Social exclusion impairs distractor suppression but not target enhancement in selective attention

Accepted Manuscript Social exclusion impairs distractor suppression but not target enhancement in selective attention

Mengsi Xu, Zhiai Li, Liuting Diao, Lingxia Fan, Lijie Zhang, Shuge Yuan, Dong Yang PII: DOI: Reference:

S0167-8760(17)30031-4 doi: 10.1016/j.ijpsycho.2017.06.003 INTPSY 11284

To appear in:

International Journal of Psychophysiology

Received date: Revised date: Accepted date:

12 January 2017 11 April 2017 6 June 2017

Please cite this article as: Mengsi Xu, Zhiai Li, Liuting Diao, Lingxia Fan, Lijie Zhang, Shuge Yuan, Dong Yang , Social exclusion impairs distractor suppression but not target enhancement in selective attention, International Journal of Psychophysiology (2017), doi: 10.1016/j.ijpsycho.2017.06.003

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ACCEPTED MANUSCRIPT Running Head: SOCIAL EXCLUSION INFLUENCES SELECTIVE ATTENTION

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Social Exclusion Impairs Distractor Suppression but Not Target Enhancement in Selective Attention

Yang1,2*

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Mengsi Xu1,2†, Zhiai Li3†, Liuting Diao1,2, Lingxia Fan4, Lijie Zhang1,2, Shuge Yuan1,2, Dong

School of Psychology, Southwest University, Chongqing, China

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Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education,

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1

Chongqing, China

The School of Psychology and Cognitive Science, East China Normal University, Shanghai,

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3

China

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School of Psychology, Beijing Normal University, Beijing, China

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4

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† These authors contributed equally to this work.

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* Corresponding author：

School of Psychology, Southwest University Tiansheng Road No. 1, BeiBei District, Chongqing, China [email protected] +86 15086850384 +86-23-68252309

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Abstract Social exclusion has been thought to weaken one’s ability to exert inhibitory control. Existing studies have primarily focused on the relationship between exclusion and behavioral inhibition, and have reported that exclusion impairs behavioral inhibition. However, whether exclusion also affects selective attention, another important aspect of inhibitory control,

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remains unknown. Therefore, the current study aimed to explore whether social exclusion impairs selective attention, and to specifically examine its effect on two hypothesized mechanisms of selective attention: target enhancement and distractor suppression. The Cyberball game was used to manipulate social exclusion. Participants then performed a

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visual search task while event-related potentials were recorded. In the visual search task, target and salient distractor were either both presented laterally or one was presented on the

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vertical midline and the other laterally. Results showed that social exclusion differentially affected target and distractor processing. While exclusion impaired distractor suppression,

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reflected as smaller distractor-positivity (Pd) amplitudes for the exclusion group compared to the inclusion group, it did not affect target enhancement, reflected as similar target-negativity

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(Nt) amplitudes for both the exclusion and inclusion groups. Together, these results extend

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our understanding of the relationship between exclusion and inhibitory control, and suggest

thought.

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that social exclusion affects selective attention in a more complex manner than previously

Keywords: social exclusion, selective attention, N2pc, target-negativity, distractor-positivity

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Introduction Inhibitory control is the ability that allows people to control themselves in accordance with social norms, and is thus essential for daily life activities, and even survival. Indeed, deficits in inhibitory control have severe consequences: failing to brake to a halt when traffic lights turn red, for example, can lead to life-threatening traffic accidents. Given the

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importance of inhibitory control in social life, it is of great importance to understand how social interactions may affect this ability. Among numerous social interaction conditions, social exclusion, in which we are rejected or unaccepted by others, is one of the most common cases (Williams, 2007). Therefore the examination about how social exclusion

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influences inhibitory control is required.

Challenging the fundamental human need for strong and stable social bonds, social

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exclusion has been suggested to impair inhibitory control, with ample evidences demonstrated that excluded participants show more impulsive behaviors and aggression

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(Baumeister, DeWall, Ciarocco, & Twenge, 2005; Leary, Twenge, & Quinlivan, 2006; Lurquin, McFadden, & Harbke, 2014). One hypothesis for this effect is that the

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self-regulation of exclusion-related negative feelings depletes limited attentional resources,

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leaving insufficient resources for effective inhibitory control (Chester & DeWall, 2014; Lurquin et al., 2014). However, existing evidence has primarily focused on behavioral

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inhibition (i.e., self-control), and few studies have explored whether social exclusion exerts similar impacts on selective attention (i.e., interference control), another important aspect of inhibitory control (Diamond, 2013; Friedman & Miyake, 2004). This gap in the literature is surprising considering the specificity and importance of selective attention, and the possible influence it may have on behavioral inhibition. Specifically, although selective attention is found to closely related with behavioral inhibition (Friedman & Miyake, 2004), they are still different in many aspects (Adams & Jarrold, 2012). While behavioral inhibition involves

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suppressing impulsive or prepotent behaviors, which denotes relatively late-stage cognitive processes; selective attention enables us to selectively attend, to focus on what we choose, and to suppress attention to other stimuli, which represents relatively early-stage cognitive processes (DeWall, Maner, & Rouby, 2009; Diamond, 2013; Verbruggen, McLaren, & Chambers, 2014). Indeed, some researchers have demonstrated the differences between

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selective attention and behavioral inhibition (Adams & Jarrold, 2012). For instance, Adams and Jarrold (2012) asked autism children to complete a selective attention task (flanker task) and a behavioral inhibition task (stop-signal task), and found that children with autism had difficulty in inhibiting irrelevant distractors but not prepotent responses. Moreover,

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Verbruggen, McLaren, and Chambers (2014) put forward an action control framework, proposing that later action control might depend on early selective attention. According to

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this framework, early-stage selective attention would exert quite a significant influence on late-stage behavioral inhibition (Friedman & Miyake, 2004; Verbruggen, Stevens, &

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Chambers, 2014). This idea has also been demonstrated recently: using a modified stop-signal task (i.e., stop signal was surrounded by salient distractors), Verbruggen, Stevens,

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and Chambers (2014) reported that worse performance on selective attention (failing to

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efficiently suppress distractors and detect stop signal) was followed by weaker behavioral inhibition. Therefore, in the present study, we sought to extend these findings and

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simultaneously help fill the gap in the literature by examining how exclusion influences selective attention.

Surrounded by vast streams of information, selective attention is vital, as it allows us to filter relevant from irrelevant information (Feldmann-Wustefeld & Schubo, 2013; Wang, Yu, & Zhou, 2013). Two mechanisms of selective attention have been proposed: target enhancement and distractor suppression (Adam & Vogel, 2016; Hickey, Di Lollo, & McDonald, 2009). To explain these terms, imagine that you take a call on your phone while

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the television plays loudly in the background. To make it easier to hear the caller, you can either turn up the volume on your phone (target enhancement) or turn down the volume on the television (distractor suppression). Both mechanisms presumably lead to the same behavioral outcome: you hear the caller more clearly. To explore the mechanisms underlying selective attention (enhancement and suppression), Hickey et al. (2009) adopted the

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additional singleton paradigm in which participants searched for a target while ignoring another more salient distractor. In this paradigm, the relative position of the stimuli is crucial for examining selective attention; target and distractor stimuli are either both presented laterally, or one is presented laterally and the other on the vertical midline (i.e., unlateralized).

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Since unlateralized stimuli cannot typically elicit a lateralized event-related potential (ERP) component, target- and distractor-evoked potentials could be analyzed independently.

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Consequently, the authors found three lateralized components considered to be markers of selective attention: the N2pc, a negative deflection of the ERP contralateral to the attended

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items (goal relevant target or physically salient distractor) when target and distractors were both lateral, reflecting attentional selection; the Pd (distractor-positivity), a positive

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deflection contralateral to the distractor when only the distractor was presented laterally,

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reflecting distractor inhibition; and the Nt (target-negativity), a negative deflection contralateral to the target when only the target was presented laterally, reflecting target

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enhancement. Moreover, the Pd and Nt were hypothesized to be subcomponents of the N2pc (Hickey et al., 2009), and this assumption has recently been verified (Gaspar & McDonald, 2014). Currently, the influence of social exclusion on selective attention (target enhancement and distractor suppression) remains unexplored. However, some indirect evidence should be noted (Baumeister et al., 2005; DeWall, Baumeister, & Vohs, 2008; Weimer, 2016). Using a dichotic listening task, Baumeister et al. (2005) presented information simultaneously to both

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ears, and asked participants to ignore the material spoken in one ear so as to be able to screen the list of words presented to the other ear. They found that excluded participants displayed worse performance than included participants did, which indicates that excluded participants experienced a greater distractor interference effect. Similarly, Weimer (2016) asked participants to perform a Flanker task, and found that excluded participants showed a trend of

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worse performance (i.e., longer response time and higher error rate) relative to included participants, suggesting that rejected participants are more susceptible to the interference of distractor stimuli. Based on these studies, it seems plausible to conclude that exclusion impairs distractor suppression. However, the Flanker task and dichotic listening task might be

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completely different tasks, tapping into very different attentional/executive function mechanisms. More importantly, because the target and distractor processing were mixed and

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could not be separately examined in these studies, it is thus difficult to know to what extent these results were related to target enhancement or distractor suppression. The question

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therefore remains as to whether and/or how exclusion influences selective attention. In summary, although existing studies have investigated how social exclusion may

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influence behavioral inhibition, few studies have extended this research to selective attention.

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Furthermore, studies that have attempted to examine this failed to distinguish target processing from distractor processing (DeWall et al., 2008; Lurquin et al., 2014).

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Consequently, the present study aimed to explore how social exclusion affects selective attention, and to disentangle the processing of the target, as reflected by the Nt component, and inhibition of a distractor, as reflected by the Pd component. To manipulate social exclusion, we implemented a Cyberball game, and to measure selective attention, participants performed a unidimensional variant of the additional singleton search task (Gaspar & McDonald, 2014). Similar to Hickey et al. (2009), target and salient distractor stimuli were either both presented laterally or one was presented on the vertical midline and the other

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laterally. We hypothesized that social exclusion would affect selective attention, which would manifest as less efficient target processing at the behavioral level as well as smaller N2pc amplitude at the neural level. In order to overcome the fact that these measures were the combined outcomes of both distractor and target processing (Gaspar & McDonald, 2014), we

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also investigated how exclusion would affect the attention-related N2pc subcomponents, Pd and Nt, and more importantly, whether they would be similarly affected. More precisely, we hypothesized that exclusion would affect distractor and target processing differently. For distractor processing, we hypothesized that exclusion would impair distractor suppression,

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which would manifest as a smaller Pd amplitude for excluded participants than for included participants (DeWall et al., 2008; Lurquin et al., 2014). This hypothesis was made based on

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the close relationship between distractor inhibition and response inhibition (Friedman & Miyake, 2004): as many previous studies have demonstrated the impairment effect of

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exclusion on response inhibition, this hypothesis might be reasonable. Moreover, because some studies have shown that exclusion does not influence basic attention performance

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(Baumeister et al., 2005; Buelow, Okdie, Brunell, & Trost, 2015), we hypothesized that, for

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target processing, exclusion would not impair target enhancement, and that this would

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manifest as a similar Nt amplitude for excluded and included participants. Methods

Participants

Thirty-six female volunteers (18–22 years; M = 20.95, SD = 1.18) took part in this experiment and were randomly assigned to either the inclusion or exclusion group. Three participants were excluded, one from exclusion group and two from inclusion group, as they doubted the credibility of the Cyberball procedure. This resulted in a total of 17 and 16 participants in exclusion and inclusion group, respectively. We included only female

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participants because previous research has shown that female subjects are more likely to suffer from social exclusion (Benenson et al., 2013). The research protocol was approved by the Ethics Committee of the School of Psychology at Southwest University. Materials and Procedure Cyberball game. The Cyberball game was used to manipulate social exclusion

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(Williams & Jarvis, 2006). In this task, participants played a virtual toss game with two other players that they did not know and did not expect to meet. The degree of social exclusion and inclusion was manipulated by varying the number of times participants received the ball from other players. Participants in the inclusion group received the ball on approximately one-third

the ball twice at the beginning of the game.

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of the total throws (40 throws total), while participants in the exclusion group only received

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Need Threat Scale. After the Cyberball game, participants completed the 20-item Need Threat Scale (van Beest & Williams, 2006). This questionnaire required participants to

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self-assess their level of satisfaction for feelings of belonging, self-esteem, meaningful existence, and control during the game on a seven-point scale (1 = “do not agree” to 7 =

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“agree”; α = 0.92). Lower scores represented an increase in perceived threat to social needs

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and indicated the effectiveness of the social exclusion manipulation. Positive and Negative Affect Schedule. Participants also completed the 20-item

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Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). The PANAS includes ten items that assess positive emotions (e.g., interested) and ten items that assess negative emotions (e.g., irritable). Participants were instructed to self-assess their current emotional state on a five-point scale (1 = “very slightly or not at all” to 5 = “extremely”; α = 0.97). Visual search task. The visual search array comprised 6 circles presented equidistant (9.2°) from a central fixation point (Figure 1). Each circle was 3.4° in diameter, with a 0.3°

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thick outline, and a vertical or horizontal gray line (11 ±0.1 cd/m2, x = 0.295, y = 0.361) was contained within each of the circles. One of these circles was a target color, one was a distractor color, and the remaining four were uniformly colored nontargets (neither targets nor distractors). The target circle was dark yellow (11 ± 0.1 cd/m2, x = 0.384, y = 0.528), the distractor circle was red (11 ± 0.1 cd/m2, x = 0.599, y = 0.357), and the nontarget circles were

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green (11 ± 0.1 cd/m2, x = 0.275, y = 0.600). All stimuli were presented on a uniform black background (0.5 cd/m2). The red and dark yellow colors were selected so that the salience of the distractor would be considerably greater than that of the target. The salience was defined in terms of the local contrast between the green nontargets and each color: the distance in

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chromaticity space between red and green was greater than the distance between yellow and green (Gaspar & McDonald, 2014). The target, distractor, and nontarget circles were

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randomly presented in one of six positions, leading to three position conditions: lateral target and lateral distractor, midline target and lateral distractor, and lateral target and midline

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distractor (Figure 1).

In the experiment, each trial began with a fixation point presented for 600–1200 ms at

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the center of the screen. Then one of the search arrays (i.e., different position conditions)

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described above was presented with the fixation point at the center. Participants were instructed to maintain fixation on the central point and to identify the orientation (vertical or

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horizontal) of the gray line inside the target circle by pressing one of two response buttons within 2000 ms. Finally, a blank display appeared for 100 ms. A total of 140 trials were conducted for each position condition, which was randomly mixed across 5 blocks, so that there were 84 trials per block. Thirty practice trials were completed before starting the experiment. All stimuli were presented on a 19-inch CRT monitor viewed at a distance of 80 cm. Behavioral Analysis

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First, in order to the test whether the exclusion manipulation was effective, the Need Threat Scale and PANAS scores were separately analyzed with independent samples t-tests that compared the exclusion and inclusion groups. Second, for the visual search task, mean accuracies and response times (RTs) were separately analyzed with group (exclusion, inclusion) × position condition (lateral target and lateral distractor, midline target and lateral

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distractor, and lateral target and midline distractor) ANOVAs. Trials with false responses and exceedingly short or long RTs (± 2 SD from the mean RT calculated separately for each participant and each position condition) were removed from the RT analysis (Feldmann-Wustefeld & Schubo, 2013).

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Electroencephalography (EEG) Recording and Analysis

Electrical brain activity was recorded at 64 scalp sites, using tin electrodes mounted in

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an elastic cap (Brain Product, Munich, Germany), with references at the left and right mastoids and a ground electrode at the medial frontal aspect. Vertical electrooculograms

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(EOGs) for the right eye were recorded supra- and infraorbitally. The horizontal EOG was recorded as the left versus right orbital rim. All electrode impedance was <5 kΩ. EEGs and

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EOGs were amplified using a 0.05–100 Hz bandpass and continuously digitized at 500

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Hz/channel. Offline, the data were referenced to the average for the left and right mastoids (average mastoid reference), and a bandpass filter of 0.1–30 Hz was applied. Eye movement

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artifacts (such as eye movements and blinking) were excluded offline. Trials with horizontal EOG voltage exceeding ± 30 μV, and those contaminated with artifacts due to amplifier clipping and peak-to-peak deflection exceeding ± 80 μV, were excluded from the average. Only trials with correct responses were analyzed, and about 4% of all trials were excluded. The continuous EEG was segmented from 200 ms before to 500 ms after the search array onset. The lateralized ERP waveforms (N2pc, Pd, and Nt) were separately computed for each group (exclusion, inclusion), each position condition (lateral target and lateral distractor,

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midline target and lateral distractor, and lateral target and midline distractor), and each contralaterality (electrode ipsilateral or contralateral to the target location when target was presented laterally, or to the distractor location when target was presented on the vertical midline). The ipsilateral waveform was computed as the average of the left-sided electrode to the left-sided targets and the right-sided electrode to the right-sided targets, whereas the

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contralateral waveform was computed as the average of the left-sided electrode to the right-sided targets and the right-sided electrode to the left-sided targets (when target was presented on the vertical midline and distractor was presented laterally, the ipsilateral and contralateral waveforms were computed based on the electrodes ipsilateral or contralateral to

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the distractor location). Based on previous researches (Gaspar & McDonald, 2014; Hickey et al., 2009) and topographical map in current study (see Supplementary material), the N2pc, Pd,

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and Nt analyses were focused on electrodes PO7 and PO8, and were quantified as the mean amplitudes voltage in the time window of 250–320 ms. In order to test how exclusion

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influenced the N2pc and its subcomponents (the Pd and Nt), average waveforms were analyzed separately with group (exclusion, inclusion) × contralaterality (electrode ipsilateral

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vs. contralateral to the location of the target or distractor) ANOVAs for the three position

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conditions. Moreover, additional analyses were made to directly verify whether the effect of exclusion on Pd was different from that on Nt: the Pd and Nt amplitudes were first computed

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separately by subtracting the ipsilateral waveform from the contralateral waveform, and then these difference waves were analyzed using ANOVA with group (exclusion, inclusion) and subcomponents (Pd, Nt) as factors. Greenhouse-Geisser adjustments to the degrees of freedom were used for all statistical analyses where appropriate. Results Behavioral Data Manipulation checks. Behavioral results are presented in Table 1. The results

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revealed lower Need Threat scores for the exclusion group (M = 3.40, SD = 0.87) compared to the inclusion group (M = 5.03, SD = 0.92), t (31) = -5.20, p < .001, d = 0.70, power (1 – β) = 0.50 (Faul, Erdfelder, Buchner, & Lang, 2009). These results suggest that the needs of excluded participants were threatened compared to those of the included participants, confirming the effectiveness of the exclusion manipulation.

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Additionally, analysis of the PANAS scores demonstrated that neither positive nor negative emotion scores differed significantly between the exclusion and inclusion groups, respectively (positive: M = 27.12, SD = 6.94 vs. M = 28.50, SD = 5.93, t (31) = −0.61, p = .544, d = 0.98, power (1 – β) = 0.78; negative: M = 20.12, SD = 8.87 vs. M = 18.25, SD =

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9.30, t (31) = 0.59, p = .559, d = 0.78, power (1 – β) = 0.58). Consistent with previous studies

result in explicit emotional responses.

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(Twenge, Catanese, & Baumeister, 2003), these results suggest that social exclusion did not

Visual search task. For accuracy, the main and interaction effects of group and

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position condition were not significant, ps > .101. For RT, the ANOVA revealed a main effect of group, F (1, 31) = 4.63, p = .039, η2p = 0.13, power (1 – β) = 0.70, with slower responses

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for exclusion (M = 721.04 ms, SD = 78.50) than for inclusion (M = 662.20 ms, SD = 78.52)

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group (Table 1); and a main effect of position condition, F (2, 30) = 5.43, p = .010, η2p = 0.26, power (1 – β) = 0.97, with slower responses for midline target and lateral distractor condition

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than for lateral target and lateral distractor condition, and lateral target and midline distractor condition (ps < .009). However, the interaction of group and position condition was not significant, F (2, 30) = 0.02, p = .981, η2p < 0.01, power (1 – β) = 0.06. ERP Data Figure 2a shows the grand-average lateralized ERPs recorded at PO7/PO8, contralateral or ipsilateral to the lateralized stimuli for both the exclusion and inclusion groups. Figure 2b shows the difference waves of the lateralized ERPs (i.e., contralateral –

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ipsilateral sides), and Figure 2c shows the mean amplitudes of the N2pc, Pd, and Nt components. For lateral target and lateral distractor condition, the ANOVA results revealed a main effect of contralaterality, F (1, 31) = 62.82, p < .001, η2p = 0.67, power (1 – β) = 1.00, with a more negative amplitude at contralateral electrode sites (M = 0.22 µV, SD = 1.71) relative to

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ipsilateral sites (M = 2.10 µV, SD = 1.78), reflecting the emergence of the N2pc. Moreover, the interaction between group and contralaterality was also significant, F (1, 31) = 6.65, p = .015, η2p = 0.18, power (1 – β) = 1.00, which indicated that the N2pc was smaller for excluded participants than for included participants (Figure 2c). These results suggested that

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exclusion affected selective attention.

For midline target and lateral distractor condition, the ANOVA results revealed a main

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effect of contralaterality, F (1, 31) = 27.81, p < .001, η2p = 0.47, power (1 – β) = 1.00, with a more positive amplitude at contralateral electrode sites (M = 1.35 µV, SD = 1.84) relative to

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ipsilateral sites (M = 0.89 µV, SD = 1.74), which reflects the emergence of the Pd component. Moreover, the interaction between group and contralaterality was also significant, F (1, 31) =

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6.01, p = .020, η2p = 0.16, power (1 – β) = 1.00, indicating that the Pd was smaller for

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excluded participants than for included participants (Figure 2c). These results suggested that exclusion impaired distractor suppression.

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For lateral target and midline distractor condition, the ANOVA results only revealed a main effect of contralaterality, F (1, 31) = 60.10, p < .001, η2p = 0.69, power (1 – β) = 1.00, with a more negative amplitude at contralateral electrode sites (M = 0.22 µV, SD = 1.72) relative to ipsilateral sites (M = 1.94 µV, SD = 1.83), which reflects the emergence of the Nt component. However, the interaction between group and contralaterality was not significant, F (1, 31) = 0.83, p = .369, η2p = 0.03, power (1 – β) = 0.64, suggesting that exclusion did not affect target enhancement.

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For the additional analyses (verify whether the effect of exclusion on Pd was different from that on Nt), the ANOVA results revealed a main effect of subcomponents, F (1, 31) = 80.13, p < .001, η2p = 0.72, power (1 – β) = 1.00, with a more positive Pd amplitude (M = 0.46 µV, SD = 0.36) relative to Nt amplitude (M = -1.72 µV, SD = 0.83). Moreover, the interaction between group and subcomponents also showed a trend to be significant, F (1, 31)

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= 3.15, p = .086, η2p = 0.09, power (1 – β) = 0.99, indicating that the effects of social exclusion on the Pd and Nt might be in the opposite direction. Discussion

The present study investigated whether social exclusion affects selective attention - an

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important component of inhibitory control - and whether this influence is related to target enhancement, distractor suppression, or both. Consistent with our expectations, we found

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behavioral and ERP evidence to show that exclusion did affect selective attention: excluded participants displayed slower behavioral responses and smaller N2pc amplitudes compared to

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included participants. More importantly, our results showed that these influences were driven by distractor suppression but not by target enhancement. This was evidenced by smaller Pd

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amplitude (a marker of distractor suppression) for excluded participants compared to

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included participants, but similar Nt amplitudes (a marker for target enhancement) between the two groups. Together, these results suggest that exclusion influences selective attention by

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impairing distractor suppression, but not target enhancement. We will now discuss some possible explanations for this. The hypothesis of limited attentional capacity proposes that all processes underlying cognitive control depend on common and limited attentional resources (Kahneman, 1973). Previous studies have shown that, when experiencing exclusion, participants deploy resources (i.e., greater right ventrolateral prefrontal cortex recruitment) to regulate the distress of social exclusion (Chester & DeWall, 2014; Riva, Romero Lauro, DeWall,

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Chester, & Bushman, 2015). Therefore, our finding that excluded participants were less able to suppress distractor representation might seem reasonable, because participants supposedly deployed more resources to regulate the negative feelings induced by exclusion, leaving fewer resources for distractor inhibition. If this explanation is true, one may ask why the resource consuming regulation process did not hinder target processing. This may be related

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to task complexity; we can suppose that distractor suppression was closely related to executive control and required more voluntary cognitive effort, and was thus more susceptible to the regulation process during exclusion. By contrast, target enhancement may be more automatic and may require fewer resources, which would explain why it was not so

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easily affected by exclusion (Baumeister et al., 2005; Buelow et al., 2015).

The attentional limitation explanation is also consistent with the salient-signal

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suppression view of attentional control (Jannati, Gaspar, & McDonald, 2013), who proposes that (1) salient visual items compete for control during the stage of visual processing that

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precedes selection, and (2) the visual system decides whether to select the location of the most salient item for further processing (selection for identification) or to selectively suppress

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that location to avoid further processing of the item there (thus enabling more efficient

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selection of the target). They further point out that this decision may be based on an observer’s current attentional control settings (Sawaki & Luck, 2010). More related to the

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present study, the excluded participants could deploy little available resources to exert top-down control, in other word, they might have difficulty in suppressing the processing of salient distractor. This speculation is supported by the behavioral results, namely the longer response time for exclusion relative to inclusion group (as included participants could exert top-down control to suppress the processing of salient distractor, enabling more efficient selection of the target). Another interpretation of our results is related to the fundamental human need to

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belong (Baumeister & Leary, 1995). In particular, socially excluded people wish to make new social connections, but at the same time want to make sure that they will not suffer rejection again (Park & Baumeister, 2015). In this sense, socially excluded participants may have responded differently to possible exclusion-related (distractor) and inclusion-related (target) stimuli. To more fully explain, missing an exclusion-related cue may result in serious

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consequences for excluded individuals (e.g., being rejected again), and so the most adaptive response is to pay more attention to all potential threats in order to determine whether they are dangerous or not (Qualter et al., 2013; Xu, Ding, et al., 2016). In the current study, participants were asked to focus on target and make correct responses, but the appearance of

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distractor disturbed target processing, and thus conflicted with task demands. Such conflict stimuli can be registered as aversive and negative stimuli (Dreisbach & Fischer, 2012), and

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excluded participants exhibit cognitive bias to treat negative stimuli as potential exclusion-related cues (Cameron, Stinson, Gaetz, & Balchen, 2010; Downey & Feldman,

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1996; Downey, Khouri, & Feldman, 1997). Therefore, excluded participants in the present study might have treated distractor stimuli as potential exclusion cues, and may have thus

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allocated more attention to explore it but not to suppress its representation, contributing to the

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smaller Pd amplitude. In contrast, given that excluded participants have a stronger motivation to reconnect with others, they may take every opportunity to display their capability so as to

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increase the likelihood of being included, especially with the appearance of an inclusion-related cue (DeWall et al., 2008; Maner, DeWall, Baumeister, & Schaller, 2007). In the current study, this reconnection motivation would drive excluded participants to treat targets as potential inclusion cues (because successful target processing would meet the experimenter’s expectations and leave a good impression, which is essential for social acceptance). Thus, excluded participants may strive to follow the task demands (i.e., focusing on the target and making correct responses), contributing to the unimpaired ability of target

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processing. Although the abovementioned explanations are plausible, one important caveat should be noted. In current study, the target and distractor singleton were different from nontargets within the dimension (color), but not across dimensions (shape and color), as has been the case in previous search tasks (Gaspar & McDonald, 2014; Wei, Muller, Pollmann, & Zhou,

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2011). While the within-dimension setting might cause people to suppress signals arising from salient but irrelevant items when searching for a known target

(salient-signal-suppression hypothesis), the cross-dimension setting might cause people to up-weight the relevant feature dimension (e.g., shape) and boost the priority of stimuli

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defined by this dimension (dimensional-weighting hypothesis). These different strategies could contribute to larger Pd amplitude but a smaller Nt amplitude in within-dimension

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settings relative to cross-dimension settings (Gaspar & McDonald, 2014). Consequently, we cannot exclude the possibility that the lack of difference in the Nt component was due to a

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floor effect, and we cannot be sure that our current results would be replicated in a cross-dimension setting. Therefore, we encouraged future studies to explore this issue.

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To the best of our knowledge, the current study was the first to investigate the

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mechanisms underlying the influence of exclusion on selective attention. Herein, we have presented evidence that social exclusion exerted different impacts on target and distractor

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processing; these results extend the existing literature from both a methodological and a theoretical point of view. At the methodological level, the current results demonstrate that the additional singleton search task is an appropriate task to test selective attention and could address some defects existed in previous studies. Specifically, previous studies usually adopted Stroop and Flanker tasks to investigate selective attention (DeWall et al., 2008; Lurquin et al., 2014; Themanson, Ball, Khatcherian, & Rosen, 2014), which might be inappropriate and problematic. To begin with, these tasks involve centrally presented sparse

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stimulus arrays, but in daily life we often need to search for a target in an array of stimuli spread out in space. Next, the Flanker task is perhaps a better measure of response competition than attentional capture by irrelevant stimuli in that “irrelevant” stimuli in the Flanker task are associated with an alternative response (Moser, Becker, & Moran, 2012). Finally and most importantly, it is difficult to distinguish distractor processing from target

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processing with these tasks. Therefore, future studies should adopt the additional singleton search task to explore selective attention.

At the theoretical level, these results firstly extend the existing literature that demonstrates the impact of exclusion on behavioral inhibition to also show that social

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exclusion affects selective attention (distractor inhibition). Next, our results could also help shed light on the relationship between exclusion and inhibitory control. Although many

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studies have tried to verify whether exclusion would impair, improve, or exert no influence on inhibitory control, most have reported the hindrance effect of exclusion (DeWall et al.,

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2008; Lurquin et al., 2014). Some more recent studies have suggested that exclusion exerts quite complicated influences on inhibitory control (Otten & Jonas, 2013; Xu, Li, et al., 2016).

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For example, Xu et al. (2016) used a modified Go/No-Go task to investigate how exclusion

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affected conscious and unconscious behavioral inhibition. The authors observed that exclusion impaired conscious behavioral inhibition (as indexed by a smaller P3 amplitude),

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but improved unconscious behavioral inhibition (as indexed by a larger P3 amplitude). Similarly, in exploring how exclusion influences selective attention, our current study found that exclusion impaired distractor suppression (indexed by smaller Pd amplitude for the excluded group vs. the included group) but not target enhancement (indexed by similar Nt amplitudes for excluded and included groups). Taken together, these results highlight the complex effect of exclusion on inhibitory control (both behavioral inhibition and selective attention), and show that previous ideas of a fixed effect (impairment, improvement, or no

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influence) were overly simplified. Furthermore, here we considered selective attention and behavioral inhibition as independent aspects of inhibitory control (Diamond, 2013; Friedman & Miyake, 2004). However, some researchers have demonstrated that early selective attention can exert substantial influences on later behavioral inhibition (Verbruggen, Stevens, et al., 2014). Indeed, our findings that exclusion impaired distractor suppression are similar to

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previous studies reporting that exclusion impaired behavioral control, which is suggestive of a possible close relation between behavioral inhibition and selection attention. The most probable solution is that selective attention and behavioral inhibition are closely related and jointly determine the performance on an inhibition task. Future studies should test this

selective attention and behavioral inhibition.

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assumption and systematically investigate how exclusion influences the interaction between

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Some limitations of the current study should be noted. First, because we only included female participants in the current study, our results could not be generalized to male subjects.

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Although our choice was based on the fact that women have been reported to be more likely to suffer from social exclusion (Benenson et al., 2013), future studies should include both

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female and male subjects, and could also make a comparison. Second, the potential influence

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of individual differences was not considered. Some studies have shown that individual differences such as rejection sensitivity and anxiety can influence the relationship between

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exclusion and cognitive control (Ayduk et al., 2008; DeWall et al., 2011). Future studies should take this issue into consideration. Third, the current study did not employ a control group. Thus, we cannot fully decipher whether between-group differences were due to an effect within the excluded group, an effect within the included group, or both. Therefore, future studies should try to avoid this problem. Fourth, the sample size of current study was small to some extent, but the power analyses results showed that power (1 – β) ranged from 0.50 to 1.00, and most of which were larger than the acceptable power (0.8), thus we thought

ACCEPTED MANUSCRIPT Running Head: SOCIAL EXCLUSION INFLUENCES SELECTIVE ATTENTION our results were acceptable. However, future study should include larger sample size to inspect the present results. Fifth, as the exclusion’s impact could persist only about 50 min (Buelow et al., 2015), to shorten the experiment duration, we did not include a control condition (i.e., no distractor condition) in current study. This manipulation was a major shortcoming as we could not make a comparison between groups on control condition;

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neither could we make a direct comparison between distractor condition and control condition. Therefore, we encourage future studies to test current results with typical visual search task including both distractor and control conditions. Conclusion

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By combining exclusion manipulation and visual search task, the current study explored how social exclusion affects selective attention and its subcomponents. We found

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that exclusion impaired distractor inhibition but not target enhancement, which extends our understanding of the relationship between exclusion and inhibitory control. Given the

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importance of the current investigation, more studies are needed to further explore the

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relationship between social exclusion and inhibitory control.

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ACCEPTED MANUSCRIPT Running Head: SOCIAL EXCLUSION INFLUENCES SELECTIVE ATTENTION Acknowledgments This work was supported by the National Natural Science Foundation of China (71472156)

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and the Fundamental Research Funds for the Central Universities (SWU1509110).

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Table 1 Means (M) and standard deviations (SD) of the Need Threat Scale (and its subscales: belonging, self-esteem, control, and meaningful existence), the Positive and Negative Affect Schedule (PANAS) scores, and behavioral results (accuracy and reaction times) for the visual

Exclusion M (SD) 3.40 (0.87)

Belonging

3.44 (0.83)

Self-esteem

3.37 (0.85)

Control

3.34 (0.84)

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Need threats (average score)

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search task.

Meaningful existence

Negative affect

M (SD)

5.03 (0.92) 5.20 (1.09) 5.22 (1.11) 4.35 (0.89)

3.41 (0.83)

5.25 (0.92)

27.12 (6.94)

28.50 (5.93)

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Positive affect

Inclusion

20.12 (8.87)

18.25 (9.30)

Lateral target and lateral distractor

0.96 (0.02)

0.97 (0.03)

Midline target and lateral distractor

0.97 (0.02)

0.98 (0.02)

Lateral target and midline distractor

0.97 (0.02)

0.96 (0.04)

Lateral target and lateral distractor

720.04 (87.01)

660.68 (68.73)

Midline target and lateral distractor

726.70 (91.37)

667.60 (65.32)

Lateral target and midline distractor

716.38 (84.73)

658.33 (72.45)

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Accuracy

Reaction times (ms)

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Figure 1. (a) Example trial from the visual search task and (b) examples of the three position

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conditions used in the present study.

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Figure 2. (a) Grand-average lateralized event-related potentials (ERPs) recorded at PO7/PO8,

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contralateral (solid lines) and ipsilateral (dashed lines) to the lateralized stimuli for both the

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exclusion (upper row) and inclusion (lower row) groups. The N2pc is the difference between electrodes contralateral and ipsilateral to the target locations when a distractor is presented

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laterally. The distractor-positivity (Pd) is the difference between electrodes contralateral and ipsilateral to the distractor locations when a target is presented vertically. The target-negativity (Nt) denotes this difference when a distractor is presented vertically; (b) Shows the same data as (a) but as difference waves (contralateral – ipsilateral); (c) Shows the mean amplitudes of N2pc, Pd, and Nt. The gray rectangle represents the time window selected for analyses (250–320 ms after the search array onset), errors bars represent standard errors, and an asterisk represents p < .050.

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Highlights 1. The relationship between social exclusion and selective attention is investigated. 2. Social exclusion impairs distractor inhibition, as evidenced by smaller Pd amplitude for exclusion group than for inclusion group. 3. Social exclusion exerts no impairment effect on target processing, as evidence by similar Nt amplitude

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between exclusion group and inclusion group.