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Avoidance: From threat encounter to action execution
Arnaudova, I.
Publication date
2015
Document Version
Final published version
Link to publication
Citation for published version (APA):
Arnaudova, I. (2015). Avoidance: From threat encounter to action execution. Boxpress.
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Chapter 1
Introduction
On an average day people might face a variety of threats to their survival or well-being: a raccoon with rabies in the forest, a car running a red light, or a yelling commuter on the train. Navigating the scene might seem challenging, but most individuals manage it without too much concern about their safety. They keep their distance from dangerous objects or people, engage in multiple other avoidance strategies and ultimately survive the day unharmed without consid-erably limiting their activities. For individuals suffering from clinically severe anxiety, however, this avoidant mode of responding becomes all-absorbing. It severely impairs their functioning (American Psychiatric Association, 2013) by preventing them from participating in activities that most people would deem non-threatening. An individual with dog phobia, for example, might avoid not only petting dogs, but also entering parks where others might walk their dogs or watching movies such as K-9 (Daniel, 1989) or 101 Dalmatians (Herek, 1996). In-depth understanding of both adaptive and maladaptive avoidance can ultimately lead to the development of more successful prevention and treatment strategies for clinically severe anxiety and pathological avoidance. This doctoral disserta-tion presents a novel theoretical framework for adaptive avoidance of threat and its proliferation in anxiety pathology. The dissertation then reports empirical investigations of key ideas of the framework.
In this introduction, we first briefly review the theoretical model presented in more detail in Chapter 2. Then, we introduce the laboratory paradigm used for testing the ideas of the model in the experiments reported in the subsequent chapters (Chapters 3 to 6). Lastly, we give the outline of the dissertation and the empirical investigations reported in it.
1.1 Threat avoidance response selection and
execution
While the acquisition of avoidance was a hot topic for research by learning ex-perts up to the 1970s (Krypotos, Effting, Kindt, & Beckers, 2015), inspiring more than one influential theory (e.g., two-factor theory, Mowrer, 1939; and
species-Chapter 1
specific defense reactions theory, Bolles, 1970), the selection and execution of avoidance responses in the presence of threat have been studied far less, par-ticularly in humans. Response selection refers to the process through which a particular avoidance response is chosen from the available behavioral alternatives (e.g., withdrawal or endurance), eventually leading to action. In Chapter 2, we present a novel theoretical framework for human threat avoidance response selection and execution (TeARS model).
In the TeARS model, we define avoidance as “any covert or overt action that
functions to physically (spatially or temporally) or psychologically distance the agent from perceived or actual threat,” so that the framework can incorporate the
large variety of avoidance behaviors performed by humans, especially those with anxiety pathology: from running away from a house on fire to planning a doctor’s appointment on the day of prom, so as to avoid being laughed at because of lack of a date for the prom.
Following a long tradition of dual-process models (Strack & Deutsch, 2004), we propose that avoidance actions result from the interaction of fast, automatic, reflex-like avoidance tendencies and a slow and controlled reflective evaluation of behavioral alternatives. Automatic avoidance tendencies refer to the preference of an individual to react to a threat encounter with avoidance rather than with another response (e.g., approach). These tendencies might or might not result in observable behavioral output (avoidance action). Thus, the final behavioral output is assumed to be resulting from the interaction of both a reflexive and a
reflective behavioral system.
Avoidance tendencies are assumed to be present whenever a threat is encoun-tered, even when the individual is not consciously aware of a threat’s presence. Threat stimuli that are unavailable to consciousness have been shown to pro-duce a number of defensive responses (e.g., sweating; ¨Ohman & Soares, 1993) and we maintain, like others ( ¨Ohman, 2013), that avoidance tendencies are sim-ilarly primed. We view avoidance tendencies as an integral part of the defensive motivational network, which is assumed to be activated in response to threat signals and guide all defensive responses (e.g., Lang, 1995). We further propose that individual differences modulate the strength of these automatic avoidance tendencies.
According to the TeARS model, the appraisal of threat imminence serves as a gatekeeper for the optimization of the response selection process. Threat immi-nence refers to the physical (spatial and temporal) and psychological (e.g., direc-tion of the threat movement) distance of the threat from the organism (Fanselow & Lester, 1988). The role of threat imminence in response selection has been extensively studied in non-human animals (rats; Fanselow & Lester, 1988). How-ever, even though the threat imminence account has often been incorporated in theoretical formulations on human fear and defensively motivated behavior (e.g., Craske, 1999, 2003; Lang, Bradley, & Cuthbert, 1997), until recently, it lacked empirical validation. Mobbs et al. (2009, 2007) were the first to show that the same neural mechanisms that operate when processing threat at different immi-nence levels in rats are active in humans. Thus, threat immiimmi-nence has a central role in the TeARS model. We propose that when threat imminence is high, re-sponse selection is optimized by deactivating the slow and cumbersome reflective system, resulting in a reflexive withdrawal or flight. However, when threat
im-minence is lower, an evaluation of various behavioral alternatives takes place. Under such conditions, the final behavioral decision of which action to undertake is assumed to be postponed until multiple factors (e.g., behavioral repertoire and affordances) are considered, provided that no changes in threat imminence occur. Consequently, changes in threat imminence need to be attended to and threat imminence appraisal has to be constantly updated in order to choose the most appropriate action.
Once an avoidance response is performed, situational feedback either termi-nates the process or restarts it. According to TeARS, if a competing activation of the appetitive motivational network is present (e.g., craving for food), the conflict would be resolved in an avoidant way, since the defensive motivational network would take control precedence (e.g., Frijda, 1996) and the output of the appetitive motivational network would be obstructed.
The TeARS model also covers situations of imbalance, where one of these sys-tems (reflexive or reflective) dominates over the other and unduly guides behavior, as in pathological anxiety. It proposes five pathways to how adaptive avoidance can go awry. First, anxious individuals are proposed to have excessively potent avoidance tendencies. Second, conditions of extreme anxiety are suggested to be associated with overestimation of current threat imminence. Third, the reflective system of individuals suffering from anxiety pathology is proposed to be incapable of modulating responding. Fourth, according to the TeARS model, regulatory re-sources might as a whole be depleted in these individuals as a result of over-usage of the reflective system. Last, but not least, avoidance is assumed to become habitual with repetitive performance.
The TeARS model integrates isolated findings from a wide range of disci-plines: human and non-human animal laboratory research, emotion theory, social psychology, human ethology and clinical psychology. Importantly, it presents a comprehensive view on avoidance and its transition from adaptive to maladaptive avoidance in clinically severe anxiety.
Lastly, the model allows making novel testable predictions about human be-havior under conditions of threat and suggests avenues for future research. This doctoral dissertation contains empirical investigations of some of these ideas. All studies presented here use a similar laboratory paradigm for testing the tenets of TeARS: classical conditioning. We continue with describing the classical con-ditioning paradigm used in these experiments and explaining the advantages of using this paradigm.
1.2 Classical conditioning
Classical or Pavlovian conditioning (after the pioneer in the field, Pavlov, 1927), is among the most widely used paradigms in the study of fear/threat learning (Beckers, Krypotos, Boddez, Effting, & Kindt, 2013) and reward learning. In its aversive form, a naturally aversive stimulus such as an electric stimulation (shock) is used as an unconditioned stimulus (US) to provoke a defensive unconditioned response (e.g., fear-potentiated eye blink startle; UR) across individuals (Figure 1.1A). In its appetitive form, a naturally appetitive stimulus, such as chocolate, is used to produce an appetitive UR (e.g., salivation). Next, a neutral stimulus (e.g., a geometric shape; conditioned stimulus, CS+) is paired with this US until
Chapter 1
an association between the two stimuli is learned (Figure 1.1B). Later, upon the presentation of the unaccompanied CS+, a conditioned response (e.g., sweating or salivation; CR) is observed (Figure 1.1C). Some theories propose that the elicitation of CR is due to the CS evoking an expectation of the US (Lovibond, 2006; Lovibond & Shanks, 2002; Reiss, 1991).
In the lab, a differential cue-conditioning paradigm is mostly used, in which responding to the CS+ is compared to responding to a neutral stimulus never paired with the US (CS-). Thus, in aversive differential classical conditioning, the CS- acts as a safety stimulus, signaling the absence of the aversive US. Our choice to use a differential cue-conditioning paradigm in the empirical studies reported in this dissertation is motivated by several factors.
Figure 1.1: An aversive classical conditioning procedure with a neutral geometric
shape as CS and an electric stimulation as US
DANGER! DANGER!
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CR
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First, this paradigm allows for the simultaneous measurement of multiple con-ditioned responses to the CS+. Regardless of whether an aversive or an appetitive conditioning procedure is used, CRs can be divided into three distinct categories: verbal, physiological and behavioral (Figure 1.2, Lang, 1995; Lang & Davis, 2006). During aversive conditioning (Figure 1.2A), individuals can verbally report their current distress or threat expectancy (see Figure 1.2B for responses in appetitive conditioning). Physiological activation can be examined through the measure-ment of eye-blink startle potentiation or skin conductance responses (SCR) to
aversively conditioned CSs. Most importantly, both, automatic action tendencies (e.g., Krypotos, Effting, Arnaudova, Kindt, & Beckers, 2014) and overt behav-ior (e.g., Lommen, Engelhard, & van den Hout, 2010) can be measured. Thus, the aversive classical conditioning paradigm allows to test the ideas proposed by TeARS about avoidance tendencies and actions and to examine whether these ideas are also valid for other well-established defensive reactions.
Figure 1.2: Categories of conditioned responses following aversive (A) and
ap-petitive (B) conditioning
Aversive'Responses'
Appe,,ve'Responses'
Approach tendencies, Overt approach Avoidance tendencies Overt avoidance Craving, Reward Expectancy Distress, Threat Expectancy Startle, Skin conductance SalivationBehavioral
Behavioral
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Second, the classical conditioning paradigm allows for testing conditioned re-sponses in a highly controlled environment. Variables such as the perceptual and temporal characteristics of both the CSs and the US can be controlled. Also, by using initially neutral stimuli as CSs and holding constant the number of CS pre-sentations being reinforced with a US, we can maintain the same level of threat imminence across individuals. In a differential cue-conditioning paradigm, where the CS+ is always reinforced and the CS- is never reinforced, the difference be-tween the two CSs is apparent and very similar responses are observed across individuals (Beckers et al., 2013; Lissek, Pine, & Grillon, 2006). This control of the threat imminence level across individuals is important for the examination of many ideas proposed in TeARS. For example, we can test the effects of threat imminence changes (e.g., approaching versus withdrawing threats), without con-sidering confounding variables such as discrepant personal experiences with the CSs among individuals or perceptual differences between the CSs.
In the TeARS model, we also propose that individual differences might play an important role in modulating avoidant responding. In order to examine such modulation by trait characteristics, weaker or more ambiguous situations are re-quired than the standard aversive differential cue-conditioning paradigm (Beckers et al., 2013; Lissek et al., 2006). Fortunately, other variants of the classical con-ditioning paradigm offer the opportunity for testing responding to such more or less ambiguous threat situations. For example, in blocking procedures, a novel
Chapter 1
stimulus (CSB) is paired with an already established CS (CSA, previously
fol-lowed by an aversive US). The compound CSACSB stimulus is then followed by
the same outcome (US) that followed CSA when presented alone. As a result
CSB becomes ambiguous, because the to-be-expected outcome for CSB remains
unclear. Individual differences in threat expectancies have been readily observed in such paradigms (Boddez et al., 2012). Another ambiguous paradigm is the generalization paradigm (Lissek et al., 2008; Lommen et al., 2010), where follow-ing the aversive differential cue-conditionfollow-ing of two stimuli at the opposite ends of a continuum (e.g., a small circle as CS- and a large circle as CS+, Lissek et al., 2008), a number of intermediate stimuli (e.g., circles of different sizes) are presented. Those generalization stimuli (GSs) also elicit a degree of defensive responding, with the strength of responding depending on the perceptual simi-larity between a given intermediate stimulus and the CS+. Responding reduces incrementally as perceptual similarity to the CS+ reduces (Lissek et al., 2008). Individual differences in conditioned fear responding have been observed in such perceptual generalization paradigms (e.g., Lissek et al., 2010) and it has been shown that avoidance behaviors generalize to the ambiguous intermediate stimuli as well, with some modulation based on individual characteristics (van Meurs, Wiggert, Wicker, & Lissek, 2014). Thus, the third reason for using variants of the classical conditioning paradigm for testing the ideas of the TeARS model is that we can examine whether personality dispositions affect avoidance responding as proposed by TeARS.
Finally, aversive classical conditioning allows for testing responses to threats that are subliminally rather than consciously processed. Subliminal or pre-attent-ive processing occurs when the brief presentation (between 14 ms and 33 ms) of a CS is immediately followed by the presentation of a novel neutral stimulus ( ¨Ohman & Soares, 1993) and the individual remains unaware of the CS presentation. As a result of pre-attentive processing of the CS, a myriad of defensive responses can be elicited in the individual (e.g. SCR, Esteves, Dimberg, & ¨Ohman, 1994) and it has been proposed that such subliminal processing can also result in avoidance tendencies ( ¨Ohman, 2013). The TeARS model similarly maintains that conscious awareness of threat might not be necessary for the activation of reflex-like avoid-ance tendencies.
In conclusion, the classical conditioning paradigm is a useful tool for the exam-ination of both defensive and appetitive responding and its aversive variants are particularly suited for critically testing hypotheses that follow from the TeARS model.
1.3 Outline of the doctoral dissertation
This doctoral dissertation firstly presents the novel iterative model for threat avoidance response selection and execution, referred to as the TeARS model, in
Chapter 2. Subsequent chapters are devoted to testing some of the model’s key
ideas.
In Chapter 3, we examine whether pre-attentive processing of conditioned threat results in the activation of conditioned avoidance tendencies and whether supraliminal changes in threat imminence can, in turn, tune attentional process-ing. We evaluate the results in light of the adaptive advantage of attentionally
and pre-attentively prioritizing threat processing.
In Chapter 4, we evaluate individual differences in fear generalization across response systems to clarify which fear responses, if any, are affected by a known vulnerability factor for anxiety, neuroticism (e.g., D. Watson, Gamez, & Simms, 2005).
In Chapter 5, we examine other individual factors pertinent to the experience of anxiety and how they relate to discriminatory fear learning and avoidance in ambiguous situations.
In Chapter 6, we investigate a different kind of threat than one that is classi-cally conditioned. Some theories propose that negative mood can serve as an in-ternal negative cue and directly influence behavior (e.g., Baker, Piper, McCarthy, Majeskie, & Fiore, 2004). If negative mood can serve as an internal threat, it should reduce appetitive behavior according to the TeARS model. In two ex-periments, we examine the effects of negative mood on appetitive learning and examine whether negative mood impairs the formation of positive associations and the acquisition of possibly adaptive behaviors for coping with negative mood. In Chapter 7, we re-examine the TeARS model in light of the findings from the empirical studies, discuss the implications of the research and theory presented in this doctoral dissertation and give suggestions for future research. We also examine treatment protocols for clinically severe anxiety from the perspective of the TeARS model and suggest potential improvements to clinical interventions.
