Enhanced visuomotor processing of phobic images in blood-injury-injection fear
Introduction
In recent years, numerous studies demonstrated that information processing of phobic stimuli is enhanced in individuals with animal phobias. For instance, motor responses are faster and visual search times are lower for phobic stimuli as compared to neutral ones (e.g., Lipp and Waters, 2007, Öhman et al., 2001). Additionally, an involuntary orientation of attention toward phobic stimuli is frequently reported (Mogg and Bradley, 2006, Rinck and Becker, 2006, for reviews see Mogg and Bradley, 1998, Williams et al., 1997). For instance, the studies by Mogg and Bradley (2006) and by Rinck and Becker (2006) suggest that phobic stimuli capture attention. While there is wide agreement about the existence of an attentional bias toward phobic stimuli, it is less clear what the exact attentional mechanisms are. Several studies suggest that an initial, involuntary orientation toward phobic images is followed by intentional avoidance (Derakshan et al., 2007, Mogg and Bradley, 2006, Rinck and Becker, 2006), but many of the currently employed paradigms are not precise enough to distinguish between automatic capture of attention and rapid modulation by top-down processes. For example, Bardeen and Orcutt (2011) as well as Peers and Lawrence (2009) demonstrated that top-down mechanisms, such as attentional control, can influence the bottom-up orientation to threat stimuli within the first 100–200 ms of processing. Beside the interpretation that attention is drawn toward phobic or threat-relevant stimuli, there is also some evidence that the bias might result from disengagement difficulties away from those stimuli in fearful individuals (cf. Amir et al., 2003, Fox et al., 2002, Gerdes et al., 2008). Despite these open questions, all these studies agree that phobic or threat-relevant stimuli benefit from some form of processing enhancement over the time-course of the first half second of processing. In this paper, we are interested specifically in the enhanced ability of phobic stimuli to drive fast motor responses, such as keypress responses performed under time pressure.
Many studies show enhanced processing of fear-relevant material in a great variety of phobias and anxiety disorders, but few studies directly compared participants with different types of anxiety disorders. Öhman et al. (2001) asked non-anxious control, spider phobic, and snake phobic participants in a visual search task to search for pictures of spiders or snakes in grid-pattern arrays of flower and mushroom pictures, or vice versa. They found that fear-relevant pictures of spiders and snakes were found more quickly than neutral pictures by all three groups, with even faster responses to phobic stimuli in the two phobic groups (also cf. Teachman et al., 2001, Wenzel and Holt, 1999).
However, Soares, Esteves, Lundquist, and Öhman (2009) reported that spider-fearful participants were specifically faster in detecting spiders compared to fear-relevant but non-phobic snakes and to neutral targets in a visual search task. In contrast, snake-fearful participants showed no differences in performance between snakes and fear-relevant but non-phobic spider pictures. We observed a similar asymmetry in a response priming study with spider-fearful, snake-fearful, and non-anxious control participants (Haberkamp, Schmidt, & Schmidt, 2013). Participants were presented with target images of spiders, snakes, flowers, or mushrooms, and had to decide as quickly as possible whether the target was an animal or non-animal by pressing one of two keys. Target images were preceded by prime images from the same four categories that could either prime the correct or incorrect response, thereby speeding or slowing responses to the target (response priming effect; Vorberg, Mattler, Heinecke, Schmidt, & Schwarzbach, 2003). In the group of spider-fearful participants, only spider pictures had a strong influence on motor responses, leading to fast response times and large priming effects. In contrast, in snake-fearful participants, enhanced processing of phobic material was less pronounced and extended not only to snake but also to spider images.
Such results suggest that information processing might differ in different types of specific phobias. Within the class of specific phobias, there is one type that especially differs from other specific phobias; that is blood-injury-injection (BII) phobia. In BII phobia, individuals experience an extreme and irrational fear of blood, injuries, or of receiving an injection or an invasive medical procedure (Öst, 1992). The prevalence rate is approximately 3.5% (Bienvenu & Eaton, 1998), and women are affected twice as often as men (Hamm, 2006). This phobia lends itself to investigation due to three reasons: (1) BII phobia has distinct features that distinguish it from all other specific phobias (e.g., experience of nausea and fainting in phobic situations; experiencing not only fear but also disgust,1 e.g., Koch et al., 2002, Schienle et al., 2005); (2) few studies have investigated the speed of information processing in individuals with BII phobia compared to the large number of studies focusing on animal and social phobia; (3) those studies that did produced mixed results. Thus, it remains unclear whether BII-fearful individuals exhibit enhanced information processing and a bias similar to that in other phobias.
Let us look at the peculiarities of BII phobia in some more detail. First of all, up to 70% of BII phobics report a history of fainting due to a marked drop in blood pressure, heart rate, or both when confronted with their phobic stimuli (i.e., blood or injections) (Öst, 1992). In contrast, in other specific phobias (e.g., animal phobia), exposure typically triggers sympathetic reactions, for instance, panic-related symptoms like sweating, trembling, and an increased heart rate and blood-pressure (Antony, Brown, & Barlow, 1997). Furthermore, individuals with BII phobia frequently avoid medical procedures, which might lead to serious health implications (Öst, 1992). Therefore, Armstrong, Hemminger, and Olatunji (2013) argue that research should contribute to develop more effective treatments for BII-fearful individuals. According to these authors, one promising area is that of studying vigilance in BII-fearful individuals since the early attentional bias may contribute to the increased distress when they are confronted with a phobic stimulus (Weierich, Treat, & Hollingworth, 2008).
Even though an attentional bias favoring phobic stimuli is a core feature of other specific phobias, the evidence for such a bias in BII fear is equivocal. For example, Sawchuk et al. (1999) used a modified Stroop task to compare semantic information processing in BII phobic and non-phobic control participants. Ten medical (e.g., “injection”), 10 disgust (e.g., “vomit”), 10 negative (e.g., “lonely”), and 10 neutral words (e.g., “spoon”) were randomly presented in black, blue, green, or red. The authors measured color-naming latencies in BII phobics and control participants for medical and disgust words and found no difference between the two groups. In particular, BII phobics were not slowed in naming the color of phobic words, indicating that their attention was not distracted by the phobic word. In line with these findings, Wenzel and Holt (1999) showed in a dot-probe task that individuals with BII phobia did not exhibit an attentional bias toward their phobic stimuli (i.e., the phobic group responded similarly fast to the probe regardless of whether it was presented at the location of a phobic or a neutral word). However, both studies are limited by the fact that they used lexical stimuli which might not be strong enough to elicit an attentional bias in BII-fearful participants (Armstrong et al., 2013). Additionally, the modified Stroop task has recently received some criticism, with some authors suggesting that the task is not suitable to measure information processing biases for emotional words (Algom et al., 2004, McKenna and Sharma, 2004, Weierich et al., 2008; for a critical review of the modified Stroop task in PTSD cf. Kimble, Frueh, & Marks, 2009; also see Bardeen & Orcutt, 2011).
The limitations of the modified Stroop task were overcome in a series of experiments that were conducted more recently by Buodo and colleagues. In their eye-tracking study, BII-fearful and control participants were shown phobic, positive emotional, and neutral pictures (Buodo, Sarlo, Codispoti, & Palomba, 2006). The authors measured free viewing times and event-related potentials (ERPs). The eye-tracking results revealed no clear pattern of visual avoidance in BII-fearful participants: Even though these participants spent less time looking at blood pictures when compared to control participants (between-groups comparison), they did not spend less time looking at blood pictures compared to the other picture categories (within-group comparison). Thus, phobic pictures were not specifically shunned by BII-fearful individuals. Additionally, the ERPs amplitudes of BII-fearful participants revealed neither an increase indicating an attentional bias toward the phobic stimuli nor a decrease indicating avoidance of the phobic stimuli. The authors concluded that BII-fearful individuals show no vigilance-avoidance pattern.
In a follow-up study, the authors measured magnetoencephalography (MEG) activity in BII-fearful and non-anxious control participants in response to phobic and non-phobic pictures (Buodo, Peyk, Junghöfer, Palomba, & Rockstroh, 2007). They found a higher activation in BII-fearful participants for the two picture categories of phobic and neutral stimuli, but not specifically for phobic pictures. Again, they interpreted these findings as evidence that phobic stimuli are not preferentially processed by BII-fearful individuals.
However, there is also evidence that BII phobia is associated with a vigilance-avoidance pattern. Tolin, Lohr, Lee, and Sawchuck (1999) used a viewing paradigm and showed that BII phobics avoided viewing injection images compared to non-anxious controls and spider phobics. Mogg, Bradley, Miles, and Dixon (2004) found the same effect for BII-fearful participants in a visual dot-probe task. In addition, the authors showed that an intentional avoidance was preceded by an initial vigilance for phobic stimuli. Finally, two studies by the group of Buodo and colleagues contradicted the group's earlier results. Buodo, Sarlo, and Munafò (2010) investigated the N2pc component of ERPs – which is assumed to reflect processes of spatial attention – in BII-fearful and non-anxious control participants and found an attentional bias followed by visual avoidance. Subsequent, Sarlo, Buodo, Devigili, Munafò, and Palomba (2011) induced cognitive-emotional sensitization in BII-fearful participants by repeatedly presenting the same pictures of blood and mutilation, randomly interspersed with neutral images. They observed an early attentional bias, indicated by larger early N100 potentials, in the group of BII phobics compared to controls, followed by attentional avoidance reflected in smaller late positive potentials.
There is even one study that reports an attentional bias but not in line with the vigilance-avoidance theory. In an eye-tracking study by Armstrong et al. (2013), BII-fearful participants showed a robust vigilance-avoidance pattern. But even though BII-fearful participants oriented their attention more often to injection images and avoided them subsequently compared with non-anxious control participants, they did not attend to those images more frequently compared to other emotional images. These results imply that BII-fearful individuals respond more vigorously to emotional images per se, but not specifically to phobic images.
In sum, the existence of a processing bias for phobic stimuli in BII phobics is equivocal. Here, we provide further evidence for enhanced processing for phobic images in BII phobia. We measured behavioral data by using a response priming paradigm (Klotz and Wolff, 1995, Vorberg et al., 2003, also cf. Schmidt, Haberkamp, & Schmidt, 2011). This paradigm focuses on rapid and automatic information processing and was successfully applied in a previous study with spider- and snake-fearful participants (Haberkamp et al., 2013, Schmidt et al., 2011a). In a typical response priming task, participants are asked to classify a target stimulus as quickly and accurately as possible by pressing either the left or the right button. For instance, participants are required to press one button if the target shows an injured body part, and the other button if it shows an uninjured body part. The target stimulus is preceded by a prime stimulus that is either assigned to the same response, speeding the response to the target (consistent prime), or it is assigned to the opposite response, slowing the response to the target and provoking response errors (inconsistent prime). The difference in response time or error rate between trials with consistent and inconsistent primes is called the response priming effect and increases with increasing stimulus-onset asynchrony (SOA) between prime and target (Vorberg et al., 2003). We have argued (Schmidt et al., 2011a, Schmidt et al., 2006, Vath and Schmidt, 2007) that response priming is based on visuomotor feedforward sweeps triggered by the primes and targets, i.e., neuronal activation progressing quickly enough from visual to motor areas to remain essentially devoid of intracortical feedback (Lamme & Roelfsema, 2000). We propose that feedforward sweeps elicited by primes and targets traverse the visuomotor system in strict sequence, leading to a motor conflict when the two stimuli are mapped to different responses (rapid-chase theory of response priming).
Response priming can measure rapid information processing of visual primitives (e.g., grouping principles, Schmidt & Schmidt, 2013) and can compare motor activation with aspects of conscious perception (Ansorge et al., 2011, Mattler, 2007, Schmidt and Vorberg, 2006, Vorberg et al., 2003). It was also successfully applied to investigate the processing of natural images which have been shown to be classified very rapidly (Kirchner and Thorpe, 2006, VanRullen and Thorpe, 2001). For instance, Schmidt and Schmidt (2009) asked participants to classify natural target images into animals and objects by means of speeded pointing responses. They demonstrated not only that primes are able to influence the pointing trajectory, but that the initial movement is controlled exclusively by the prime, which determines the finger's initial flight-path independent of the actual target. In contrast, later phases of the movement are controlled by the target (cf. Schmidt et al., 2006). This pattern of strictly sequential response control by primes and targets lends strong support to the idea that response priming is based on sequential visuomotor feedforward sweeps, even when natural images are involved. Response priming should thus be suitable for measuring basic processing characteristics for BII-relevant stimuli like pictures of harmed and unharmed body parts. It has the additional advantage that strategic response biases (which are common in fearful individuals) are not likely to influence the results. In addition, we can analyze the fastest responses of the participants to confirm a strong prediction of rapid-chase theory: Priming effects should be fully present in the fastest responses and not increase any further in slower responses (Haberkamp et al., 2013, Schmidt and Schmidt, 2014).
We chose to employ images of small injuries plus control images of unharmed body parts. These pictures of small injuries represent phobic stimuli for BII-fearful participants, but merely fear-relevant stimuli for the non-anxious control participants. The control pictures represent neutral stimuli for both groups. We assumed that highly arousing pictures of severe mutilations would also evoke strong reactions in the control participants, so that possible differences between them and the BII-fearful group would be difficult to detect. In contrast, minor injuries, which are frequently encountered in everyday life, should elicit strong emotional reactions only in the BII-fearful participants but not in control participants. In the present experiment, one prime and one target were presented in rapid sequence, and participants classified the targets as quickly as possible by pressing one button for injury pictures and another button for non-injury (neutral) pictures. We hypothesized that the BII-fearful participants would show enhanced processing of the injury pictures. This will be expressed in larger priming effects by injury as compared to neutral primes (within-group comparison) or as compared to non-anxious control participants (between-groups comparison). In addition, there should be faster responses to injury targets as compared to neutral targets (within-group and between-groups comparisons).
Section snippets
Methods
Participants. Fifty-one participants took part in the experiment, recruited through the University of Kaiserslautern. All of them were naïve to the purpose of the study. We specifically asked for participants who rated themselves as being highly afraid of blood, injuries, and injections, or neither of these. All participants were screened for fear of blood, injury and injections before the experiment started. For this purpose, we applied two blood-injury-injection-questionnaires (German version
Results
We first analyze the influence of the primes on response times in the two groups and link the effect to the influence of the targets on overall response times. Second, we test whether the influences of primes and targets are fully present in the fastest responses (i.e., in the 2nd and 3rd deciles of the response time distribution).
Influence of the primes on response times. Response times for the two groups (controls and BII fear) and prime types (injured vs. unharmed body parts) are displayed
Discussion
Overall, we found robust response priming effects for each of the two prime categories in the two groups of non-anxious control and BII-fearful individuals. In all experimental conditions (except one, but see below), inconsistent trials led to slower response times and more errors compared to consistent ones. These findings are in line with previous results from the image classification literature (e.g., Bacon-Macé et al., 2007, Kirchner and Thorpe, 2006; for a review see Fabre-Thorpe, 2011) as
Author note
This work was supported by the German Research Foundation (DFG), grant Schm1671/1 to T.S. We especially thank Nicole Reinert, Marie Salzmann, and Dessislava Todorova for data collection. For a profound revision of an earlier manuscript version, thanks to Shanley Allen, Filipp Schmidt, and Andreas Weber. Furthermore, we thank our student assistants Peter Kohl and Miriam Neumann.
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