The neural chronometry of threat-related attentional bias: Event-related potential (ERP) evidence for early and late stages of selective attentional processing

Abstract

Rapid and accurate detection of threat is adaptive. Yet, threat-related attentional biases, including hypervigilance, avoidance, and attentional disengagement delays, may contribute to the etiology and maintenance of anxiety disorders. Behavioral measures of attentional bias generally indicate that threat demands more attentional resources; however, indices exploring differential allocation of attention using reaction time fail to clarify the time course by which attention is deployed under threatening circumstances in healthy and anxious populations. In this review, we conduct an interpretive synthesis of 28 attentional bias studies focusing on event-related potentials (ERPs) as a primary outcome to inform an ERP model of the neural chronometry of attentional bias in healthy and anxious populations. The model posits that both healthy and anxious populations display modulations of early ERP components, including the P1, N170, P2, and N2pc, in response to threatening and emotional stimuli, suggesting that both typical and abnormal patterns of attentional bias are characterized by enhanced allocation of attention to threat and emotion at earlier stages of processing. Compared to anxious populations, healthy populations more clearly demonstrate modulations of later components, such as the P3, indexing conscious and evaluative processing of threat and emotion and disengagement difficulties at later stages of processing. Findings from the interpretive synthesis, existing bias models, and extant neural literature on attentional systems are then integrated to inform a conceptual model of the processes and substrates underlying threat appraisal and resource allocation in healthy and anxious populations. To conclude, we discuss therapeutic interventions for attentional bias and future directions.

Keywords: Anxiety; Attention; Attention bias modification treatment; Event-related potentials; Mindfulness-based cognitive therapy.

Conflict of interest statement

Conflict of Interest: The authors have no competing interests to declare.

Copyright © 2019 Elsevier B.V. All rights reserved.

Figures

Figure 1.. An ERP model of the neural chronometry of attentional bias.

ERPs are schematically represented across stimuli and paradigms. In this image, negative voltages are plotted upward. Subcomponents are not explicitly shown, but are included with their primary, overarching components (e.g. “N1” in the figure includes N170 modulations and “N2” in the figure includes N2pc modulations). Amplitude and latency modulations have been estimated to enhance visualization of differences between populations and conditions.

Figure 2.. A Conceptual Model for Threat Appraisal and Resource Allocation.

Early and late stages of threat appraisal and resource allocation are represented. The model builds upon existing attempts to synthesize the extant literature depicting stages of information processing in attentional bias (Bar-Haim et al., 2007; Cisler & Koster, 2010; Williams et al., 1988), the neural substrates supporting ERP markers, and state and trait modulation of attention (see Mogg & Bradley, 2016; 2018; Okon-Singer, 2018). A sensory object is appraised as having high or low threat value through an Affective Decision Mechanism (ADM). This mechanism is likely early and automatic in nature, detecting salience and threat potential of a sensory stimulus with little interference by conscious awareness. Low threat facilitates pursuit of current goals; high threat induces fear and its associated affective expression. The salience network, dorsal frontoparietal attention network, along with pre-conditioned limbic and brainstem (BS) circuits are implicated in mediating the monitoring and initial threat appraisal associated with the ADM. If the stimulus is appraised as high threat, fear expression is elicited, state arousal increases and the stimulus is sent to upstream neural pathways for increased processing. Early ERP markers ( 250 ms) and fMRI data support the idea that high threatening stimuli are either engaged by attention with higher levels of inhibitory control for any distractions, or are elaborated further through cognitive processes supported by the default mode network (DMN), with low levels of inhibitory control. The RAM and associated engagement and disengagement processes are thought to be supported by dorsal and ventral aspects of the frontoparietal networks. Trait anxiety and mindfulness are proposed to modulate the RAM, such that high-trait anxiety (HTA) increases engagement and elaboration, thereby facilitating disengagement delays and increasing state modulatory input (e.g., arousal). Low-trait anxiety (LTA) is proposed to facilitate disengagement and negatively feedback on state modulatory input. Disengagement from task-relevant objects may also be displaced by ruminative thoughts that interfere with task demands. Mindful approach behavior and an inhibitory control mechanism are proposed to facilitate healthy disengagement. Salience network includes the dorsal anterior cingulate cortex (dACC), anterior insular cortex (AIC), amygdala (AMY), and parts of the brainstem (BS). The dorsal fronto-parietal attentional network includes the frontal eye fields (FEF) and superior parietal lobe. The ventral frontoparietal attentional network includes the frontopolar cortex (FPC), ventrolateral PFC (vlPFC), temporoparietal junction (TPJ), and anterior inferior parietal lobe (IPL), and are implicated in mediating the RAM. The DMN includes the ventromedial PFC (vmPFC) and posterior cingulate cortex (PCC), and is implicated in elaborative appraisal in later stages, facilitating avoidance through distraction, and decreasing available resources for ongoing task demands.