Effects of predictability of shock timing and intensity on aversive responses
Research Highlights
► Both unpredictable and predictable aversive events lead to negative emotions. ► However, unpredictable aversive events lead to more intense anxious responding. ► Most studies manipulate predictability of timing, but not other characteristics. ► We found that unpredictable timing or intensity of shock elevated anxious responding. ► Anxiety may arise when multiple features of aversive stimuli are unpredictable.
Introduction
Researchers have long been interested in emotional responsivity to unpredictable aversive stimuli or events (Barlow, 2000, Davis, 2006, Grillon et al., 2004, Imada and Nageishi, 1982). Both predictable and unpredictable aversive stimuli induce negative emotional states (Fanselow, 1980, Grillon, 2002), but animal studies suggest that unpredictable aversive stimuli are associated with more disturbed physiological responding, such as muscle tension and ulceration (Mineka and Kihlstrom, 1978, Seligman, 1968, Seligman and Maier, 1967, Weiss, 1970), and are more likely to evoke avoidance behavior (Frankel and Vom Saal, 1976, Lockard, 1963; see Imada and Nageishi, 1982). Emotional reactions to predictable and unpredictable aversive stimuli have also been shown to be mediated by overlapping but distinct neural systems (Davis, 2006, Gray and McNaughton, 2000). Moreover, a heightened sensitivity to unpredictable aversiveness has been proposed to be a key variable in the etiology and maintenance of anxiety disorders, particularly post-traumatic stress disorder and panic disorder (Craske et al., 2009, Grillon, 2008a, Grillon et al., 2008, Grillon et al., 2009).
One of the ways psychophysiological researchers have examined unpredictability is by measuring startle response while individuals anticipate either a predictable or unpredictable aversive stimulus (e.g., a shock). The startle response is a well-documented indicator of aversive system activation (Lang, 1995). It is modulated by aversive emotional states, such as anxiety (Lang et al., 1998), and its neurobiology has been studied extensively (Koch, 1999).
Grillon and colleagues developed a novel startle paradigm to measure aversive responses to unpredictability (Grillon et al., 2004, Grillon et al., 2008, Grillon et al., 2009). The paradigm consists of three within-subjects conditions (i.e., No Threat, Predictable Threat, Unpredictable Threat), and during each condition participants are presented with a geometric cue several times on a computer screen while they receive startle probes (e.g., brief, loud acoustic probes presented through headphones). During the “No Threat” condition, participants are never in danger of receiving the aversive stimulus (e.g., shock). During the “Predictable Threat” condition, participants can only receive the aversive stimulus while the geometric cue is present on the screen and are safe from the aversive stimulus when it is absent (i.e., during the inter-trial interval [ITI]). During the “Unpredictable Threat” condition, participants can receive the aversive stimulus while the geometric cue is on the screen or when it is absent (i.e., the cue does not predict the aversive stimulus). In short, participants can predict when they will receive the aversive stimulus during the Predictable Threat condition but cannot predict its occurrence during the Unpredictable Threat condition. Studies that have used this paradigm suggest that those with certain anxiety disorders show elevated startle responses to unpredictable threat but not predictable threat (Grillon et al., 2008, Grillon et al., 2009). Additionally, substances such as alcohol and benzodiazepines appear to only affect responses to unpredictable threat, suggesting that the two threats are pharmacologically distinct (Grillon et al., 2006, Moberg and Curtin, 2009). These latter findings also support the theory that predictable aversiveness yields a qualitatively different response from unpredictable aversiveness (often labeled fear and anxiety, respectively; Davis, 2006, Grillon, 2008a).
To date, the majority of research examining the effects of predictability in humans has focused on manipulating the timing of aversive stimulus delivery (i.e., whether the person is able to predict the onset of the aversive stimulus). However, not being able to predict other characteristics of aversive stimuli may also play a role in aversive responding. Indeed, animal studies of aversive responding have manipulated the predictability of multiple features of aversive stimuli (see Imada and Nageishi (1982), for review). For example, a few studies have manipulated whether the intensity of the aversive stimulus is predictable or unpredictable. Using a classic shuttle-box experiment, Marlin et al. (1979) presented rats with shocks that were either of predictable or unpredictable intensity and animals were significantly more likely to avoid the latter. Fujii et al. (1994) conducted a similar experiment and found that unpredictable intensity induced a suppression of licking behavior (a behavioral indicator of an aversive emotional state). In both of these studies, the predictability of the shock's intensity was the only parameter that was manipulated as the onset (timing) of the shocks was always predictable. This suggests that the effects of predictable intensity may be independent of predictable timing.
The aim of this study is therefore to compare in humans two cases of unpredictability — timing and intensity. Specifically, we will adapt the startle paradigm of Grillon and colleagues’ (Grillon et al., 2004, Grillon et al., 2008) to manipulate the predictability of the timing and intensity of aversive stimuli. This will allow us to examine the independent and interactive effects of unpredictable timing and intensity on startle and subjective responses.
While the hypotheses for timing manipulation are essentially to replicate what others have reported in the literature (i.e., elevated response in the unpredictable condition during the ITI), the hypotheses for the intensity manipulation are less clear. We expect that those in the unpredictable intensity groups would experience the task as more aversive than those in the predictable intensity groups, but it is unclear whether this will manifest itself as elevated responses during the ITI, cue, or both. Within our design, the two Intensity groups are balanced on Timing (i.e., the variable which specifically manipulates the meaning of the cue). Thus, the cue and the ITI should have the same meaning in both Intensity groups. However, as this is an exploratory manipulation, we hesitate making a strong hypothesis regarding which conditions will be affected by the intensity manipulation.
The present study also adapted the Grillon et al., 2004, Grillon et al., 2008 paradigm in another significant way. Because the aforementioned paradigm is a within-subjects’ design, it is possible that the effects of one condition may carry-over into the effects of another (Greenwald, 1992). For example, responses to the unpredictable threat condition may influence responses to the predictable threat condition, as the latter is likely to be preferred according to the “preference-for-signaled-shock phenomena” (Badia et al., 1979, Fanselow, 1980). Also, consistent with the carry-over effect hypothesis, several studies using the Grillon and colleagues paradigm reported that participants’ startle responses were elevated during the ITI of the predictable condition relative to the ITI of the no threat condition (Grillon et al., 2004, Grillon et al., 2008). That is, even though participants were “safe” during the ITI of the predictable condition (i.e., the cue is not on the screen), they nonetheless exhibited an elevated startle response. Grillon et al. (2004) suggested that this elevated response may reflect anticipation of the cue in the predictable condition (and possibly contextual anxiety; Fanselow, 2010), although it may have also reflected carry-over effects from the unpredictable condition.
In order to rule out carry-over effects in the present study, we changed the Grillon et al., 2004, Grillon et al., 2008 design so that the predictable and unpredictable conditions were between-subjects rather than within-subjects conditions. Additionally, our intensity manipulation (predictable vs. unpredictable) was a between-subjects manipulation. An added advantage of examining both parameters of interest (timing and intensity) as between-subjects factors is that it allowed a more direct comparison of their independent and interactive effects on aversive responding.
Section snippets
Participants
One-hundred fifteen undergraduates from a large Midwestern university participated in the study for course credit. The sample was 64.5% female and had an average age of 19.51 (SD = 1.35). The sample was ethnically diverse with 37.3% Caucasian, 5.5% African-American, 19.1% Hispanic, 25.5% Asian, and 12.7% of other ethnic descent. All participants gave informed consent.
Stimuli and physiological responses
Stimuli were regulated by Contact Precision Instruments (London, UK) and startle data were recorded using a PC-based acquisition
Results
Participants rated the shocks as moderately intense (M = 4.59, SD = 1.00) and indicated that they would prefer to avoid receiving the shocks again (M = 2.74, SD = 1.18). This suggests that the shocks had the intended aversive effect. Additionally, a Timing × Intensity ANOVA on these measures did not yield any main effects for Timing or Intensity (p's > .25), or a Timing × Intensity interaction (p's > .26), suggesting that groups did not differ in their perception of the shocks. The groups also did not differ
Discussion
Unpredictability has been operationalized in animal studies as a “class of situations involving elements of irregularity, [or] lack of lawfulness…about environmental events” (Imada and Nageishi, 1982, p. 574). The present study sought to examine two of these “classes” — unpredictable timing and unpredictable intensity. Specifically, we examined whether startle and subjective anxiety were potentiated differently when participants did not know a) when they would receive a shock and/or b) the
Acknowledgements
This study was supported by a UIC Office of Social Science Research grant awarded to Stewart A. Shankman. We would like to acknowledge the assistance of Natalia Ryszko, Ana Genkova, Alicia Oplustil, Megan Preusker and Mallory Swift in data collection and coding. We would also like to thank Christian Grillon and Shmuel Lissek, whose work inspired the idea for this study.
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