows. Topographic maps to the right display the brain activity during these specific windows, with highlighted electrodes marking the regions of interest.

FIGURE 3.

FIGURE 3

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Feedback‐locked ERPs: FRN and FB‐P3. Grand‐average waveforms and topographic maps are presented for the FPE, FNE, and Control groups across all combinations of incentive condition (reward [R], punishment [P], neutral [N]) and feedback valence (positive [Pos], negative [Neg]), abbreviated as R‐Pos, R‐Neg, P‐Pos, P‐Neg, N‐Pos, N‐Neg. Shaded areas on the waveforms indicate the analyzed time windows. Topographic maps to the right display the brain activity during these specific windows, with highlighted electrodes marking the regions of interest.

Time‐frequency decomposition was performed using the short‐time Fourier transform (STFT). The analysis epoch spanned from 500 ms before to 1000 ms after feedback onset (with feedback onset defined as 0 ms). A 400 ms sliding window and a frequency resolution of 1 Hz were applied. Baseline correction was performed using the interval from 300 to 200 ms prior to feedback onset. Based on prior literature (e.g., Gheza et al. 2018; Liu et al. 2020) and topographical maps, mean spectral power in the delta (0.1–4 Hz) and theta (4–7 Hz) bands was extracted from a fronto‐central region of interest (Fz, FCz, Cz). Power was averaged within post‐feedback windows of 300–450 ms for delta and 200–300 ms for theta (see Figure 4).

FIGURE 4.

FIGURE 4

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Feedback‐elicited neural oscillations: delta and theta band activity. Time‐frequency representations and topographic maps during the feedback phase for the FPE, FNE, and Control groups. The time‐frequency representations depict delta (red boxes) and theta (gray boxes) band activity in response to positive and negative feedback, across reward (R), punishment (P), and neutral (N) incentive conditions. Topographic maps to the right display the brain activity during these specific time windows and frequency bands, with highlighted electrodes marking the regions of interest.

2.5. Statistical Analysis

In order to determine whether observed differences were driven by distinct evaluative‐fear traits rather than by underlying anxiety and depression symptoms, scores on the BDI‐II and LSAS were included as covariates in all primary analyses. Behavioral reaction times (RT) and accuracy (ACC) were each analyzed using a repeated‐measures ANCOVA with group (FPE, FNE, control) as the between‐subjects factor, incentive category (reward, punishment, neutral) as the within‐subjects factor. For EEG data, a parallel repeated‐measures ANCOVA framework was applied. Cue‐locked components (Cue‐N2, Cue‐P3, CNV) were analyzed using a 3 (group) × 3 (incentive category) design. Feedback‐locked components (FRN, FB‐P3, delta, theta) were examined with a 3 (group) × 3 (incentive category) × 2 (feedback valence: positive, negative) design.

All statistical analyses were performed using SPSS 23.0. Post hoc pairwise comparisons were conducted with Bonferroni correction, in which SPSS automatically adjusted raw p‐values to account for multiple comparisons, with an adjusted p < 0.05 considered statistically significant. To explore potential dimensional relationships between core social anxiety symptoms and neurophysiological measures, two‐tailed Spearman correlations were conducted between the LSAS total score and its Fear and Avoidance subscale scores (all non‐normally distributed) and the key behavioral, ERP, and oscillatory measures.

3. Results

Across all analyses, the covariates (BDI‐II and LSAS scores) yielded no significant main effects or interactions with experimental factors (Ps > 0.05).

3.1. Behavioral Data

A repeated‐measures ANCOVA revealed a significant main effect of incentive category for RT, F(2, 134) = 7.932, p = 0.001, η p 2 = 0.106 (Figure 5A). Pairwise comparisons showed that responses were faster in both potential reward trials (227.49 ± 4.519 ms) and potential punishment trials (228.35 ± 4.31 ms) compared to neutral trials (237.75 ± 4.33 ms, both p < 0.001). Neither the main effect of group, F(2, 67) = 0.543, p = 0.583, η p 2 = 0.016, nor the group × incentive category interaction, F(4, 134) = 0.905, p = 0.463, η p 2 = 0.026, was significant.

FIGURE 5.

FIGURE 5

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Behavioral and anticipatory phase neural results. (A) Accuracy (ACC) and reaction time (RT) for the three groups (FPE, FNE, and Control) under the three conditions (reward, punishment, neutral). (B) Correlation between the LSAS Fear subscale scores and theta power in response to positive feedback within the potential punishment context. (C) Anticipatory phase ERP results (Cue‐N2, Cue‐P3, CNV) for the three groups across the three conditions, with post hoc tests corrected using the Bonferroni method (*p < 0.05, **p < 0.01, ***p < 0.001).

For ACC, There was a significant main effect of group, F(2, 67) = 5.492, p = 0.006, η p 2 = 0.141, Post hoc tests revealed that the FPE group (53.32% ± 0.15%) and Control group (53.43% ± 0.16%) exhibited higher accuracy than the FNE group (52.75% ± 0.15%). No significant differences were found between the FPE group and Control group (p > 0.999). When controlling for depression and anxiety, the main effect of incentive category was significant, F(2, 134) = 4.209, p = 0.017, η p 2 = 0.059. However, Bonferroni‐corrected pairwise comparisons revealed no significant differences among potential reward trials (53.21% ± 0.11%), potential punishment trials (53.21% ± 0.09%), and neutral trials (53.08% ± 0.11%) (all ps > 0.05). The significant overall F‐test likely reflects reduced error variance after covariate adjustment, but the adjusted marginal means were too closely clustered (range: 0.00%–0.13%) to yield significant pairwise contrasts under Bonferroni correction.

No significant effect of group × incentive category interaction, F(4, 134) = 0.904, p = 0.464, η p 2 = 0.026, was observed (Figure 5A).

3.2. Anticipation Stage

3.2.1. Cue‐N2

The group × incentive category interaction was significant, F(4, 134) = 3.456, p = 0.010, η p 2 = 0.094, indicating distinct patterns of neural responsiveness to incentive cues across groups. Simple effect analyses elucidated this interaction. In the FPE group, the N2 was more negative for the potential punishment condition (−3.437 ± 0.853 μV) than for both the potential reward (−1.646 ± 0.890 μV, p < 0.001) and neutral conditions (−0.654 ± 0.810 μV, p < 0.001). The potential reward condition also elicited a more negative N2 than the neutral condition (p = 0.045). In the FNE group, the N2 was more negative for the potential punishment condition (−3.783 ± 0.861 μV) than for the neutral condition (−2.723 ± 0.818 μV, p = 0.042). No significant differences were found among conditions in the control group (Figure 5C).

The main effect of group, F(2, 67) = 0.743, p = 0.479, η p 2 = 0.022, and incentive category, F(2, 134) = 1.930, p = 0.149, η p 2 = 0.028, was not significant.

3.2.2. Cue‐P3

The main effect of incentive category was significant, F(2, 134) = 6.950, p = 0.001, η p 2 = 0.094. Pairwise comparisons revealed that the Cue‐P3 was more positive for potential reward trials (4.025 ± 0.394 μV) and potential punishment trials (3.993 ± 0.394 μV) compared to neutral trials (2.670 ± 0.366 μV, both p < 0.001) (Figure 5C). The main effect of group, F(2, 67) = 0.526, p = 0.593, η p 2 = 0.015, and the interaction between group × incentive category, F(4, 134) = 1.595, p = 0.179, η p 2 = 0.045, were not significant.

3.2.3. CNV

The interaction effect between group × incentive category was significant, F(4, 134) = 3.333, p = 0.012, η p 2 = 0.090. Simple effect analyses elucidated this pattern. In the FPE group, the CNV was more negative for both potential reward (−5.834 ± 0.758 μV) and potential punishment trials (−5.148 ± 0.704 μV) compared to neutral trials (−3.711 ± 0.795 μV, both p < 0.01). In the control group, the CNV was more negative for potential reward trials (−6.030 ± 0.822 μV) than for neutral trials (−4.657 ± 0.862 μV, p = 0.034). No significant differences were observed among conditions in the FNE group (Figure 5C).

The main effects of group, F(2, 67) = 0.104, p = 0.902, η p 2 = 0.003, and incentive category, F(2, 134) = 0.971, p = 0.381, η p 2 = 0.014, were not significant.

3.3. Feedback Stage

3.3.1. FRN

The main effect of incentive category was significant, F(2, 134) = 8.166, p < 0.001, η p 2 = 0.109. Pairwise comparisons revealed that the FRN amplitude was significantly more negative for neutral trials (−4.152 ± 0.432 μV) than for both potential punishment trials (−2.154 ± 0.482 μV, p < 0.001) and potential reward trials (−1.861 ± 0.516 μV, p < 0.001).

The incentive category × feedback valence interaction was also significant, F(2, 134) = 3.057, p = 0.050, η p 2 = 0.044. Simple effect analyses elucidated this interaction: In the potential reward condition, the FRN was more negative for negative feedback trials (−2.759 ± 0.507 μV) than for positive feedback trials (−0.962 ± 0.563 μV, p < 0.001). In the potential punishment condition, the FRN was more negative for positive feedback trials (−3.100 ± 0.526 μV) than for negative feedback trials (−1.208 ± 0.485 μV, p < 0.001). No significant difference between feedback types was found in the neutral condition (Figure 6A). Further, no other effects reached statistical significance.

FIGURE 6.

FIGURE 6

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Feedback phase neural results. (A) ERPs (FRN, FB‐P3) during the feedback phase. (B) Time‐frequency responses (delta, theta oscillations) during the feedback phase. Plots show neural responses to positive and negative feedback across reward (R), punishment (P), and neutral (N) contexts (abbreviated as R‐Pos, R‐Neg, P‐Pos, P‐Neg, N‐Pos, N‐Neg) for the FPE, FNE, and control groups.

3.3.2. Fb‐P3

The main effect of incentive category was significant, F(2, 134) = 40.763, p < 0.001, η p 2 = 0.378. Pairwise comparisons revealed that the FB‐P3 amplitude was more positive for both potential reward trials (12.419 ± 0.577 μV) and potential punishment trials (12.386 ± 0.609 μV) compared to neutral trials (5.078 ± 0.335 μV, both p < 0.001). The main effect of feedback valence was also significant, F(1, 67) = 11.162, p = 0.001, η p 2 = 0.143, with more positive amplitudes for positive feedback trials (10.552 ± 0.492 μV) than for negative feedback trials (9.370 ± 0.467 μV, p < 0.001) (Figure 6A). No other effects reached statistical significance.

3.3.3. Delta

The analysis revealed a significant main effect of incentive category, F(2, 134) = 14.934, p < 0.001, η p 2 = 0.182. Post hoc comparisons indicated that power was significantly higher in both potential reward trials (1.685 ± 0.134 dB) and potential punishment trials (1.675 ± 0.139 dB) compared to neutral trials (0.584 ± 0.064, both p < 0.001). The group × feedback valence interaction effect was also significant, F(2, 67) = 3.865, p = 0.026, η p 2 = 0.103. Simple effects analyses revealed a simple effect of feedback was present specifically in the control group, with higher power for positive (1.648 ± 0.211 dB) than for negative feedback (1.196 ± 0.200 dB, p < 0.001). This feedback effect was not significant in either the FPE or FNE groups (Figure 6B).

3.3.4. Theta

A significant main effect of incentive category, F(2, 134) = 10.565, p < 0.001, η p 2 = 0.136. Pairwise comparisons showed that theta power was significantly higher in the potential reward condition (1.387 ± 0.148 dB) than in both the potential punishment (1.112 ± 0.099 dB, p = 0.005) and neutral conditions (0.610 ± 0.079 dB, p < 0.001). Power was also higher in the potential punishment condition than in the neutral condition (p < 0.001). The group × feedback valence interaction effect was also significant, F(2, 67) = 4.971, p = 0.015, η p 2 = 0.118. Simple effects analyses revealed a simple effect of feedback (positive: 1.398 ± 0.223 dB > negative: 0.971 ± 0.183 dB) was present specifically in the control group (p = 0.001), but not in the FNE group and FPE group (Figure 6B). In addition, no other effects were significant.

3.4. Correlation Results

A significant negative correlation was observed between the LSAS Fear subscale score and theta power in response to positive feedback within the potential punishment context (r s  = −0.337, n = 72, p = 0.004) (Figure 5B). No other significant correlations were observed.

3.5. Sensitivity Analyses

In addition, we performed sensitivity analyses by repeating all key analyses using two alternative model specifications: (a) including only BDI‐II scores as a covariate, and (b) including no covariates. The statistical significance (p < 0.05) and the pattern of all core results—specifically, the key group × incentive category interactions for Cue‐N2 and CNV during anticipation, and the group × feedback valence interactions for delta and theta oscillations during feedback—remained consistent across all three analytical models (see Supplemental Results).

4. Discussion

This study examined whether FNE and FPE correspond to dissociable neuro‐affective response patterns (“specific” vs. “generalized”) during social‐motivational processing. We employed a SID task combined with EEG to identify the trait‐specific correlates and underlying dynamic processes of these fears. During the anticipation phase, the two traits exhibited distinct neural profiles. The FPE group showed increased N2 and CNV amplitudes in response to both reward and punishment cues, whereas the FNE group exhibited heightened N2 amplitudes selectively to punishment cues, accompanied by attenuated CNV amplitudes. During the feedback phase, unlike the control group, neither the FPE nor the FNE group exhibited differential delta or theta oscillatory activity in response to positive versus negative feedback. Critically, these core patterns proved robust to whether or how broadly we controlled for co‐occurring anxiety and depressive symptoms (see Sensitivity Analyses), strengthening the inference that they reflect trait‐specific processes rather than general negative affect. Together, these findings robustly support our primary hypotheses: FPE is characterized by a generalized pattern of neuro‐affective hyper‐engagement to evaluative cues, whereas FNE shows a specific pattern of vigilance to and withdrawal from threat. The subsequent discussion will further explore these key findings.

4.1. Differential Early Alertness: Specific Vigilance in FNE Versus Generalized Vigilance in FPE

Analyses of the Cue‐N2 component revealed a distinct, trait‐dependent pattern of early conflict monitoring during cue evaluation. The Cue‐N2—an index of conflict monitoring and cognitive control (Zhang et al. 2024; Novak and Foti 2015)—revealed distinct alertness patterns between FNE and FPE individuals. Individuals with FNE showed enhanced N2 amplitudes specifically to potential punishment cues, consistent with the classical view that fear of negative evaluation involves heightened sensitivity to social‐threat signals (Leary 1983; Weeks et al. 2005). In contrast, individuals with FPE exhibited enhanced N2 amplitudes to both reward and punishment cues. According to the template‐mismatch account, a larger N2 reflects a deviation from pre‐established expectations (Glazer et al. 2018; Novak and Foti 2015). The enhanced N2 to reward cues in FPE may reflect expectancy violation arising from a conflict between positive social signals and internal templates. Notably, the enhanced N2 to punishment cues suggests that early conflict monitoring in FPE is not valence‐specific; rather, any cue carrying social‐evaluative meaning appears to engage their conflict‐monitoring system. This pattern contrasts with FNE, which showed similar enhancement only to punishment (i.e., negative evaluation) cues. This interpretation is supported by multiple lines of evidence. Behavioral studies have shown that individuals high in FPE report greater anxiety when facing classic evaluative threat situations, such as delivering an evaluative speech (Weeks and Zoccola 2015); crucially, FPE predicts heightened anticipatory anxiety before a subsequent speech, irrespective of prior feedback valence (Weeks and Zoccola 2016). At the neural level, higher FPE scores have been associated with enhanced N1 amplitudes to both positive and negative social evaluative feedback (Song et al. 2025). Furthermore, a longitudinal study in adolescents demonstrated that FNE mediated the relationship between social anxiety and negative affect, whereas FPE mediated the relationship between social anxiety and suppression of both positive and negative affect (Tsarpalis‐Fragkoulidis and Zemp 2024). From a functional perspective, this pattern supports the view that FPE is particularly salient in group contexts: positive evaluation (i.e., reward) from one group member may simultaneously trigger concerns about social reprisal (i.e., punishment) from other witnessing members (Weeks et al. 2015). Consequently, individuals high in FPE need to maintain dual vigilance for both positive and negative evaluation cues to avoid the unique threat of appearing “too good,” which differs from the threat of appearing “not good enough” characteristic of FNE (Weeks et al. 2024).

The Cue‐P3 component, reflecting attentional allocation (Stim et al. 2023; Pfabigan et al. 2014), showed a similar pattern across groups, with both reward and punishment cues eliciting larger amplitudes than neutral cues. This pattern aligns with evidence that Cue‐P3 encodes motivational salience rather than valence (Chronaki et al. 2017; Pornpattananangkul and Nusslock 2015). The lack of group differences in Cue‐P3 suggests that cue salience detection remains largely intact in both FPE and FNE.

4.2. Divergent Anticipatory Preparation: CNV Distinctions Between FPE and FNE Traits

The CNV component reflects anticipatory attention, motivation, and motor preparation (Catalano et al. 2022; Novak et al. 2016; Schevernels et al. 2014). Consistent with typical reward‐approach behavior (Hughes et al. 2013; Pfabigan et al. 2014), the control group showed enhanced CNV amplitudes specifically for potential reward cues. In contrast, the FPE group exhibited heightened CNV to both reward and punishment cues. Combined with the N2 findings, this generalized, non‐valence specific pattern suggests that FPE may be characterized by excessive neurocognitive mobilization in response to any cue signaling social evaluation—indicating a core hypersensitivity to “being evaluated.” Conversely, the FNE group showed no significant CNV enhancement to either incentive type, suggesting diminished motivational engagement. This pattern may reflect a preemptive avoidance strategy to forestall potential distress (Huhman 2006). More specifically, the temporal sequence of early vigilance to punishment (N2) followed by weakened preparation (CNV) may align with the “vigilance‐avoidance” hypothesis in SAD (Mogg et al. 2004), illustrating the shift from threat detection to disengagement in FNE. Alternatively, it could stem from self‐regulatory resource depletion due to excessive cognitive control, as proposed by the resource depletion model (Kashdan et al. 2011).

Behaviorally, the observed accuracy advantage in both the FPE and control groups over the FNE group is consistent with the patterns of motivational preparation indexed by the CNV. Specifically, the attenuated CNV in the FNE group suggests a deficit in anticipatory engagement, which likely impaired task performance. In contrast, both the FPE and control groups exhibited significant CNV mobilization to motivationally salient cues (reward for controls; both reward and punishment for FPE), which plausibly supported their higher behavioral accuracy. Crucially, this motivational bias appeared to selectively impact response precision rather than speed. The absence of group differences in RT may suggest that the simple sensorimotor demands of the task were less sensitive to evaluation‐driven motivational biases.

4.3. Altered Neural Differentiation to Social Feedback: A Shared Pattern in High‐Order Reward Processing

Analysis of the FRN and FB‐P3 revealed typical, context‐sensitive patterns across all participants. The FRN, sensitive to prediction errors (Glazer et al. 2018), showed larger amplitudes for unexpected outcomes: negative feedback in reward contexts and positive feedback in punishment contexts (Xu et al. 2020; Yu and Zhang 2014). Neutral feedback elicited the largest FRN, likely due to its high unpredictability (Zhou et al. 2025; Mei et al. 2018). The FB‐P3, which indexes motivated attentional allocation (Guo et al. 2023), was significantly modulated by both incentive context and feedback valence (Di Gregorio et al. 2019). Its amplitude was larger for trials with motivational cues (reward and punishment) than for neutral trials, and larger for positive than for negative feedback. However, the absence of group differences for these components may indicate that initial feedback evaluation and motivational assessment are largely preserved in both FPE and FNE.

In contrast, delta and theta oscillatory activity revealed clear group‐level patterns. Delta oscillations, associated with fine‐grained reward encoding (Bernat et al. 2015), were enhanced in the control group specifically following positive feedback (e.g., social acceptance; Sailer et al. 2024), but not in the FPE or FNE groups. This indicates impairment in the neural mechanism that translates social approval into detailed value signals among individuals with evaluation fears. Frontal midline theta oscillations reflect the integration of motivational salience and prediction errors to engage cognitive control (Cavanagh and Frank 2014; Paul et al. 2020), typically increasing after salient, unexpected, or negative outcomes (Andreou et al. 2015; Paul et al. 2020). Consistent with this function, theta power in our study was significantly higher in both reward and punishment contexts than in the neutral condition, highlighting its sensitivity to motivationally relevant cues. Notably, only the control group showed a significant overall enhancement of theta activity for positive versus negative feedback. Given that enhanced frontal theta reflects the dynamic regulation of cognitive control (Cavanagh and Frank 2014; Cavanagh and Shackman 2015) and is crucial for updating value estimates and behavioral strategies during reinforcement learning (Begus and Bonawitz 2020), this finding suggests that individuals with evaluation fears may be unable to effectively mobilize theta‐mediated control in response to motivationally salient positive feedback. This could impede the reinforcement of successful social experiences and adaptive behavioral updating. Additionally, a significant negative correlation was found between LSAS Fear scores and theta power following successful avoidance, indicating that greater subjective social fear is linked to weaker neural mobilization of cognitive control after a positive outcome. This may reflect a deficit in using “successful harm avoidance” to optimize future behavior (Nigbur et al. 2011).

In summary, although both traits retained basic feedback discrimination, neither experimental group exhibited the valence differentiation effect (positive > negative) observed in the control group during higher‐order reward integration: specifically, possibly a blunted neural encoding of social acceptance (reduced delta) and an impaired mobilization of cognitive control based on positive feedback (reduced theta differentiation). This may reflect a common difficulty in translating positive social outcomes into adaptive motivated behavior.

4.4. Limitations and Future Directions

Several limitations warrant consideration. First, the cross‐sectional design precludes causal inference regarding whether the observed neurophysiological dissociations contribute to or result from FPE/FNE traits. Second, stringent screening and the moderate correlation between traits resulted in a limited sample size, necessitating replication in larger, more diverse cohorts. Third, the current group‐based design compared relatively purified high‐FPE and high‐FNE phenotypes, but could not address co‐occurring elevations of both traits within the same individual. Although we incorporated FPES and BFNE as continuous predictors in linear mixed‐effects models (see Table S3), we did not find evidence for linear synergistic effects or single‐dimension dominance of co‐occurring FPE and FNE in the present sample. Future studies with samples covering a wider range of scores on both dimensions, or employing a full 2 (high/low FPE) × 2 (high/low FNE) factorial design that includes a dual‐high group, are needed to directly test co‐occurrence and potential interaction effects. Fourth, one measurement consideration is that our BFNE‐S used a 0–4 metric instead of the original 1–5 format. Although this adapted version has been validated in prior work, we acknowledge that it may limit direct comparability with studies using the original metric. Finally, generalizability from our high‐trait, non‐clinical sample to diagnosed Social Anxiety Disorder requires empirical validation. While our trait‐focused approach isolates core neural correlates from clinical confounds (e.g., chronicity, comorbidity), it raises a key translational question: future studies should directly compare clinical SAD and high‐trait non‐clinical groups to determine whether the identified neural patterns are (a) quantitatively amplified, (b) qualitatively altered, or (c) interact with broader psychopathology to predict symptoms or treatment outcomes. Clarifying this clinical continuity is essential for translating trait‐based biomarkers into stratified or personalized interventions.

5. Conclusion

This study aimed to examine whether FPE and FNE rely on dissociable and/or shared neurophysiological mechanisms during dynamic social motivational processing. The results confirm a dissociation: during anticipation, FPE manifested a “generalized over‐engagement” to evaluative cues (enhanced N2/CNV to both reward and punishment), reflecting a state of hyper‐vigilant preparation for the evaluative context itself, whereas FNE showed “specific threat vigilance with motivational withdrawal” (enhanced N2 only to punishment cues, coupled with diminished CNV), consistent with a defensive inhibitory state. Despite this anticipatory divergence, both groups showed a similar pattern of attenuated delta/theta oscillations to social acceptance during feedback, which may reflect a common difficulty in deep reward integration.

Author Contributions

Jinhong Ding: conceptualization, supervision, project administration, funding acquisition, resources, writing – review and editing. Rui Zhang: conceptualization, investigation, data curation, methodology, writing – original draft, writing – review and editing, visualization.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1: Supporting Information.

PSYP-63-e70374-s004.doc (95.5KB, doc)

Table S1: Subjective ratings (Liking, Wanting, Valence, Arousal) of feedback stimuli.

PSYP-63-e70374-s003.doc (27KB, doc)

Table S2: Mean number of artifact‐free trials by condition and group.

PSYP-63-e70374-s002.docx (11.6KB, docx)

Table S3: Summary of linear mixed‐effects models examining continuous FPES and BFNE as predictors of N2, CNV, delta, and theta ERP/oscillatory responses.

PSYP-63-e70374-s001.doc (77KB, doc)

Acknowledgments

We thank all the participants for their unending contributions to this work.

Data Availability Statement

The data and analysis code supporting the findings of this study are openly available on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/J5BA6. All analyses were conducted using MATLAB (version 2024b) and the EEGLAB toolbox (version 2025).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1: Supporting Information.

PSYP-63-e70374-s004.doc (95.5KB, doc)

Table S1: Subjective ratings (Liking, Wanting, Valence, Arousal) of feedback stimuli.

PSYP-63-e70374-s003.doc (27KB, doc)

Table S2: Mean number of artifact‐free trials by condition and group.

PSYP-63-e70374-s002.docx (11.6KB, docx)

Table S3: Summary of linear mixed‐effects models examining continuous FPES and BFNE as predictors of N2, CNV, delta, and theta ERP/oscillatory responses.

PSYP-63-e70374-s001.doc (77KB, doc)

Data Availability Statement

The data and analysis code supporting the findings of this study are openly available on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/J5BA6. All analyses were conducted using MATLAB (version 2024b) and the EEGLAB toolbox (version 2025).

Articles from Psychophysiology are provided here courtesy of Wiley

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