Brief Report

The role of Anxiety Sensitivity in fear conditioning: a moderation effect

Bianca Gerardoa,b, Raquel Guiomara,b, Mariana Moura-Ramosb, Ana Ganho-Ávilaa,b*

aProaction Laboratory, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal; bCenter for Research in Neuropsychology and Cognitive Behavioral Intervention, Coimbra, Portugal

* Corresponding Author: Ana Ganho-Ávila, Center for Research in Neuropsychology and Cognitive and Behavioral Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Rua do Colégio Novo, 3001-115 Coimbra, Portugal. Email: [email protected] Abstract

Anxiety sensitivity (AS; the degree of fear of experiencing or imagining experiencing anxiety symptoms and its possible consequences) is associated with expression of conditioned fear responses. However, findings regarding the relationship between AS and fear acquisition indexed by skin conductance responses are rather conflicting. Here we aim to clarify this interaction. We classified 144 women that underwent fear conditioning procedures as either high-AS or low-AS. We found that high-AS participants show one of two patterns maintained over time: poor stimuli discrimination or good stimuli discrimination. This suggests that different patterns of fear acquisition potentially support the distinction between anxiety disorders.

Keywords: anxiety sensitivity, fear conditioning, skin conductance responses, moderation analysis. Introduction Fear is a highly adaptive core emotion triggered by the perception of danger cues. Individuals learn how to detect danger and express fear by associating threats with internal or external cues (Lang et al., 2000). Whereas an adjusted associative learning of the fear response warrants individuals’ survival, a disrupted associative learning may lead to anxiety – a future-oriented and over amplified expression of fear in the absence of danger (Barlow, 2002; Shin and Liberzon, 2010). The degree of fear of experiencing or imagining experiencing anxiety symptoms and its possible consequences is called Anxiety Sensitivity (AS; e.g. Taylor et al., 1992). According to the expectancy theory, high levels of AS are a vulnerability factor to the development of pathological anxiety (Reiss, 1991). Here we aim to explore the interaction between AS and the associative learning of fear, clarifying the contribution of AS to the development of anxiety disorders. According to the classical conditioning model, the acquisition of fear responses is an associative learning by means of repeatedly pairing a neutral stimulus (CS; a stimulus that does not induce fear response), with an unconditioned stimulus (US; a stimulus that innately induces a fear response). By associative learning, the CS acquires the US emotional and motivational value and becomes a conditioned stimulus (CS+US = CS+). By itself, the CS+ is (from then on) then able to elicit a conditioned response (CR) that will be equivalent to the fear response elicited by the US alone. Several studies have suggested that clinical anxiety is associated with abnormalities in fear learning in that anxious patients are more ‘conditionable’ showing faster and enhanced fear conditioned responses than non-anxious individuals (e. g. Otto et al., 2007; Orr et al., 2000). Similarly, the literature has suggested the association between AS and the expression of conditioned fear responses. Conflicting findings show that during fear acquisition, AS is either negatively correlated with the fear response measured by skin conductance responses (SCRs; phasic or event-related; Kelly and Forsyth, 2007) or AS has no correlation at all with the SCRs differentials (calculated by subtracting the CS+ minus the CS- SCRs; Harrison et al., 2015). Similarly, Kelly and Forsyth (2009), found that there is no association between AS and fear responses measured using skin conductance levels (SCL - the tonic electrodermal activity). Finally, during orientation responses (adjustment responses to the first presentation of the CS) AS seems to be positively correlated with fear SCRs (Otto et al., 2007). The abovementioned studies show that the relationship between AS and fear conditioning is methodologically dependent in that inconsistent findings may be due to both the heterogeneity of the methods used to index the fear response, and the experimental procedure/fear response phase that is under observation. It is thus our understanding that this lack of consensus in the literature has been hindering AS contribution to the genesis and maintenance of anxiety disorders. Here, we aim to uncover in what degree AS effectively contributes to the acquisition of fear responses. Our hypothesis is that high levels of AS (indexed by ASI-3) change the regular pattern of fear acquisition (indexed by the SCRs differentials), moderating the relationship between the pattern of SCRs in the early and the late phases of the fear-acquisition procedure.

Methods Participants This study is part of a larger ongoing research project on fear conditioning and extinction including three experimental sessions. We selected data from the first session – fear acquisition procedure – for 144 women (mean age = 21, SD = 5.95) that gave their informed consent after a debriefing session. The study is compliant with the Declaration of Helsinki and was approved by the local ethical committee. Exclusion criteria for participation included: (1) current psychiatric diagnosis; (2) use of psychoactive medication; (3) pregnancy; (4) caffeine and/or alcohol intake 24 hours before sessions; (5) physical exercise or having had a meal two hours before sessions (Boucsein, 2012); and (6) auditory or visual (non-corrected) deficit. Additionally, participants who did not show fear acquisition measured by contingency ratings were excluded from the sample. Final sample included 121 healthy women.

Procedure Stimulus Stimulus and task are described in Asthana et al. (2013), all is similar, except for the non-invasive neuro-stimulation session (was not performed). We used a visual analogic pain scale (ranging from 1 to 9; Huskisson, 1974) to individually adjust the US intensity to a level where it would be perceived as uncomfortable but not painful. The average US intensity for low-AS participants was 93.60%, and for high-AS participants was 94.28%, respectively.

Experimental procedure All participants gave their informed consent. We then collected the sociodemographic and clinical data (BSI; Canavarro, 1999; ASI-3-PT; Ganho-Ávila et al., in press; Wheaton et al., 2012; STAI; Silva, 2003). The experimental session was divided in 1) instructions and US calibration, 2) instructions, rating scales, habituation, rating scales and fear acquisition phase, 3) closing questions [for details, see Asthana et al. (2013)]. We collected SCRs during sessions to measure inter-individual psychophysiological differences in fear expression.

Data acquisition and analysis Stimuli presentation apparatus and SCRs data collection is described elsewhere (Ganho-Ávila et al., 2019). AS scores correspond to the global ASI-3-PT index estimated by the sum of individual items.

Analytic strategy Habituation phenomenon is the reduction of the fear response to a stimulus that is repeatedly presented (Ramaswami, 2014; Lonsdorf et al., 2017). In our data, we systematically observed habituation to the CS+ in the last phase of the acquisition session (the last 5 trials). Accordingly, for the purpose of our study, we avoided confounders due to habituation by dividing the SCRs into early, middle and late phases (with 5 trials each) and discarding the latter phase (middle SCRs: M = .055, SEM = .006; late SCRs: M

= .040, SEM = .005; t (134) = 3.403, p = .001, 95% CI [.006, .023]). We divided participants into two groups (high-AS group and low-AS group), using the clinical cut-off value for the ASI-3-PT. We used descriptive statistics to characterize the sample and independent samples t-tests to estimate groups differences (high-AS vs. low-AS). Because AS is an important risk factor for the development of anxiety disorders, by dividing the sample into high- and low-AS, we can perceive what is the impact of distinctive degrees of AS in in fear acquisition. Thus, we used AS indexed by ASI-3-PT global score as the moderator variable, the early phase of the fear acquisition as the IV and the middle phase as the DV.

Results

Descriptive statistics and differences between high- and low-AS Independent samples t-tests showed that the percentage of US intensity did not differ between groups (high-AS: M = 94.28, SEM = .54; low-AS: M = 93.60, SEM =

1.45; t (85) = .465, p = .643, 95% CI [-2.215, 3.568]). Groups differed in age (high-AS: M

= 19.53, SEM = .39; low-AS: M = 22.78, SEM = 1.27; t (47.636) = -2.444, p = .018, 95% CI [-5.924, -.576]), but not in years of education (high-AS: M = 12.81, SEM = .21; low-AS:

M = 13.16, SEM = .30; t (83) = -.974, p = .333, 95% CI [-1.063, .364]). As expected, the scores obtained in the ASI-3-PT were significantly different for each group (t (135) = 17.293, p < .001, 95% CI [17.201, 21.643]), with the high-AS participants scoring higher (M = 34.57; SEM = .93) than the low-AS group (M = 15.15; SEM = .61). Similarly, the high-AS group also scored higher in both STAI subscales (STAI 1: M = 45.79, SEM = 2.05; STAI 2: M = 47.33, SEM = 1.70), comparatively to the low-AS group (STAI 1: M = 35.10, SEM = 1.66; t (85.547) = 4.054, p < .001, 95% CI

[5.450, 15.938]; STAI 2: M = 36.29, SEM = 1.49; t (88) = 4.783, p < .001,95% CI [6.450, 15.618]). In contrast, high-AS participants showed lower global severity indexes in the

BSI (M = .027, SEM = .001) than the low-AS subjects (M = .033, SEM = .001; t (75.721) = 3.228, p = .002, 95% CI [.002, .010]).

AS moderation effect in fear acquisition We examined the association between AS total score and the early and middle SCRs. Overall, the moderation model was statistically significant, with a significant interaction between AS and early fear acquisition in predicting middle fear acquisition (F

(4,75) = 2.494, p = .050). The moderation effect of AS accounted for 11.74% of the variance in the acquisition of conditioned fear responses. To probe the interaction between AS and early SCRs (b = .5978, t (75) = 2.787, p = .007, 95% CI [.170, 1.025]; Figure 1) we tested the conditional effects of AS at its two levels (high and low). Simple slopes analysis revealed that whereas for high-AS participants early SCRs significantly predicted middle

SCRs (b = .4422, t (75) = 2.794, p = .007, 95% CI [.127, .757]), for low-AS, there was no statistically significant relationship between early and middle SCRs (b = -.156, t (75) = - 1.076, p = .285, 95% CI [-.444, .132]). Simple slopes analysis revealed that, by its selves, neither AS total score (b = .005, t (75) = .325, p = .7460, 95% CI [-.024, .031]), early SCRs

(b = -.156, t (75) = -1.076, p = .285, 95% CI [-.444, .132]) or age (b = -.0002, t (75) = -.161, p = .873, 95% CI [-.002, .002]) significantly predicted middle SCRs.

Figure 1. Conditional effect of early SCRs on middle SCRs at low and high levels of Anxiety Sensitivity.

Discussion The inconsistent results concerning the relationship between AS and the associative learning of fear is hampering our understanding about the contribution of AS to the genesis and maintenance of anxiety disorders. Our study aimed for a clarification by analysing the relationship between AS and patterns of fear acquisition. Our results show that AS significantly moderates the relationship between conditioned fear responses in the early and middle phases of the fear-acquisition procedure. Indeed, although for women with low levels of AS the relationship between the SCRs in initial and later stages of fear acquisition is not significant, for women with high AS, initial fear responses significantly predict later fear responses. Herewith, high- AS women present either poor stimuli discrimination (similar SCRs to both threatening cues and neutral cues) or good stimuli discrimination (clear distinctive SCRs), preserved throughout the procedure. Accordingly, high-AS women can be grouped into two categories: weak discrimination patterns, thus a decreased ability to adjust the fear response across fear conditioning procedures; and strong discrimination patterns thus, a highly efficient associative learning over time. Whereas women in the first group may be more vulnerable to uncertainty and fear generalization, women in the second group may be more vulnerable to inflexibility and rigid learning. Indeed, although independent, AS and intolerance of uncertainty (IU) share a strong association (Carleton et al., 2007). IU is the tendency to perceive the possibility of occurrence of a negative event as threatening (regardless of its probability; Dugas et al., 2001), and is a powerful stressor that has been widely incorporated in theories of anxiety. Individuals showing high IU tend to present heightened anxiety levels towards undetermined outcomes (Dugas et al., 2001), due to perceiving ambiguous information as threatening (Heydayati et al., 2003). Both AS and IU are based on this undefined threat when facing unknown consequences, and both are related to anxiety diagnosis such as Generalized Anxiety Disorder (GAD; Holaway et al., 2006; Keller, 2002; Starcevic and Berle, 2006) and Panic Disorder (PD; Apfeldorf et al., 1994; Dugas et al., 2001). Indeed, the common feature between AS and IU is uncertainty as high levels of AS are based in the uncertainty regarding the consequences of experiencing anxiety symptoms, and high IU leads to exacerbated anxiety given the inability to tolerate that uncertainty regarding these symptoms (Carleton et al., 2007). As for rigidity and inflexibility, perseverative cognition (PC) is at play - the cognitive process of repeated activation of stress content regarding either past stressful or future feared events. PC is manifested by ruminative thinking or worryness (Brosschot et al., 2006), and is closely related with mood and anxiety (Hughes et al., 2008). Because rumination (past) and worry (future) imply a state of readiness to act and therefore physiological responses, PC unleashes a prolonged autonomic activity (increased cortisol levels, heart rate, systolic and diastolic blood pressure; Brosschot et al., 2005, 2006; Ottaviani et al., 2016). Furthermore, PC is associated with increased levels of cognitive rigidity (effortful inhibition, intrusiveness and slower reaction times) and autonomic inflexibility (lower heart rate variability; Ottaviani et al., 2013). PC has a negative impact on psychological and physiological well-being and is typical in individuals that narrowly recognize safety signals (Brosschot et al., 2010; Verkuil et al., 2010). Thus, although a highly efficient associative learning process is adaptative, it seems plausible that high levels of AS support the perseveration of heightened fear responses not only in general, but also during fear extinction procedures. From the translational perspective, a preserved pattern of stimuli discrimination with rigid identification of aversive stimuli is associated with anxiety disorders such as specific phobias (Schweckendiek et al., 2011), whilst patterns of stimuli generalization are typical of PD (Lissek et al., 2009) and GAD (Lissek et al., 2014). Since AS is a risk factor for the development of clinical anxiety (Reiss, 1991), this information may be useful for the understanding of women mental health and the risk factors for developing different anxiety disorders. In the herein study, the decision to observe only women was motivated by the fact that women show greater phasic reactivity to threatening conditions than men (Stockhorst and Antov, 2016), and so, future replication studies in male samples are deemed necessary. As we found a habituation effect in the late phases of fear acquisition, we dismissed the later third of SCRs to both CSs. Future studies should consider the optimal length for fear acquisition procedures. Our findings show two patterns of fear conditioning for women scoring above the clinical cut-off in ASI-3-PT suggesting a distinguishing feature that may characterize different clinical groups. This information is particularly useful for research when relying in SCRs to measure fear in clinical populations. Thus, future studies should not only observe clinical vs. non-clinical groups but also compare fear conditioning patterns between anxiety disorders to confirm our assumptions. Declaration of conflicting interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Foundation for Science and Technology, Portugal and Programa COMPETE [grants numbers SFRH/ BD/80945/2011, PTDC/MHC-PAP/5618/2014 (POCI-01-0145-FEDER-016836)]. The Cognitive and Behavioral Center for Research and Intervention of the Faculty of Psychology and Educational Sciences of the University of Coimbra is supported by the Portuguese Foundation for Science and Technology and the Portuguese Ministry of Education and Science through national funds and co-financed by FEDER through COMPETE2020 under the PT2020 Partnership Agreement [UID/PSI/01662/2013].

References ADInstruments Inc. (2019) PowerLab 26 Research Series Owner's Guide. Available at: http://m-cdn.adinstruments.com/owners-guides/PowerLab%2026%20Research %20Series%20-%20Jan%202019.pdf Apfeldorf WJ, Shear MK, Leon AC, et al. (1994) A brief screen for panic disorder. Journal of Anxiety Disorders 10: 71–78. Asthana M, Nueckel K, Mühlberger A, et al. (2013) Effects of transcranial direct current stimulation on consolidation of fear memory. Frontiers in Psychiatry 4(107): 1-7. DOI: 10.3389/fpsyt.2013.00107. Barlow DH (2002) The origins of anxious aprehension, anxiety disorders, and related emotional disorders: triple vulnerabilities. In: Barlow DH (ed.) Anxiety and its Disorders. The Nature and Treatment of Anxiety and Panic. New York: The Guilford Press, pp. 251-290. Boucsein W (2012) Electrodermal Activity (2nd ed). NewYork: Springer. Bradley MM. and Lang PJ (1999) International affective digitized sounds (IADS): Stimuli, instruction manual and affective ratings. Gainesville, FL: The Center for Research in Psychophysiology, University of Florida. Brosschot JF, Gerin W and Thayer JF (2006) The perseverative cognition hypothesis: A review of worry, prolonged stress-related physiological activation, and health. Journal of Psychosomatic Research 60(2): 113-124. Brosschot JF, Pieper S and Thayer JF (2005) Expanding stress theory: Prolonged activation and perseverative cognition. Psychoneuroendocrinology 30(10): 1043- 1049. Brosschot JF, Verkuil B and Thayer JF (2010) Conscious and unconscious perseverative cognition: is a large part of prolonged physiological activity due to unconscious stress?. Journal of psychosomatic research 69(4): 407-416. Canavarro MC (1999) Inventário de Sintomas Psicopatológicos: BSI. In: Simões MR, Gonçalves M and Almeida LS (eds) Testes e provas psicológicas em Portugal (vol. II). Braga: SHO/APPORT, pp.87-109. Carleton RN, Sharpe D and Asmundson GJ (2007) Anxiety sensitivity and intolerance of uncertainty: Requisites of the fundamental fears?. Behaviour Research and Therapy 45(10): 2307-2316. Dugas MJ, Gosselin P and Ladouceur R (2001) Intolerance of uncertainty and worry: investigating specificity in a nonclinical sample. Cognitive Therapy and Research 25: 551–558. Ganho-Ávila A, Goncalves OF, Guiomar R, et al. (2019) The effect of cathodal tDCS on fear extinction: a cross-measures study. bioRxiv [Internet]. DOI: https://doi.org/10.1101/561803 Ganho-Ávila A, Moura-Ramos M, Gonçalves O, et al. (in press) Measuring vulnerability to anxiety: Factorial structure, reliability, validity and discriminatory accuracy of the Anxiety Sensitivity Index-3-PT. Measurement and Evaluation in Counseling and Development IF: 0.902. Harrison BJ, Fullana MA, Soriano‐ Mas C, et al. (2015) A neural mediator of human anxiety sensitivity. Human Brain Mapping 36(10): 3950-3958. Hayes AF (2016) PROCESS [Computer software]. Available at: http://www.processmacro.org/index.html Hayes AF and Rockwood NJ (2017). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour Research and Therapy 98: 39-57. Heydayati M, Dugas MJ, Buhr K, et al. (2003, November). The relationship between intolerance of uncertainty and the interpretation of ambiguous and unambiguous information. Poster presented at the Annual Convention of the Association for Advancement of Behaviour Therapy, Boston, MA. Hedayati, M.; Dugas, MJ.; Buhr, K.; Francis, K. The relationship between intolerance of uncertainty and the interpretation of ambiguous and unambiguous information; Poster presented at the annual conference for the Association for Advancement of Behavior Therapy; Boston, MA: 2003 Nov. p. 20-23. Heydayati M, Dugas MJ, Buhr K, Francis K. The relationship between intolerance of uncertainty and the interpretation of ambiguous and unambiguous information. Presented at: The Annual Convention of the Association for Advancement of Behaviour Therapy. Boston, MA, USA, November 2003. Holaway RM, Heimberg RG and Coles ME (2006) A comparison of intolerance of uncertainty in analogue obsessive-compulsive disorder and generalized anxiety disorder. Journal of Anxiety Disorders 20: 158–174. Hughes ME, Alloy LB and Cogswell A (2008) Repetitive thought in psychopathology: The relation of rumination and worry to depression and anxiety symptoms. Journal of Cognitive Psychotherapy 22(3): 271-288. Huskisson EC (1974) Measurement of pain. The Lancet 304(7889): 1127-1131. Keller MB (2002) The long-term clinical course of generalized anxiety disorder. Journal of Clinical Psychiatry 63: 11–16. Kelly MM and Forsyth JP (2007) Observational fear conditioning in the acquisition and extinction of attentional bias for threat: An experimental evaluation. Emotion 7(2), 324-335. Kopacz FM and Smith BD (1971) Sex differences in skin conductance measures as a function of shock threat. Psychophysiology 8(3): 293-303. Lang PJ, Davis M and Öhman A (2000) Fear and anxiety: animal models and human cognitive psychophysiology. Journal of Affective Disorders 61(3): 137-159. Lissek S, Kaczkurkin AN, Rabin S, et al. (2014). Generalized anxiety disorder is associated with overgeneralization of classically conditioned fear. Biological Psychiatry 75(11): 909-915. Lissek S, Rabin S, Heller RE, et al. (2009) Overgeneralization of conditioned fear as a pathogenic marker of panic disorder. American Journal of Psychiatry 167(1): 47- 55. Lonsdorf TB, Menz MM, Andreatta M, et al. (2017) Don’t fear ‘fear conditioning’: Methodological considerations for the design and analysis of studies on human fear acquisition, extinction, and return of fear. Neuroscience & Biobehavioral Reviews 77: 247-285. Orr SP, Metzger LJ, Lasko NB, et al. (2000) De novo conditioning in trauma-exposed individuals with and without posttraumatic stress disorder. Journal of abnormal psychology 109(2): 290-298. Ottaviani C, Shapiro D and Couyoumdjian A (2013) Flexibility as the key for somatic health: From mind wandering to perseverative cognition. Biological Psychology 94(1): 38-43. Ottaviani C, Thayer JF, Verkuil B, et al. (2016) Physiological concomitants of perseverative cognition: A systematic review and meta-analysis. Psychological Bulletin 142(3): 231-259. Otto MW, Leyro TM., Christian K, et al. (2007) Prediction of “fear” acquisition in healthy control participants in a de novo fear-conditioning paradigm. Behavior Modification 31(1): 32-51. Ramaswami M (2014) Network plasticity in adaptive filtering and behavioral habituation. Neuron 82: 1216–29. Reiss S (1991) Expectancy model of fear, anxiety, and panic. Clinical psychology review 11(2): 141-153. Schweckendiek J, Klucken T, Merz CJ, et al. (2011) Weaving the (neuronal) web: fear learning in spider phobia. Neuroimage 54(1): 681-688. DOI: 10.1016/j.neuroimage.2010.07.049. Shin LM and Liberzon I (2010) The neurocircuitry of fear, stress, and anxiety disorders. Neuropsychopharmacology 35(1): 169-191. Silva DR (2003) O inventário de estado-traço de ansiedade (STAI). In: Gonçalves MM, Simões MR, Almeida LS, et al. (eds) Avaliação Psicológica, instrumentos validados para a população portuguesa. Coimbra: Quarteto Editora, pp.45-63. Starcevic V and Berle D (2006) Cognitive specificity of anxiety disorders: A review of selected key constructs. Depression & Anxiety 23: 51–61. Stockhorst U and Antov MI (2016) Modulation of fear extinction by stress, stress hormones and estradiol: a review. Frontiers in Behavioral Neuroscience 9: 359. DOI: 10.3389/fnbeh.2015.00359. Taylor S, Koch WJ and McNally RJ (1992) How does anxiety sensitivity vary across the anxiety disorders?. Journal of Anxiety Disorders 6(3): 249-259. Verkuil B, Brosschot JF, Gebhardt WA, et al. (2010) When worries make you sick: a review of perseverative cognition, the default stress response and somatic health. Journal of Experimental Psychopathology 1(1): 87-118. Wheaton MG, Deacon BJ, McGrath PB, et al. (2012) Dimensions of anxiety sensitivity in the anxiety disorders: Evaluation of the ASI-3. Journal of Anxiety Disorders 26: 401-408.