Research PaperAttention bias modification reduces neural correlates of response monitoring
Introduction
Errors are motivationally-salient events that have the potential to place an individual in danger (Weinberg, Riesel, & Hajcak, 2012). The detection of errors is evolutionarily important as errors may signal potential harm (e.g., slipping and cutting oneself) or missed opportunities (e.g., food acquisition). Error commission elicits a number of physiological changes consistent with defense system activation, including skin conductance response (Hajcak, McDonald, & Simons, 2003), heart rate deceleration (Hajcak et al., 2003), pupil dilation (Critchley, Tang, Glaser, Butterworth, & Dolan, 2005), potentiated startle reflex (Hajcak & Foti, 2008), and amygdala activation (Pourtois et al., 2010). As such, error detection is considered an important element of a general performance monitoring system that further evaluates the consequences of behavior and makes adjustments to optimize outcomes (Holroyd & Coles, 2002).
A neural index of error detection is the error-related negativity (ERN), a negative deflection in the event-related potential (ERP) that peaks at frontocentral electrodes approximately 50 ms following error commission (Hajcak, 2012). The ERN magnitude is sensitive to the motivational salience of errors, such that it is enhanced when errors are punished (Riesel, Weinberg, Endrass, Kathmann, & Hajcak, 2012), performance is evaluated (Barker, Troller-Renfree, Pine, & Fox, 2015; Hajcak, Moser, Yeung, & Simons, 2005; Kim, Iwaki, Uno, & Fujita, 2005), or accuracy is emphasized over speed (Falkenstein, Hoormann, Christ, & Hohnsbein, 2000; Gehring, Goss, & Coles, 1993). The ERN has excellent psychometric properties, including high test-retest reliability across two weeks (Olvet & Hajcak, 2009a) and two years (Weinberg & Hajcak, 2011), and high internal consistency in as few as six trials (Olvet & Hajcak, 2009b). The ERN is also moderately heritable (Anokhin, Golosheykin, & Heath, 2008) and related to particular genotypes (Manoach & Agam, 2013), suggesting genetic contributions.
Although there are many theories surrounding the mechanisms that underlie the generation of the ERN (see Weinberg, Dieterich, & Riesel, 2015 for review), it is commonly believed to reflect the activity of a generic error monitoring system which tracks ongoing performance (Falkenstein et al., 2000; Gehring et al., 1993; Holroyd & Coles, 2002). In addition to its role in a generic performance monitoring system, there is growing evidence that variability in the magnitude of the ERN indexes individual differences in sensitivity to errors. Consistent with this notion, an enhanced ERN has been associated with increased anxiety symptoms (Hajcak, 2012; Moser, Moran, Schroder, Donnellan, & Yeung, 2013; Proudfit, Inzlicht, & Mennin, 2013), and risk for anxiety disorders. Specifically, the ERN is larger in healthy individuals with a family history of obsessive-compulsive disorder (Carrasco et al., 2013, Riesel et al., 2011), and an enhanced ERN prospectively predicts the new onset of anxiety disorders in children (Meyer, Hajcak, Torpey-Newman, Kujawa, & Klein, 2015). Thus, the ERN has been suggested to be a potential marker of risk for anxiety disorders (Hajcak, 2012; Meyer, 2016; Olvet & Hajcak, 2008).
In a recent investigation, Nelson, Jackson, Amir, and Hajcak (2015) examined whether a single session of attention bias modification could reduce the ERN. Attention bias modification is a computerized intervention that trains attention away from negative stimuli and towards positive stimuli, and targets a core mechanism of dysfunction in anxiety disorders (i.e., attentional bias toward threat) (Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van IJzendoorn, 2007). Attention bias modification has been shown to successfully decrease threat biases and anxiety symptoms (Kuckertz & Amir, 2015; Macleod & Clarke, 2015). Given that attention bias modification is designed to modify attentional biases away from threat and reduce vulnerability to anxiety, we hypothesized that attention bias modification would modulate the ERN, a posited neural index of threat sensitivity (Weinberg et al., 2016). In Nelson et al., participants were randomly assigned to complete attention bias modification either before or after the ERN was measured (i.e., AB/BA design). Results revealed that the ERN was smaller in participants who completed attention bias modification before, relative to those who completed attention bias modification after, the ERN was measured. These results support the hypothesis that individuals who completed attention bias modification first showed a smaller ERN relative to their attention bias modification-naive counterparts. Furthermore, changes in attentional bias occurred on a continuum, with some participants showing more or less change in their biases away from negative and toward positive stimuli. Upon examining these bias scores, we found that greater attentional disengagement from negative stimuli during attention bias modification was associated with a smaller ERN across both groups, suggesting that the ERN may be both a mechanism and predictor of attention bias modification-related changes in attentional bias to threat.
Nelson et al. (2015) provides a critical first indication that the ERN—a posited neural marker of threat sensitivity and risk for anxiety—can be altered by a computerized attention bias modification task. However, Nelson et al. contained several methodological limitations that proscribe causal conclusions about the effect of attention bias modification on the ERN. Specifically, it did not include a control group that completed an analogous cognitive task. Thus, it is unclear if attention bias modification training directly altered the ERN, or if there were other factors (e.g., task fatigue) that indirectly impacted the ERN. Additionally, Nelson et al. did not include pre- and post-training assessments of the ERN, thereby prohibiting the examination of within-subject changes in the ERN.
The present study examined the impact of attention bias modification on the ERN using a pre-test/post-test design, across both attention bias modification and a control task. Specifically, 64 participants completed a flanker task designed to elicit the ERN and correct response negativity (CRN)—a smaller negative deflection in the ERP which also peaks at frontocentral electrodes approximately 50 ms following correct responses—and were then randomly assigned to complete a single session of attention bias modification or a control task. The control task included similar instructions, stimuli, and an identical number of trials, but did not train attention away or toward stimuli. After completing the attention bias modification or control task, participants again completed the flanker task to elicit the ERN and CRN. The present study focused on a sample of individuals who were unselected for initial attention bias or anxiety symptoms to minimize the contribution of psychopathology that may be more prevalent in clinical populations on initial attention bias or the ERN. We hypothesized that participants who completed attention bias modification, but not the control task, would demonstrate a within-subject reduction in the ERN. Furthermore, in the participants who completed attention bias modification, we hypothesized that a greater change in negative attention bias would be associated with a smaller ERN.
Section snippets
Participants
In an attempt to replicate and extend Nelson et al. (2015), the present study recruited a sample that was of similar size and demographic composition. To this end, the sample included 64 undergraduates from Stony Brook University who participated for course credit. Participants were randomly assigned to attention bias modification (n = 34) or the control condition (n = 30). Informed consent was obtained prior to participation and participants were allowed to terminate participation at any time
Demographics
Table 1 presents descriptive and inferential statistics for demographics. Attention bias modification and control participants were matched on all demographics and current depression and anxiety symptoms.
Behavior
Table 1 also presents flanker behavioral performance. For response accuracy, results indicated a main effect of time, F(1, 58) = 8.00, p < 0.01, ηp2 = 0.12, such that participants were less accurate during the post- relative to pre-training assessment. However, there was no main effect or interaction
Discussion
The present study examined the impact of a single session of attention bias modification, relative to a control task, on the neural correlates of response monitoring. Attention bias modification and control participants did not differ in behavioral performance; however, there were group differences in the neural correlates of response monitoring, including error-related brain activity. Specifically, attention bias modification reduced the ERN, CRN, and ΔERN (i.e., ERN – CRN) from the pre- to
Acknowledgments
Dr. Amir was formerly a part owner of Cognitive Retraining Technologies, LLC (“CRT”), a company that marketed anxiety relief products. Dr. Amir’s ownership interest in CRT was extinguished on January 29, 2016, when CRT was acquired by another entity. Dr. Amir has an interest in royalty income generated by the marketing of anxiety relief products by this entity.
The specific implementation described in this article is not available for purchase through the company. This project was supported by
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2022, Biological Psychiatry: Cognitive Neuroscience and NeuroimagingCitation Excerpt :This distinction has important clinical consequences because intervention or prevention strategies will likely differ whether detection or control is targeted. For example, in contrast to control processes, detection processes (e.g., error monitoring) are not impacted by explicit, cognitive, and behavioral strategies, such as cognitive behavioral therapy (45–47), but are modified by implicit interventions, such as attention-bias modification training (48–50) and a computerized intervention that was designed to directly reduce sensitivity to errors (51). Future studies should continue to develop and evaluate personalized intervention strategies for modifying specific components of cognitive control that may place individuals at higher risk for anxiety during adverse situations.
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2021, Developmental Cognitive NeuroscienceCitation Excerpt :More negative ERNs are indicative of greater vigilance to non-social threat (Hajcak et al., 2005; Moser et al., 2013), index magnitude of unexpected threat (Frank et al., 2005), and moderate the link between early childhood avoidance and subsequent onset of social anxiety (Buzzell et al., 2017b; Filippi et al., 2019). Additionally, the ERN is potentiated by higher levels of threat (Chiu and Deldin, 2007; Ganushchak and Schiller, 2008; Meyer and Gawlowska, 2017; Riesel et al., 2012), and is attenuated when attention to non-social threat is reduced via intervention (Nelson et al., 2015, 2017). Between ages 12 and 17, the ERN becomes dramatically more negative (Davies et al., 2004), suggesting that greater threat-vigilance emerges in adolescence.