Elsevier

Brain and Cognition

Volume 78, Issue 1, February 2012, Pages 63-73
Brain and Cognition

Attention training and the threat bias: An ERP study

https://doi.org/10.1016/j.bandc.2011.10.007Get rights and content

Abstract

Anxiety is characterized by exaggerated attention to threat. Several studies suggest that this threat bias plays a causal role in the development and maintenance of anxiety disorders. Furthermore, although the threat bias can be reduced in anxious individuals and induced in non-anxious individual, the attentional mechanisms underlying these changes remain unclear. To address this issue, 49 non-anxious adults were randomly assigned to either attentional training toward or training away from threat using a modified version of the dot probe task. Behavioral measures of attentional biases were also generated pre- and post-training using the dot probe task. Event-related potentials (ERPs) were generated to threat and non-threat face pairs and probes during pre- and post-training assessments. Effects of training on behavioral measures of the threat bias were significant, but only for those participants showing pre-training biases. Attention training also influenced early spatial attention, as measured by post-training P1 amplitudes to cues. Results illustrate the importance of taking pre-training attention biases in non-anxious individuals into account when evaluating the effects of attention training and tracking physiological changes in attention following training.

Highlights

► Behavioral effects of attention training depend on pre-training biases. ► Early spatial attention to emotional stimuli is affected by attention training. ► Physiological changes in attention are associated with behavior after training.

Introduction

Anxious individuals show an attentional bias towards threat (Mathews and Mackintosh, 1998, Mogg and Bradley, 1998). For example, using the dot probe task, several labs have demonstrated that anxious, but not non-anxious individuals, detect probes faster when they are preceded by threatening versus non-threatening stimuli (e.g., words, emotional faces, phobia-specific stimuli) (MacLeod et al., 1986, Mogg and Bradley, 2005, Mogg et al., 2004, Wilson and MacLeod, 2003), a pattern confirmed by a recent meta-analysis (Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van IJzendoorn, 2007).

Several studies have now shown that this threat bias can be reduced in anxious participants using a modified version of the dot probe task in which participants are trained to avoid threat. Specifically, when participants are presented with a systematic contingency between cue and probe locations to induce a temporary bias away from threat (e.g., probes always appear in the location of the non-threatening stimulus), there are reductions in attentional bias to threat and symptoms of generalized anxiety disorder (Amir, Beard, Burns, & Bomyea, 2009), social anxiety disorder (Schmidt, Richey, Buckner, & Timpano, 2009), and social phobia (Amir et al., 2009). A recent meta-analysis demonstrated that this type of attention training, attentional bias modification (ABM), is effective in reducing anxiety and stress responsiveness at a medium effect size (d = .61) (Hakamata et al., 2010). However, while threat bias reduction is highly relevant for anxiety treatment, the complementary question of whether an attentional bias to threat can be induced may inform our understanding of the causal relationship between the threat bias and anxiety. This is a primary goal of the present study.

A small number of behavioral studies have addressed this by demonstrating that an attentional bias to threatening stimuli can be experimentally induced in non-anxious participants using a modified version of the dot probe task with a systematic contingency between the location of the threatening stimulus and probe. Specifically, participants trained towards threat in this manner show speeded response latencies to probes cued by threat as well as elevations in stress responsivity (Clarke et al., 2008, Eldar et al., 2008, MacLeod et al., 2002). Taken together, these ABM studies suggest that there may be a causal link between the threat bias and anxiety, since reducing the threat bias also reduces symptoms and anxiety whereas inducing a threat bias increases emotional vulnerability to stress (Bar-Haim, 2010). Despite these promising early findings, little is known about the cognitive changes underlying ABM effects, and behavioral measures alone lack the sensitivity to capture subtle changes in distinct cognitive processes that may be influenced by attention training.

Although these behavioral studies have provided important information about the threat bias in anxiety and the utility of ABM in clinical and normative groups, they cannot measure very rapid attentional processing of threat. Scalp-recorded event-related potentials (ERPs), which can capture changes on the order of milliseconds, are particularly sensitive to attentional processes related to the threat bias. For example, four published studies have used ERPs during non-attention training versions of the dot probe task to track the time course of the threat processing in anxious relative to non-anxious participants (Bar-Haim, 2010, Fox et al., 2008, Helfinstein et al., 2008, Mueller et al., 2009). Fox et al. (2008) found greater N2pc amplitudes to angry faces for anxious relative to non-anxious individuals in a go/no-go version of the dot probe task, demonstrating early attentional capture by threatening stimuli in anxiety. Also using a go/no-go version of the dot probe task, Mueller et al. (2009) found greater P1 amplitudes to angry-neutral face pairs versus happy-neutral face pairs in participants with social anxiety disorder, providing further support for enhanced early and relatively automatic attention in the threat bias. In a primed version of the dot probe task, Helfinstein et al. (2008) found greater P1 and reduced N1 amplitudes to face pairs in socially anxious versus non-anxious individuals. Only angry-neutral face pairs were used in this study, however, thus precluding any conclusions about threat-specific emotional processing in social anxiety. In contrast, Eldar et al. (2010), by using the dot probe task with angry–neutral, happy–neutral, and neutral–neutral face pairs, were able to assess processing of threat relative to happy stimuli. They found that anxious individuals showed enhanced C1 amplitudes to angry-neutral face pairs and greater P2 amplitudes to all face pairs relative to controls. The authors argue that this pattern suggests enhanced automatic capture of attention (C1) as well as greater elaborated processing of emotional faces (P2) in anxious individuals. Taken together, these studies provide suggestive evidence for the hypothesis that the threat bias may be driven both by early attentional capture by threat as well as later, more elaborated processing.

One ABM study addressed this hypothesis directly by examining training effects on specific ERPs thought to reflect relatively early/automatic and later/elaborated cognitive processes (Eldar & Bar-Haim, 2010). In this study, anxious participants who were trained to attend to neutral faces showed reductions in P2 and enhanced N2 amplitudes to the face pairs on the post-training assessment. The authors suggest that this pattern of changes reflects reduced distraction by decreasing the processing of emotional stimuli (P2) and greater control of attentional resources (N2) since the N2 has been linked to activity of anterior cingulate cortex (van Veen & Carter, 2002). Furthermore, participants who were trained away from threat showed increases in P3 amplitudes to probes replacing neutral faces from angry-neutral pairs, regardless of anxiety level (Eldar & Bar-Haim, 2010). Taken together, results suggest that the ABM procedure may facilitate recruitment of both automatic and more elaborated/controlled cognitive functions during the dot probe task. This interpretation of the ERP findings is bolstered by recent fMRI studies demonstrating that lateral prefrontal cortical areas (Browning, Holmes, Murphy, Goodwin, & Harmer, 2010) and temporal occipital areas (Monk et al., 2004) mediate the modification of attention biases. It remains unclear, however, what cognitive processes might mediate the modification of attention biases in normative, non-clinical samples.

In addition to using ERPs to disambiguate the processes underlying attention changes following training, changes in behavioral components of the threat bias can be assessed as well. The proposed components of the threat bias are facilitated attention to threat, difficulty disengaging from threat, and strategic avoidance of threat (Cisler et al., 2009, Cisler and Koster, 2010). In its original format, the dot probe task can confirm the presence of the threat bias but cannot identify the mechanisms through which it occurs. A modification of the task includes an additional trial type, where two non-threatening stimuli are presented simultaneously and then followed by a probe in the location of one of the stimuli (Koster, Crombez, Verschuere, & De Houwer, 2004). Response latencies from these baseline trials are compared to the threat and non-threat cued trials: Faster responding to threat versus baseline cues suggests greater initial capture of attention by threat (i.e., vigilance toward the threatening location), while faster responding to baseline versus non-threat cues suggests greater attentional hold by threat (i.e., difficulty disengaging from the threatening location). Several studies using this adapted dot probe methodology have supported a difficulty disengaging model of attentional bias, but not a facilitated attention model (Koster et al., 2004, Salemink et al., 2007). Attentional avoidance, directing attention away from threatening stimuli, is generally found following initial vigilance for threat when stimulus presentation durations are prolonged (Koster et al., 2006, Mogg et al., 2004). In the present study we included angry and happy faces, consistent with an early attentional training study by Mathews and MacLeod (2002). Thus, in order to assess attentional capture and hold by threat (angry face) relative to non-threat (happy face) a pair of happy faces was used as the baseline trial. Happy faces were used instead of neutral faces in order to hold arousal constant while having both a threat-relevant and non-threat relevant stimulus.

Several studies have demonstrated that the pattern of bias toward or avoidance of threat depends on the duration of exposure to stimuli. Using both highly threatening (HT) and moderately threatening (MT) stimuli, Koster, Verschuere, Crombez, and Van Damme (2005) demonstrated that both anxious and non anxious individuals show a bias toward HT at 100 ms and 500 ms, but only anxious individuals show a bias toward MT at 500 ms. Among just non-anxious individuals, the threat bias is found at 100 ms but not at 500 ms (Koster et al., 2007, Mogg et al., 1997). However, in another study the threat bias was found at 100 ms and an avoidance of threat at 500 ms for non-anxious participants (Cooper & Langton, 2006). Taken together, these studies suggest for non-anxious individuals that at shorter durations the threat bias is present while at longer durations it is either absent or reversed. However, a more recent study varied cue duration and the effects of ABM did not appear for the non-anxious sample of participants at the shorter durations (i.e., 30 and 100 ms) (Koster, Baert, Bockstaele, & De Raedt, 2008). Thus, in order to explore how the effects of presentation duration on attentional bias interact with ABM, the current study included short (100 ms) and long (500 ms) cue conditions.

In summary, the present study addressed important gaps in the research on ABM in several ways. First, we examined whether a bias towards threat can be induced or reduced in non-anxious adults using the dot probe task, by training participants to develop either an attentional bias towards angry faces (train toward threat group) or away from angry faces (train away from threat group). Second, we incorporated two modifications to the dot probe task, in order to assess changes in attentional capture and hold: (1) we included baseline trials (with two non-threatening stimuli, happy faces) in order to distinguish between vigilance for threat and difficulty disengaging from threat in the attentional bias; and (2) we included two presentation durations to assess changes in the threat bias in short and long exposure conditions. Third, we examined the neural processes underlying ABM by analyzing whether ABM influenced ERPs reflecting early and later stages of attentional processing.

We tested the following predictions for behavioral and ERP effects. Given the previous ABM study incorporating ERPs (Eldar & Bar-Haim, 2010), we predicted that individuals in the train away from versus train toward threat group will showed decreased attentional bias scores (attentional bias, vigilance, difficulty disengaging) and reduced attentional capture by threat as indicated by reduced ERP amplitudes at early (P1) and later, more elaborated stages (N170, P2, N2, P3) of attentional processing in response to threatening versus non-threatening cues and probe locations. In addition, we predicted that individuals in the train away from threat versus train toward threat group will show reduced subjective anxiety.

We also tested the hypothesis that effects of ABM will be greater for cues presented at short (100 ms) versus long (500) exposure durations since previous research suggests that the threat bias is most clearly detectable for non-anxious individuals when stimuli are briefly presented (Koster et al., 2005, Koster et al., 2007, Mogg et al., 1997).

Additionally, because the threat bias is more prevalent among anxious individuals (Bar-Haim et al., 2007), we expected that in this non-clinical sample attention training effects may only occur for those participants who already show a bias towards threat at baseline (for the train away from threat group) or a bias away from threat at baseline (for the train toward threat group), due to ceiling and floor effects, respectively.

Finally, in exploratory analyses, we examined whether relationships exist between ERP and behavioral biases following ABM. We predicted that greater neural processing of threat relative to non-threat at post-training will correlate with greater behavioral biases to threat, whereas greater neural processing of non-threat will correlate with reduced behavioral biases.

Section snippets

Participants

Participants were 61 non-disordered adults recruited through the psychology participant research pool at Hunter College, The City University of New York. Prior to completing the tasks, participants were screened for psychological impairments (anxiety, depression) via self-report questionnaires. Twelve participants were excluded from analyses for the following reasons: participant refusal (f = 1), experimenter error during EEG recording (f = 2), too many incorrect responses during the dot probe task

Descriptive statistics

See Table 1, Table 2 for descriptive statistics of behavioral biases and ERP amplitudes at pre- and post-training. There were no differences between the train toward train away from threat groups on either state anxiety [t(47) = −0.25, p = .80] or trait anxiety [t(47) = 1.07, p = .28]. For all analyses, outliers in the data were replaced with sample means.

Below, we present separate analyses for behavioral threat bias, subjective anxiety, and ERP outcome variables for the sample as a whole. Following

Discussion

The goal of the present study was to examine the effects of ABM on behavioral attention biases and neurophysiological measures of early and later attention processing in non-anxious individuals. Results suggest training-related changes in the behavioral threat bias only emerged among a subset of participants who showed pre-training attention biases towards and away from threat. In addition, ABM also influenced ERP measures of early spatial attention to emotional face cues. Finally,

Acknowledgments

This research was supported by grants from the National Institutes of Mental Health (NIMH) Grant K01MH075764 and S06GM060654 awarded to Tracy A. Dennis. The project described was supported by Grant Number RR003037 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NCRR or NIH.

References (50)

  • R.M. Klein

    Inhibition of return

    Trends in Cognitive Sciences

    (2000)
  • E.H.W. Koster et al.

    Selective attention to threat in the dot probe paradigm: Differentiating vigilance and difficulty to disengage

    Behaviour Research and Therapy

    (2004)
  • E.H.W. Koster et al.

    Components of attentional bias to threat in high trait anxiety: Facilitated engagement, impaired disengagement, and attentional avoidance

    Behaviour Research and Therapy

    (2006)
  • E.H.W. Koster et al.

    Time-course of attention for threatening pictures in high and low trait anxiety

    Behaviour Research and Therapy

    (2005)
  • A. Lutz et al.

    Attention regulation and monitoring in attention

    Trends in Cognitive Sciences

    (2008)
  • K. Mogg et al.

    A cognitive-motivational analysis of anxiety

    Behaviour Research and Therapy

    (1998)
  • K. Mogg et al.

    Time course of attentional bias for threat information in non-clinical anxiety

    Behaviour Research and Therapy

    (1997)
  • K. Mogg et al.

    Effect of threat cues on attentional shifting, disengagement and response slowing in anxious individuals

    Behaviour Research and Therapy

    (2008)
  • C.S. Monk et al.

    Experience-dependent plasticity for attention to threat: Behavioral and neurophysiological evidence in humans

    Biological Psychiatry

    (2004)
  • E. Salemink et al.

    Selective attention and threat: Quick orienting versus slow disengagement and two versions of the dot probe task

    Behaviour Research and Therapy

    (2007)
  • N. Tottenham et al.

    The NimStim set of facial expressions: Judgments from untrained research participants

    Psychiatry Research

    (2009)
  • V. van Veen et al.

    The anterior cingulate as a conflict monitor: fMRI and ERP studies

    Physiology & Behavior

    (2002)
  • N. Amir et al.

    Attention modification program in individuals with generalized anxiety disorder

    Journal of Abnormal Psychology

    (2009)
  • N. Amir et al.

    Attention training in individuals with generalized social phobia: A randomized controlled trial

    Journal of Consulting and Clinical Psychology

    (2009)
  • Y. Bar-Haim

    Research review: Attention bias modification (ABM): A novel treatment for anxiety disorders

    The Journal of Child Psychology and Psychiatry

    (2010)
  • Cited by (58)

    • Positive attention bias in high socially anxious individuals: Evidence from an ERP study

      2022, Journal of Affective Disorders
      Citation Excerpt :

      These results suggest that high socially anxious individuals show significant automatic and sustained attention processing to positive stimuli. All of these researchers used positive stimuli as non-threatening stimuli and compared them to the negative stimuli (Li et al., 2018; O'Toole and Dennis, 2012; Pfabigan et al., 2014). Therefore, positive attention bias in these studies was explained from the view of further understanding of the negative attention bias.

    • Enhanced contralateral theta oscillations and N170 amplitudes in occipitotemporal scalp regions underlie attentional bias to fearful faces

      2021, International Journal of Psychophysiology
      Citation Excerpt :

      N170 was measured as the mean amplitude between 150 and 190 ms (Carlson and Reinke, 2010) and the N2pc was the mean amplitude between 250 and 320 ms (Holmes et al., 2009) after face onset. The P7 (left hemisphere) and P8 (right hemisphere) electrodes were used for N170 (Carlson and Reinke, 2010; O'Toole and Dennis, 2012; Rossignol et al., 2013; Torrence et al., 2018) and N2pc (Brosch et al., 2011; Holmes et al., 2009, 2014; Osinsky et al., 2014; Reutter et al., 2017). For N170 and N2pc analysis we collapsed across hemispheres and used repeated measures one-way ANOVAs to assess the effect of laterality (contralateral, ipsilateral, and neutral) on mean ERP amplitudes.

    View all citing articles on Scopus
    View full text