Avoidance and its bi-directional relationship with conditioned fear: Mechanisms, moderators, and clinical implications

Pittig, Andre; Wong, Alex H.K.; Glück, Valentina M.; Boschet, Juliane M.

doi:10.1016/j.brat.2020.103550

Cited by 107 publications

(108 citation statements)

References 332 publications

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“…However, our analyses did not show any robust correlations, which are present in both experiments, between avoidance behaviors and traits assessed by subjective questionnaires. Regarding sex differences, Sheynin et al (2014) and Pittig et al (2020) reported enhanced avoidance in female compared to male participants. In line with that, we found increased avoidance in female participants in the behavioral forced-choice task.…”

Section: Discussionmentioning

confidence: 91%

“…This raises the question whether these differences are driven by trait factors. Pittig et al (2020) listed trait anxiety, intolerance of uncertainty, anxiety sensitivity, neuroticism, and age as possible moderators of avoidance. However, our analyses did not show any robust correlations, which are present in both experiments, between avoidance behaviors and traits assessed by subjective questionnaires.…”

Section: Discussionmentioning

confidence: 99%

“…In laboratory settings, human avoidance behavior is currently assessed by questionnaires or computer-based tasks, during which button presses or a joystick navigation on the screen serve as measurement of behavior. This has provided valuable insights, for example, into the mechanisms of avoidance learning (Pittig et al, 2020), the effect of cost of avoidance (Rattel et al, 2017), or sex differences (Sheynin et al, 2014). Due to their experimental nature, avoidance tasks to date are primarily focused on avoiding the aversive event.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying Human Avoidance Behavior in Immersive Virtual Reality

Binder

Spoormaker

2020

Front. Behav. Neurosci.

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Avoidance behavior is a key symptom of most anxiety disorders and a central readout in animal research. However, the quantification of real-life avoidance behavior in humans is typically restricted to clinical populations, who show actual avoidance of phobic objects. In experimental approaches for healthy participants, many avoidance tasks utilize button responses or a joystick navigation on the screen as indicators of avoidance behavior. To allow the ecologically valid assessment of avoidance behavior in healthy participants, we developed a new automated immersive Virtual Reality paradigm, where participants could freely navigate in virtual 3-dimensional, 360-degrees scenes by real naturalistic body movements. A differential fear conditioning procedure was followed by three newly developed behavioral tasks to assess participants' avoidance behavior of the conditioned stimuli: an approach, a forced-choice, and a search task. They varied in instructions, degrees of freedom, and high or low task-related relevance of the stimuli. We initially examined the tasks in a quasi-experiment (N = 55), with four consecutive runs and various experimental adaptations. Here, although we observed avoidance behavior in all three tasks after additional reinforcement, we only detected fear-conditioned avoidance behavior in the behavioral forced-choice and search tasks. These findings were largely replicated in a confirmatory experiment (N = 72) with randomized group allocation, except that fear-conditioned avoidance behavior was only manifest in the behavioral search task. This supports the notion that the behavioral search task is sensitive to detect avoidance behavior after fear conditioning only, whereas the behavioral approach and forced-choice tasks are still able to detect "strong" avoidance behavior after fear conditioning and additional reinforcement.

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Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantifying Human Avoidance Behavior in Immersive Virtual Reality

Binder

Spoormaker

2020

Front. Behav. Neurosci.

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“…Specifically, we investigated whether trauma-exposed individuals with more severe PTSD symptoms would show a pattern of behaviour best explained by a greater or lower tendency to infer novel environmental causes, when compared to trauma-exposed individuals with less severe or no post-traumatic stress. We were particularly interested in whether differences in inference across aversive conditioning and extinction learning were related to individual difference in avoidance symptoms, as inappropriate avoidance behaviour is thought to be a core mechanism maintaining resistance to extinction in anxiety disorders (Arnaudova et al, 2017;Pittig et al, 2020). Following recent theoretical developments that favour modelling psychological disorders as consisting of complex associations of interacting symptoms and other psychosocial factors (Borsboom, 2017), individual differences in latent cause inference were also related to multiple psychological symptom dimensions using network analysis (Greene et al, 2018;Armour et al, 2017;Fritz et al, 2018;de Haan et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Latent cause inference during extinction learning in trauma-exposed individuals with and without PTSD

Norbury¹,

Brinkman²,

Kowalchyk³

et al. 2020

Preprint

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Problems in learning that sights, sounds, or situations that were once associated with danger have become safe (extinction learning) may explain why some individuals suffer prolonged psychological distress following traumatic experiences. Although simple associative learning models have been unable to provide a convincing account of how and why this learning fails, it has recently been proposed that this may be explained by individual differences in beliefs about the causal structure of the environment. Here, we tested two competing hypotheses as to how differences in causal inference might be related to trauma-related psychopathology, using extinction learning data collected from clinically well-characterized individuals with varying degrees of post-traumatic stress (N=56). Latent cause modelling revealed that individuals with more severe PTSD were more likely to assign observations from conditioning and extinction stages to a single underlying cause. Specifically, multivariate analysis incorporating multiple PTSD and depression symptom dimensions revealed a negative relationship between tendency to infer multiple causes were active in the environment and re-experiencing symptom severity. We interpret these results as providing evidence of a primary deficit in discriminative learning in participants with more severe PTSD re-experiencing symptoms. Specifically, in these individuals, a greater tendency to attribute all stimulus configurations to the same underlying cause resulted in greater uncertainty about stimulus-outcome associations, and impeded learning both that certain stimuli were safe, and that certain stimuli were no longer dangerous. Better understanding of the role of causal inference in trauma-related psychopathology may have relevance for the refinement of cognitive therapies for these disorders.

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“…In a following instrumental learning phase, participants learn that performing a designated response during CS+ presentation prevents the US. This response is referred to as "US-avoidance" given that it prevents the US but does not terminate CS+ presentation (see Pittig, Wong, Glück, & Boschet, 2020). Empirical studies found that participants readily acquired stronger safety behavior to the CS+ compared to a safety cue (CS-; e.g., Dymond et al, 2011;Lovibond, Saunders, Weidemann, & Mitchell, 2008;Morriss, Chapman, Tomlinson, & van Reekum, 2018;Pittig, 2019;Vervliet & Indekeu, 2015).…”

Section: Preprintmentioning

confidence: 99%

A dimensional measure of safety behavior: A non-dichotomous assessment of costly avoidance in human fear conditioning

Ahk¹,

Pittig²

2020

Preprint

Self Cite

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Safety behaviour in anxiety disorders is often maladaptive given it prevents patients to disconfirm unrealistic threat beliefs (protection from extinction). These behaviours range from mild to excessive, however, are commonly examined as binary responses. The current study aimed to validate a dimensional measure of safety behaviour. After acquiring differential conditioned fear to a warning cue (CS+) and a safety cue (CS-), participants acquired dimensional safety behaviour that had a negative linear relationship with the admission of an aversive outcome (0-100% omission). Next, a Reward group received a fixed (Experiment 1) or an individually calibrated monetary incentive (Experiment 2) for non-avoidance while a Control group received no incentive. Overall, the paradigm replicated well-established effects. Intensity of safety behaviour strongly aligned with threat expectancy. The Reward group showed less frequent safety behaviour which initiated extinction learning to CS+. Surprisingly, no group differences in protection from extinction were observed. Post-hoc analyses revealed that overall group differences were biased by some high avoiders in the Reward group who constantly engaged in safety behaviour. Novel findings revealed that despite similar conditioned fear to CS-, the Control group showed stronger safety behaviour to it. This suggests that other processes besides fear are involved in low-cost avoidance

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Avoidance and its bi-directional relationship with conditioned fear: Mechanisms, moderators, and clinical implications

Cited by 107 publications

References 332 publications

Quantifying Human Avoidance Behavior in Immersive Virtual Reality

Quantifying Human Avoidance Behavior in Immersive Virtual Reality

Latent cause inference during extinction learning in trauma-exposed individuals with and without PTSD

A dimensional measure of safety behavior: A non-dichotomous assessment of costly avoidance in human fear conditioning

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