Neural mechanisms underlying heterogeneous expression of threat-related attention in social anxiety

Highlights

• Socially anxious individuals may exhibit multiple patterns of attention to threat.

• A novel computation method dissociated multiple attention patterns to threat.

• Attention patterns to threat exhibited differential Default Mode Network activity.

• Attention patterns to threat also exhibited differential amygdala-STS connectivity.

• In social anxiety, threats elicit functionally distinct patterns of attention.

Abstract

Theoretical frameworks propose that threat-related attention, which is typically assessed using the dot-probe paradigm, plays a key role in social anxiety. Within the dot-probe paradigm, novel computational approaches demonstrate that anxious individuals exhibit multiple patterns of threat-related attention on separate trials. However, no research has leveraged such novel computational methods to delineate the neural substrates of threat-related attention patterns in social anxiety. To address this issue, fifty-three socially anxious adults (22.38 ± 3.12, 33 females) completed an fMRI-based dot-probe paradigm. A novel, response-based computation approach revealed conjoint patterns of vigilant orientation, avoidant orientation, slow disengagement, and fast disengagement, which were masked by standard computation measures. Compared to vigilant orientation and fast disengagement, avoidant orientation and slow disengagement were greater in magnitude, respectively. Mirroring behavioral findings, avoidant orientation and slow disengagement elicited greater deactivation of several regions within the Default Mode Network and stronger connectivity between the right amygdala and superior temporal sulcus. Taken together, these results suggest that distinct neural processes facilitate the heterogeneous expression of threat-related attention in social anxiety.

Introduction

Perturbations in threat-related attention play a key role in the etiology and maintenance of social anxiety (Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van IJzendoorn, 2007; Heeren, Mogoase, Philippot, & McNally, 2015). Across separate studies, however, individuals with social anxiety exhibit multiple expressions of threat-related attention. For example, socially anxious individuals may disproportionately orient attention towards or away from threat, or have difficulty disengaging attention from threat (e.g., Amir, Elias, Klumpp, & Przeworski, 2003; Klumpp & Amir, 2009; Mansell, Clark, Ehlers, & Chen, 1999; Pineles & Mineka, 2005). Given that different expressions of threat-related attention are putatively supported by distinct neurocognitive processes (Cisler & Koster, 2010), mechanistic insights into social anxiety are currently limited. Mixed findings may be attributable to standard computation approaches, which assume that threat-related attention is expressed in a consistent manner across trials. In contrast, novel computation methods demonstrate that anxious individuals may exhibit multiple, distinct patterns of threat-related attention across separate trials (Zvielli, Bernstein, & Koster, 2014a; 2014b). For example, an anxious individual may orient attention toward threat on some trials, but orient attention away from threat on other trials. The conjoint expression of both orientation patterns would suggest a more complex pattern of threat-related attention mechanisms in social anxiety (Evans & Britton, 2018). To systematically investigate the expression of threat-related attention and its neural mechanisms in social anxiety, the present study used both standard and novel dot-probe computation approaches in conjunction with fMRI methodology.

Meta-analytic findings demonstrate that social anxiety is characterized by an attentional bias in response to threat (Bar-Haim et al., 2007). Traditionally, attention bias is assessed by presenting threat-neutral stimulus pairs and comparing average reaction time (RT) on trials where response probes replace a threat (congruent trials) or a neutral stimulus (incongruent trials). Faster RT to congruent trials than incongruent trials suggests a bias towards threat, whereas slower RT suggests a bias away from threat. However, theoretical frameworks propose that threat-related attention can be further segregated into distinct cognitive processes of orientation and disengagement of attention (Koster, Crombez, Verschuere, & De Houwer, 2004; Mogg & Bradley, 2016). Specifically, orientation refers to the initial allocation of attention towards a threat, whereas disengagement refers to the subsequent shifting of attention away from a threat (Amir et al., 2003). To disentangle these components of attention in the dot-probe paradigm, RT on neutral-neutral trials serves as a reference to generate separate measures of orientation (congruent trials) and disengagement (incongruent trials; Koster et al., 2004; but for limitations, see Clarke, MacLeod, & Guastella, 2013).

Within these orientation and disengagement components, expressions of threat-related attention may be further dissociated along fuzzy boundaries of automatic and regulatory processes (Barry, Vervliet, & Hermans, 2015). Attentional models propose that vigilant orientation facilitates rapid, automatic detection of threats (Bar-Haim et al., 2007). In contrast, avoidant orientation regulates negative affect elicited by threat by directing attention away from threats (Cisler & Koster, 2010). Fast disengagement from threat may operate to automatically shift attention away from threats and towards safety cues (Cisler & Koster, 2010; Yiend et al., 2015). Conversely, slow disengagement facilitates elaborative processing of threats and may stem from poor regulatory attentional processes (Cisler & Koster, 2010). In summary, these dissociable components of attention may be supported by related, but distinct, processes that are dysregulated in social anxiety.

Given these functional differences, distinct neural mechanisms are proposed to underlie each expression of threat-related attention (Cisler & Koster, 2010). Within the orientation component, the amygdala plays a central role in orienting attention towards threat (i.e., vigilant orientation; Monk et al., 2008; van den Heuvel et al., 2005). Conversely, avoidant orientation away from threat down-regulates amygdala activity by recruiting regulatory regions such as the ventrolateral prefrontal cortex (vlPFC; Adenauer et al., 2010; Browning, Holmes, Murphy, Goodwin, & Harmer, 2010; Fani et al., 2012; Kim & Hamann, 2007; Taylor et al., 2014). Within the disengagement component, fast disengagement is associated with less amygdala activation, which could be attributable to enhanced processing of non-threating stimuli (El Khoury-Malhame et al., 2011). Slow disengagement may reflect a failure to recruit the vlPFC, which impairs shifting attention away from threat (Bishop, 2009; Britton et al., 2012). Given these functional differences among components of attention, past research has aimed to more precisely characterize patterns of threat-related attention in social anxiety.

Across studies, however, social anxiety-related differences in orientation and disengagement components of attention are highly inconsistent. In separate samples, social anxiety has been associated with vigilant orientation, avoidant orientation, slow disengagement, or no differences in threat-related attention (e.g., Amir et al., 2003; Evans, Walukevich, & Britton, 2016; Klumpp & Amir, 2009; Mansell et al., 1999; Pineles & Mineka, 2005). Although some methodological differences exist across studies that may explain these divergent results, inconsistent findings are observed even when studies utilize similar or identical task parameters (Klumpp & Amir, 2009; Price, Tone, & Anderson, 2011; Vassilopoulos, 2005). As a result, it is unlikely that heterogenous findings in social anxiety can be attributed to methodological differences across studies. Instead, inconsistent findings may be attributable to the limitations of standard computation approaches, which characterize the direction in which attention is generally modulated by threat stimuli.

Recent research suggests that anxious individuals may express multiple patterns of threat-related attention, rather than a single, consistent pattern of threat-related attention (Zvielli et al., 2014a; 2014b). On separate trials, for example, an individual may orient attention towards threat or orient attention away from threat in equal magnitude (see Fig. 1). Because the magnitude of vigilant (RT_Neutral > RT_Congruent = positive score) and avoidant trials (RT_Neutral < RT_Congruent = negative score) average to form a zero score, this attention pattern would be miscategorized as a general absence of threat-related orientation. Additionally, individuals may exhibit vigilant and avoidant orientation on separate trials, albeit with unequal magnitudes (vigilant > avoidant = positive score). In both cases, a single average measure may obscure the conjoint presence of both vigilant and avoidant orientation in social anxiety. Similarly, a standard computation approach is also used in fMRI research employing the dot-probe paradigm to quantify neural activation patterns associated with threat-related attention. As a result, standard computation approaches that average neural activation across trials may similarly fail to isolate neural mechanisms underlying each expression of threat-related attention.

To address these limitations, recent research has developed computation approaches that aggregate individual trials based on the type of threat-related attention exhibited on each trial (Evans & Britton, 2018; Zvielli et al., 2014a, 2014b). Using response-based computation, for example, individual reaction times on congruent trials can be separately indexed against that participant's average reaction time on neutral trials (i.e., Trial 1: RT_NeutralMean - RT_{Congruent 1,} Trial 2: RT_NeutralMean - RT_{Congruent 2} … Trial n: RT_NeutralMean - RT_{Congruent n}). Across trials, positive and negative difference scores are subsequently aggregated to generate separate measures of vigilant orientation and avoidant orientation, respectively (see Fig. 1). Consistent with capturing distinct attention processes, response-based computation improves psychometric properties of threat-related attention measures and reveals unique anxiety-related associations (Evans & Britton, 2018).

By isolating specific attention processes using response-based computation, it is possible to address several related research questions concerning social anxiety. First, heterogeneous expressions of threat-related attention in social anxiety are consistent with mixed findings observed across previous studies. Dissociating attentional processes across trials may more accurately characterize threat-related attention in social anxiety. For example, social anxiety may not be characterized by one particular pattern of threat-related attention (e.g., vigilant orientation), but instead be more accurately characterized by multiple expressions of threat-related attention across trials (vigilant orientation and avoidant orientation). Second, dissociating attentional processes across trials may better isolate the neural mechanisms that contribute to conjoint patterns of threat-related attention in social anxiety. Specifically, evoked neural signatures can be directly extracted from trials in which a particular expression of threat-related attention is observed. Finally, the behavioral and neural measures generated by response-based computation may reveal anxiety-related associations that provide additional mechanistic insights into social anxiety. To date, however, no research has utilized response-based computation in conjunction with fMRI methodology in a socially anxious sample.

To address these research questions, we utilized standard and novel dot-probe computation approaches in conjunction with fMRI data from a previously published attention training study (Britton et al., 2015). In this previous report, the authors characterized neural activation changes associated with Attention Bias Modification (ABM) training in a sub-clinical social anxiety sample. Prior to randomization to active ABM or placebo protocols, participants completed the same baseline dot-probe task while in the MRI scanner (Amir et al., 2009). In the published study, ABM-related changes in neural activation were examined in a smaller sub-sample of individuals who completed all treatment phases (n = 30). In the current study, we analyze data from the larger baseline sample who completed the baseline dot-probe task in the MRI scanner prior to treatment randomization (n = 53).

Using response-based computation in this larger baseline sample, we hypothesized that social anxiety would be characterized by the conjoint presence of multiple threat-related attention patterns (i.e., vigilant orientation, avoidant orientation, and slow disengagement), which would not be observed in standard computation measures. Based on previous conceptualizations and empirical research (Bishop, 2009; Browning et al., 2010; Cisler & Koster, 2010; Monk et al., 2008; Taylor et al., 2014), we hypothesized that each pattern of threat-related attention would be associated with distinct neural signatures. First, we hypothesized that vigilant orientation would be characterized by greater amygdala activation, whereas avoidant orientation would be characterized by greater connectivity between the amygdala and vlPFC. Second, we hypothesized that and faster and slower disengagement from threat would be characterized by stronger and weaker vlPFC activation, respectively.