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To investigate the influence of emotion regulation and impulsivity measures on instrumental reversal learning in patients with borderline-personality disorder and healthy controls

Due to adaption mechanisms, continuous perception of a simple stimuli can lead to perceptual fading, and successive perception of stimuli of the same general category but with different characteristics can lead to illusionary perceptual exaggeration of differences. Another reason for perceptual illusions is peripheral vision due to sparse neural representations of peripherally perceived stimuli. Some adaptation-based illusions are potentiated or exclusive in peripheral vision, which postulates an interaction between adaption mechanisms and peripheral vision. Consecutively perceived faces in peripheral vision appear distorted after the first few faces within a sequence, a phenomenon called flashed face distortion effect. Here we aim to systematically analyze adaptation-based neural and perceptual consequences of sequential and pairwise consecutive face perceptions in central and peripheral vision.

Facial expression recognition is central to social communication and dependent on environmental conditions. For example, in a dangerous situation, we tend to identify threat better than safety information. Such recognition biases in favour of threat detection can prevent harm and injury but, if exaggerated, also contribute to the development and maintenance of anxious psychopathology. We will examine interindividual differences in threat perception and its malleability through threat-safety reversal learning using whole-head magnetoencephalography. This will involve an emotion recognition test with subtle expressions of fearful or happy faces in contextual settings of threat-of-shock or safety. Previous findings show early neural priming of context-congruent face processing (i.e., fearful faces during threat). Based on this, we predict this threat-selective bias is pronounced in individuals prone to anxious psychopathology who benefit less from threat reversal to safety. The results will improve our understanding of perceptual biases from healthy functional to the anxiety disorder spectrum.

Experimental files and aggregated data and statistics

A. Main Question and Hypotheses The aim is to investigate the influence of contextual threat (compared to safety) learning and its reversal on person perception and recognition in healthy individuals. Threat and safety information will be transmitted by means of social learning to better understand the underlying mechanisms of vicarious and verbal (threat and safety) learning on how we perceive and remem-ber other people. For this purpose, memory performance and physiological reactions (heart rate, skin conductance response, ERPs in EEG) will be assessed during the encoding, reversal and recognition of facial stimuli while participants anticipate unpleasant electrical shocks. Additional-ly, questionnaire data on adverse childhood experiences and (trait and social) anxiety will be col-lected as potential modifying factors in the acquisition, (partial) reversal and recognition of threat and safety stimuli. Rating data will be collected as a means of manipulation check. The recognition and adequate response to dynamically changing threat and safety condi-tions is crucial for adaptive and successful behavior. For example, emotions such as fear can be evoked by recognizing a predator and corresponding actions (e.g. avoidance) can be initiated. On the other side, learning that certain situations are safe brings a similar advantage to adjust to dy-namically changing contextual conditions. This is important, for example, to prevent the emer-gence of pathological fear (e.g., in anxiety disorders or post-traumatic stress disorder; PTSD) before it leads to generalized, dysfunctional avoidance behavior and pathological fear responses. In order to reverse previously learned threat and safety associations, the inhibition of old and the acquisition of new threat and safety associations occur simultaneously but are directed towards different stimuli or contextual conditions. Accordingly, the potential threat remains pre-sent but is associated with a new stimuli that was formerly signaling safety (Schiller et al., 2008). Thus, reversal learning differs from extinction learning (in which the non-existence of a threat-association is learned) and may better reflect a constantly changing environment and flexible up-dates of contextual threat/safety associations (Schiller & Delgado, 2010). Since this process does not aim at an absolute change in perception (e.g., complete disappearance of fear), this form of threat/safety learning could be relevant to therapeutically interventions. From a clinical perspective, social means of threat learning are important for the develop-ment of pathological fear (see DSM 5, vicariously acquired trauma in PTSD), however, its rever-sal through social learning has rarely been investigated. The assumption here is that previously learned threat cues can be re-trained as safety cues through verbal or observational learning (Cos-ta et al., 2015; Pan et al., 2020). Previous research has indicated that both verbal and observa-tional fear learning show indistinguishable behavioral effects that are comparable to direct fear learning (Olsson & Phelps, 2004, 2007, Lindström et al., 2018). While direct or Pavlovian fear conditioning is investigated in large detail on the behavioral and neural level with the amygdala as the critical region to physiological expression of learned fear, little work has focused on how social information modulates learned threat memories or how social safety information is trans-mitted and processed, especially with focus on reversal learning. Social learning leads to a rapid acquisition of fear responses and selective processing of threatening compared to safe stimuli (Bublatzky & Schupp, 2012). However, a more distributed neural network including other re-gions apart from the amygdala (the striatum, Anterior Insula, ACC, MPFC, orbitofrontal cortex) is likely involved in social learning, involving perceptional and evaluation processes (Olsson & Phelps, 2007, Lindström et al., 2018). For instance, verbal threat learning seems highly efficient in reestablishing a safety (and threat) condition, e.g. shown by reversed skin conductance (Atlas & Phelps, 2018). Yet, there seem to be different underlying mechanisms between verbal and ob-servational learning, for instance in the transfer of threat associations on instrumental decision making (Lindström et al., 2019). A direct comparison of verbal and observational learning during reversal with an emphasis on the transmission of safety information, however, is still lacking. Safety learning seems to be impaired in highly anxious individuals and those with trauma history; a possible mechanism is the over-generalization of threat towards safe situations (Schiller, Levy, Niv, LeDoux & Phelps, 2008; Jovanovic, Kazama, Bachevalier & Davis, 2012; Gazendam, Kamphuis & Kindt, 2013). To this end, we compare verbal instruction and observational threat/safety and reversal learning (Lindström et al., 2018) and use faces as central stimuli that are embedded within differing contextual threat and safety settings. Exploratory analyses will look into the potential modifying impact of previous trauma experience and anxiety on rever-sal/memory. While flexible threat and safety learning helps organizing successful behavior, it is im-portant to remember both central and contextual aspects of a situation. Here, both emotional arousal and violation of expectations have been shown to increase recognition performance (Weymar et al., 2013; Dolcos et al., 2020), and may mutually improve face recognition in (partial-ly) reversed contextual setting. Therefore, we hypothesize that faces from a threatening context (which used to signal safety previously) should be recognized best, whereas faces from a safe context that had always signaled safety should be recognized worst. Hypotheses: 1. Instantiation phase Threat-selective processing for both instructional and observational learning: As in previous stud-ies (Schellhaas et al., 2020; Bublatzky et al., 2010, 2012) a processing difference of stimuli from a threatening context compared to a safe context is expected for early and late ERP components (enhanced N170, EPN and LPP for threat compared to safe face-context compounds). With higher scores of adverse childhood experiences and anxiety, less pronounced threat-safety differ-ences are expected because the safety context is perceived as less safe, and threat generalizes to non-threatening conditions (Jovanovic, Kazama, Bachevalier, & Davis, 2012; Gazendam, Kam-phuis & Kindt, 2013; Ehlers & Clark, 2000). Regarding psychophysiological defense activation, increased skin conductance and heart rate deceleration are expected for threat compared to safe-ty context conditions (Bublatzky et al., 2014, 2017; Costa et al., 2015). 2. Reversal phase For the reversal block, four different combinations of threat/safety associations are possible (safe-to-threat, threat-to-safe, safe-safe, threat-threat). We expect that: i) faces with a maintaining safe or threat context (safe-safe and threat-threat) do not differ between the instantiation and reversal presentations; ii) faces whose context becomes safe show reduced early positivity (reversed threat-to-safe faces); iii) faces whose context becomes threatening show increased positivity (re-versed safe-to-threat faces). For both reversal conditions (safe-to-threat and threat-to-safe), an increased P3 is expected reflecting novelty and/or memory update processes. Moreover, a processing hierarchy is assumed between the stimuli in the second learning phase (cf. Bublatzky et al., 2020), which should be reflected in a linear change in late positive amplitudes (reversed safety-to-threat stimuli > maintained threat stimuli > reversed threat-to-safety stimuli > maintained safety stimuli). Reversal from threat to safety (safety to threat) should lead to an immediate attenuation (potentiation) of the defensive reactions compared to stimuli that maintain cueing threat, indexed by reduced (enhanced) skin conductance response and heart rate deceleration (Costa et al., 2015). No differences between observational and verbal learning are assumed. For higher levels of adverse childhood experiences and anxiety, it is as-sumed that the difference between reversed safety and stimuli that had consistently signaled threat declines (Jovanovic, Kazama, Bachevalier & Davis, 2012; Gazendam, Kamphuis & Kindt, 2013). 3. Recognition phase ERPs and behavioral performance For retrieval, ERP differences are expected when viewing old and new stimuli and especially when the stimuli are recognized as old (Ventura-Bort et al., 2016; Weymar et al., 2013). This ef-fect (enhanced positivity for old stimuli, early and late parietal-occipital, 300 – 500ms, > 500ms) is assumed to vary based on context conditions from the instantiation and reversal phase: again, the processing hierarchy is assumed to persist throughout the phases, with the largest effect from reversed safety-to-threat and smallest effect from maintained safety. Regarding recognition performance, old faces are better recognized than new faces. Also for the recognition performance, a processing hierarchy is assumed, with best memory for the faces from the reversed safety-to-threat and worst memory for the faces from the maintained safe environ-ments. No differences between observational and verbal learning are assumed. For self-report data, in both learning phases it is expected that a threatening context is perceived as more unpleasant, arousing and threatening than a safe context. B. Methods & Analyses Design & Procedure Electrocortical activity is recorded using a 64-channel system (BrainProducts, Munich, Germany). For this purpose, Ag/AgCl active electrodes are placed on the head with a cap and a saline sensor gel using a 10-10 electrode placement standard. A fake electrode is then attached to the non-dominant forearm of the test persons to induce aversive anticipation (without experi-ence). Skin conductance activity is recorded through Ag/AgCl- electrodes, placed on the hy-pothenar of the left palm, using The BrainAmp ExG amplifier (BrainProducts, Munich, Germa-ny) with a sampling rate of 20 Hz. Heart rate is collected through two electrodes on the collar-bones and one ground electrode placed on the ankle, sampling rate will be 1000Hz. Color (blue/green) and texture (striped/squared) are combined to form four sets of distinct perceptual context cues (blue striped, blue squared, green striped and green squared; Costa, Bradley, & Lang, 2015). In the instantiation phase, participants learn about threat/safety associa-tions via verbal instructions (e.g. Bublatzky et al., 2010) or by means of observing a model using a video demonstration (observational learning; Haaker et al., 2017). Threat/safety associations are established for a certain contextual feature (i.e. color or texture) that indicate the risk of receiving electrical shocks (e.g. blue context indicates threat), whereas the other color indicates safety (e.g. green) they are safe from electrical stimuli (safety context). Participants then are presented with 60 neutral face pictures (4 seconds each), 15 within each of the four contexts. A variable inter stimulus interval (8-12 seconds) separates picture presentation. Afterwards, in the reversal phase, participants are again verbally instructed or learn via observation that the second context feature (e.g., texture striped) indicates the risk of receiv-ing a shock and the other dimension (e.g. texture squared) signals safety. Therefore, the resulting four contexts either (1) always signal threat of shock (e.g. blue striped), or (2) safety (e.g. green squared) or reverse their meaning from (3) threat-to-safety (e.g. blue squared) or (4) from safety-to-threat (e.g. green striped). In fact, no electrical stimuli are administered during the experiment. Again, the 60 faces from instantiation phase are shown (same contexts and durations). In a fol-lowing 45 minutes retention phase participants will participate in an unrelated spatial navigation task serving as distractor. This time lag is introduced to strengthen the memory trace and enhance the recognition probability (consolidation, McGaugh, 1966, 2000; LaBar & Phelps, 1998; Dudai et al., 2015). Following both learning phases, 90 face pictures (60 previously presented and 30 new) without context are presented on a white screen and the participants complete a face recognition task. To this end, participants need to decide whether a face has been presented previously or whether it is new; moreover, how confident they are with their decision (Likert scale from 0–10). Before and after the instantiation and reversal phases as well as the memory task, the con-text compounds are rated in terms of valence, arousal (Self-Assessment Manikin, SAM, Bradley & Lang, 1994) and perceived threat (Likert scale from 0 to 10). This serves as a self-report meas-ure to check that the threat instruction shows the predicted (reversal) effects. At the end of the experiment participants rate the credibility, naturalness, expressiveness, discomfort and empathy for the model in the video (observational learning, if applicable; Haaker et al., 2017). Key dependent variable(s). Event-related potentials (N170, EPN, LPP, P300), SCR, HR, memory in recognition task (hit rate (HR), false alarm rate (FAR), item recognition (HR – FAR)), self-reported ratings (valence, arousal, threat, confidence) Conditions. (Social) learning, instruction vs. observation  between Context instantiation phase, threat vs. safety  within Context reversal phase, threat-threat, threat-to-safe, safe-to-threat, safe-safe  within Planned analyses. Mean ERP amplitudes will be submitted to repeated measures ANOVAs with the factors: 2 (Learning) × 2 (Phase). Follow-up analyses focus separately on the instantiation session (Context × Learning), and the reversal (Learning × Reversal Context). Regarding memory performance, relevant measures (hit rate, false-alarm rate, and accuracy) will be analyzed with separate 4 (Re-versal Context) × 2 (Learning) ANOVAs. As a manipulation check, rating data will be submitted to a 3 (Time) × 4 (Reversal Context) statistical design. Sample size. Sample size estimation via G*Power (Faul, Erdfelder, Lange& Buchner, 2007) Number of groups = 2 (observation vs. instruction) Estimated effect size f= 0.25 Alpha error probability = 0.05 Power (1- beta error probability) = 0.95 N = 40 total/ 20 per group (actual: 36 total) Planned sample Inclusion criteria: - Age: 18-60 years - Consent to participate Exclusion criteria: - Acute and/or chronic physical diseases (e.g. cardiovascular, respiratory or neurological diseases) - Acute and/or chronic psychotic disorders - Medical advice to avoid stressful situations - Use of psychotropic drugs (except SSRIs and SNRIs), substance dependence and/or abuse - Pregnancy Participants are recruited in Germany, mostly Mannheim, via online ads (homepage of the central institute of Mental Health (CIMH)), social media (Facebook, WhatsApp), flyer. Answer the following final questions: Has data collection begun for this project? o No References Atlas, L. Y., & Phelps, E. A. (2018). 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Reduced individuation of other-ethnicity faces (outgroup homogeneity effect) results from overlapping neural representations due to low perceptual expertise. While established expertise for own-ethnicity faces leads to distinct neural representations and therefore lower repetition suppression between consecutive perceptions of different faces than of the same face, this distinction was shown to be absent with other-ethnicity faces. Here we attempt to replicate this result for the N170 repetition suppression. Additionally, to study psychological consequences, we ask if reduced individuation on a perceptual and neural level leads to the generalization of associations over members of a different ethnicity. Specifically, we investigate if the threat association of a single other-ethnicity identity results in pronounced LPP amplitudes elicited by different other-ethnicity faces not associated with threat.

A. Main Question and Hypotheses The aim is to investigate the influence of social threat/safety learning on face percep-tion and memory in individuals with adverse childhood experiences. For this purpose, we record physiological reactions (event related potentials (ERP) in EEG (Electroen-cephalography), behavioral and memory measures during the encoding, retrieval and intermediate memorization of facial stimuli during the anticipation of unpleasant events (electrical stimuli). Additionally, questionnaire and rating data are collected. Key questions are: (a) Does social threat learning via instructions and observations has a beneficial effect on memory processes, probably depending on memory modality (i.e. source memory and working memory capacity)? (b) Does severe traumatization in early childhood and adolescence (adverse childhood experiences, ACEs) lead to a reversal of these effects? Hypotheses: Source memory: (1) During the encoding phase of the source memory task, processing differences be-tween stimuli (faces) presented against a threat background compared to a safe back-ground are expected for early and late ERP amplitudes (N170, EPN, LPP; Schellhaas et al., 2020; Bublatzky et al., 2010). (2) For the recognition phase of the source memory task, ERP differences are expected when recognizing old and new stimuli (old/new recognition effect; ~300-500ms, Ventu-ra-Bort et al., 2016; Weymar et al., 2013) and especially when the stimuli are recog-nized as old (Senkfor & van Petten, 1998). This difference should be more pronounced if the stimuli were shown in the encoding phase with a threatening background, as this seems to be the neural correlate for correct source recognition (~600-800ms, Ventura-Bort et al., 2016; Rugg & Curran, 2007). (3) Furthermore, ERP processing differences are expected for old stimuli in the recog-nition phase that were presented in the encoding phase with a threatening context, especially if they can be correctly assigned to the source (Schellhaas et al., 2020). (4) With regard to memory performance, better recall is expected for stimuli that were presented against a threatening background during the encoding phase (Ventura-Bort et al., 2016; Weymar et al., 2013). Furthermore, a better memory of the source in case of threat is expected compared to safety. Working Memory Capacity: (5) With regard to the sustained posterior contralateral negativity (SPCN; Sessa, Luria, Gotler, Jolicœur & Dell'Acqua, 2011) and, analogously, contralateral delay activity (CDA, Stout, Shackman & Larson, 2013), an increased amplitude is expected when the number of objects maintained in WM increases (Ikkai et al., 2010). In the case of stimuli in a threatening context compared to a safe context a modulated amplitude is expected, with either decreased (task irrelevant, Ward et al., 2020) or increased amplitude (task relevant, Stout et al., 2013). (6) Regardless of the context, working memory performance should be higher if only one target stimulus is presented in comparison to two. Regarding threat manipulation, previous research shows mixed results. Working memory capacity performance could be worse when the presentation and identification of target stimuli takes place under threat (reduced ability to actively inhibit distracting information, Moran, 2016), could be equally good (Ward, 2020), or even better (greater recruitment of cognitive resources in order to maintain task performance especially with low memory load; Moriya, & Sugiu-ra, 2013). ACE: (7) It is suspected that increasing levels of ACEs modulate neural processing of the threat, but also safe condition, especially at moderate-severe levels (Karl et al., 2006; McFarlane et al., 2005). The differences between threat and safety contexts postulated above are suspected to decrease, as might the overall strength of processing (e.g. P300, Galletly et al., 2001) (8) With increasing levels of ACEs, it is assumed that the perceived threat generalizes and affects cognitive processing and memory and tends to inhibit adequate perfor-mance, so that opposite effects should emerge as postulated above (Pechtel & Piz-zagalli, 2011). Thus, it is expected that the recall of faces and source under threat as well as maintaining them in working memory (Goodman et al., 2018; especially under high load) is generally worsened. Questionnaire measures (CTQ, German version; Bernstein & Fink, 1998) are included in the analyses (both ERP and performance) as covariates and dimensional factors (for (7) and (8)). Exploratory hypotheses: (1) We investigate both instructional and observational threat learning on memory pro-cessing. As findings are scarce in that regard, the factor ‘learning path’ is explorative. No differences in initial threat learning (as used in the current study) are assumed (Olsson & Phelps, 2004). (2) For working memory capacity, P300 will be analyzed exploratory as an index of cognitive load (Sirevaag et al., 1989; Morgan et al., 2008). (3) Different types of ACEs (i.e. abuse and neglect), also measured by the CTQ, are included in the analyses (both ERP and performance). If possible, group comparisons between no ACE and moderate-severe ACEs according to the type of ACE will be con-ducted as some effects of early trauma on cognition might depend on type and severity (Westermair et al., 2018; Herzog & Schmahl, 2018). The Brief Symptom Inventory (BSI; German version; Franke, 2000) as a measure of psychopathology will be used to ex-plore any associations to memory and perceptual processing (of threat). Other anxiety measures (e.g. social anxiety) are also tested on an explorative base. B. Methods & Analyses Design & Procedure Electrocortical activity is recorded using a 64-channel system (BrainProducts, Munich, Germany). Ag/AgCl active electrodes are placed on the head with a cap and a saline sensor gel using a 10-10 electrode placement standard. A (fake) electrode is then at-tached to the non-dominant forearm of the test persons to induce aversive anticipation (without experience). The participants are then verbally instructed (e.g. Bublatzky et al., 2010) or learn via observing a model using a video demonstration (observational learning; Haaker et al., 2017) that for a certain context color (e.g. blue) they could receive an electrical shock (threat context), whereas for another color (e.g. green) they are safe from electrical stimuli (safety context). In fact, no electrical stimuli are administered during the entire experiment, thus social learning about threat/safety associations is examined (i.e. via observations or instructions). After the acquisition phase, participants complete two memory tasks, a source and a working memory capacity task (randomized sequence). The tasks are PC-based standard tasks in the field of experimental cognitive psycholo-gy: In a typical source memory task (Johnson et al., 1997) the participants are not only supposed to recognize the previously presented stimulus but also to remember specific features of the stimulus or context. For this purpose, the participants see face pictures of 60 different people displaying neutral facial expressions. Each 30 faces are pre-sented within a colored background frame (e.g. blue or green). The participants are in-structed to look at the pictures carefully and memorize them as they will be asked to recognize them later (explicit learning instruction), while the following source memory task was not mentioned (implicit learning). The pictures are presented one after the other for 6 seconds each, and the frame colors alternated after every 10th picture. After a short break, all 60 old faces and additional 30 new images are presented in random-ized order without color frames. Participants are asked to indicate the background against which a face was presented in the learning phase (combined item and source memory) or whether it is a new face. The visual working memory capacity is tested with neutral face pictures using a change detection task (Stout et al., 2013; Luck & Vogel, 1997; Beck, Rees, Frith & Lavie, 2001; Little & Woollacott, 2015). Per trial, participants are presented with two or four faces (i.e. 1 or 2 target and distractor images each), whose positions are evenly distributed across the screen. Again, the face images are surrounded by different col-ored frames (blue/green), which signal safety or threat of electrical shocks. Importantly, the position of the faces to be remembered (target images) or possible changes, are indicated by arrows to the right or left (e.g. Beck et al., 2001; Pessoa & Ungerleider, 2004). After a short waiting period, the faces are presented again and the participants have to decide whether one of the target faces has changed. As a manipulation check, background colors are rated in terms of valence, arousal (Self-Assessment Manikin, SAM, Bradley & Lang, 1994) and perceived threat (Likert scale from 0 to 10) before threat learning and after the memory tasks. At the end of the experiment, additional ratings are obtained regarding credibility, naturalness, expres-siveness, discomfort and empathy for the model in the video (observational learning; Haaker et al., 2017). Key dependent variable(s) • Source Memory (multinomial processing tree models, MPT), HR (hit rate), FAR (false alarm rate), Recognition Memory (HR-FAR)) • Working Memory Capacity (RT (reaction time), Pashler’s K, d’, HR, FAR (signal detection theory)) • Source memory, working memory capacity and encoding/recognition & threat/safety face related ERP components. ERP components of key interest are the P1, P2, N170, EPN and LPP for the source memory task, as well as the CDA and SPCN for the working memory task • Ratings (valence, arousal, perceived threat) Conditions • Social Learning (Obervervational vs. Instructional)  between • Context (Threat vs. Safety)  within Planned analyses (excerpt) The following procedures are planned for data analysis. Accounting for previous re-search (cf. Schupp et al., 2006; Schindler & Bublatzky, 2020), ERP analyses base on mean amplitudes within early (~100-300 ms; e.g. N170 (~150-190 occipito-parietal, cen-tral), EPN (~200-300 ms occipito-parietal)) and late time windows (>300 ms; e.g. LPP (parieto-occipital ~400-800 ms), in which the difference between the threat and safety condition should be at its maximum. ERP components are tested with separate ANOVAs with repeated measurements. These include the factors of the studies: context (threat vs. safety), social learning (in-struction vs. observation), as well as recognition (old vs. new), change detection (no change vs. change), as well as traumatization as a dimensional variable. Furthermore, behavioral estimates for working memory capacity (Pashler, 1988) and reaction times are used for the change detection task. Behavioral measures – such as hit rate (HR), false alarms (FA), discrimination index (HR-FA), average conditional source identification measure (ACSIM) – are analyzed using ANOVAs with the factors of these studies. Multinomial processing tree modelling will be used for analyzing the source memory task. Planned sample Inclusion criteria: - Age: 18-60 years - Consent to participate - adverse childhood experience(s) (CTQ) Exclusion criteria: - Acute and/or chronic physical diseases (e.g. cardiovascular, respiratory or neurologi-cal diseases) - Acute and/or chronic psychotic disorders - Medical advice to avoid stressful situations - Use of psychotropic drugs (except SSRIs and SNRIs), substance dependence and/or abuse - Pregnancy Participants are recruited all over Germany via online ads (homepage of the central institute of Mental Health (CIMH), Mannheim, the homepage of the Graduate School GRK2350: https://www.grk2350.de/index.php?option=com_content&view=article&id=46&Itemid=238), ads in newspapers, flyer (at the CIMH, therapist offices), letters through the regis-tration’s office in Mannheim. They are part of a central recruitment of the GRK2350 and will participate in numerous studies including the one described here while they are on site. 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It is generally thought to be adaptive that fear relevant stimuli in the environment can capture and hold our attention; and in psychopathology attentional allocation is thought to be cue-specific. Such hypervigilance toward threatening cues or difficulty to disengage attention from threat has been demonstrated for a variety of stimuli, for example, toward evolutionary prepared animals or toward socially relevant facial expressions. Usually, specific stimuli have been examined in individuals with particular fears (e.g., animals in animal fearful and faces in socially fearful participants). However, different kinds of stimuli are rarely examined in one study. Thus, it is unknown how different categories of threatening stimuli compete for attention and how specific kinds of fears modulate these attentional processes. In this study, we used a free viewing paradigm: pairs of pictures with threat-related content (spiders or angry faces) or neutral content (butterflies or neutral faces) were presented side by side (i.e., spiders and angry faces, angry and neutral faces, spiders and butterflies, butterflies and neutral faces). Eye-movements were recorded while spider fearful, socially anxious, or non-anxious participants viewed the picture pairs. Results generally replicate the finding that unpleasant pictures more effectively capture attention in the beginning of a trial compared to neutral pictures. This effect was more pronounced in spider fearful participants: the higher the fear the quicker they were in looking at spiders. This was not the case for high socially anxious participants and pictures of angry faces. Interestingly, when presented next to each other, there was no preference in initial orientation for either spiders or angry faces. However, neutral faces were looked at more quickly than butterflies. Regarding sustained attention, we found no general preference for unpleasant pictures compared to neutral pictures.