Although AB toward addiction-related stimuli is commonly reported, how the brain's attentional systems are affected to render such bias has remained unclear. For example, it is not clear whether this bias reflects a substance users' attention being selectively drawn towards drug-related items, or being held for longer periods and/or more extensive processing. Here, we investigated this issue using multiple attention tasks within subjects. Our data indicate that active nicotine use is associated with selective capture of attention by smoking cues, an effect that is positively correlated with smoking habit severity.
Classic studies of attentional capture by a reflexive cue found that short cue–target SOAs (up to ~300 ms) produce facilitation of processing at the cued location, while longer SOAs do not, and may produce an inhibition of return (IOR), in which processing is enhanced for cue-incongruent targets (
Posner and Cohen 1984;
Klein 2000). Here, we found that smokers' responses to smoking-cued targets were like those in classic reflexive cueing studies, supporting the interpretation that involuntary attentional capture by cigarette cues is enhanced in smokers, as the 200-ms SOA is not sufficiently long to allow voluntarily direction of attention toward smoking cues. The positive correlation between the AB at the 200-ms SOAs and the number of cigarettes smoked per day suggests that this attentional effect provides an objective index of smoking addiction severity. This absence of reflexive attentional capture in the control experiment with sports enthusiasts, suggests that the attentional capture effect in smokers is not due simply to the familiarity of the smoking cues. We speculate that this enhanced attentional capture reflects alteration of the brain's object detection system as a result of addictive processes. The incentive-sensitization theory of addiction posits that repeated use of an addictive substance heightens the “incentive salience” of stimuli associated with using that drug, leading to increased attention toward, and processing of such stimuli (
Robinson and Berridge 1993). A similar theory posits that as drug-related stimuli become associated with substance use, exposure to such stimuli increases dopamine release in corticostriatal circuitry, drawing attention to these stimuli; this heightened attention increases perception and processing of drug cues, helping to perpetuate the cycle of drug use (
Franken 2003). It is important to note that smoking habit duration varied among our AS group, with a large portion of relatively novice smokers; we would expect larger group differences with more experienced smokers in the AS group. Additionally, based on the wide range of “time since last cigarette” in this study, the dependence and/or withdrawal levels within the AS group was quite variable. While this variation allowed us to use regression analysis to assess individual differences, it potentially diluted the attentional effects in our AS group, which should be considered in future studies.
The current finding of quick attentional capture by smoking cues in smokers is consistent with results from previous studies of smoking cue bias using spatial cuing tasks. While few studies have used such short cue presentations,
Bradley et al. (2004) also found a greater bias towards smoking cues in smokers relative to non-smokers using a 200-ms cue. That study also found AB towards smoking cues with a 2000-ms SOA, a finding confirmed in other studies (
Bradley et al. 2003;
Mogg et al. 2005), which would seem to contradict our finding of no bias at a longer SOA (550 ms). However, studies of the time course of reflexive attention indicate that capture, and subsequent IOR, decays over a period of seconds and that by 1,500–2,000-ms IOR may be extinguished (
Coward et al. 2004;
Zhou 2008), allowing voluntary attentional processes to take over. Thus, the targets presented at the long SOA in Bradley and colleagues' study may have appeared outside the temporal window for reflexive attention and IOR. The fact that
Bradley et al. (2004) observed a bias towards smoking cues using a 2,000-ms SOA suggests that additional attention factors, such as voluntary deployment of attention, may also play a role in addiction-related bias. Another spatial-cueing study providing support for quick capture of smokers' attention by smoking cues is that of
Mogg et al. (2005), which found that most mildly dependent smokers more often made their first fixation to a smoking cue than did nonsmokers. Importantly, our inclusion of trials with two neutral stimuli in EXPERIMENT 3 allows us to definitively conclude that smoking cues are facilitating responses to smoking-congruent stimuli in active smokers. This latter result strongly supports the interpretation that smoking cues reflexively capture the attention of smokers.
While studies using very short or very long cue presentations provide fairly consistent evidence of smoking-cue bias in smokers, results from studies using a middle range of timings are more variable. Here, we found no AB with a cue-target SOA of 550 ms, but two studies using 500-ms cue durations found conflicting results (
Bradley et al. 2003;
Ehrman et al. 2002). This discrepancy likely reflects the proportion of smokers in those studies who had made repeated quit attempts. Although we did not collect information as to quit attempts in our participants, the fact that they were a largely novice group of smokers would suggest that few had made repeated quit attempts. Interest in quitting and repeated quit attempts could produce bias effects at the longer cue presentation based a greater contribution of volitional control of attention. Individuals trying to quit smoking may actively attend to smoking cues in an effort to avoid cigarettes and smoking-related situations. In addition, the other studies using a mid-range SOA used color images and a small dot or asterisk target, each of which might have contributed to differences in our results.
A potential caveat for this study is the possibility of group differences in nicotine levels during testing, given the attention-enhancing effects of nicotine (
Wesnes and Warburton 1984;
Koelega 1993;
Stolerman et al. 1995;
Foulds et al. 1996;
Mancuso et al. 1999;
Newhouse et al. 2004). However, the possibility that the observed group differences are due solely to differences in nicotine levels can be refuted by several arguments. First, plasma nicotine falls back to baseline levels within 10 min after smoking a cigarette (
Sakurai and Kanazawa 2002); our subjects arrived for testing an average of 96 min after smoking, and testing began ~20 min after arrival. Second, our regression analyses did not identify any significant correlations between bias effects and reported time from last cigarette. Despite this evidence, it remains possible that acute nicotine played a role in the observed effects; future tests of whether acute nicotine administration, or short- or long-term abstinence modulates these attentional effects will prove informative. A related concern is the effect of caffeine consumption on attention, as cigarette smokers are reportedly more likely to consume caffeine (
Istvan and Matarazzo 1984), which also affects attentional processing (
Lorist et al. 1994). While caffeine would not be expected to selectively affect attention toward smoking-related cues, future studies would benefit from quantifying and controlling for caffeine use.
A few attentional blink studies have shown that a drug-related T2 can preferentially capture the attention of addicts (
Liu et al. 2008;
Tibboel et al. 2009); however our novel test of the effects of T1 manipulation in an attentional blink paradigm found that detection of T2 was enhanced by a smoking-related T1 for smokers or a by sports-related T1 for sports enthusiasts. While our paradigm is novel, some published studies shed light on our results. First,
Most et al. (2005,
2007) have described an “attentional rubbernecking” phenomenon caused by emotional stimuli in attentional blink tasks. Specifically, processing of a target was interrupted when it appeared shortly after an emotionally charged stimulus. Similarly,
Munafo et al. (2005) found that cigarette-related words presented within a rapid stream can interrupt processing of a subsequent target in some smokers. A difference between these and more typical attentional blink studies (including our own) is that the critical stimuli that interrupt target processing are irrelevant to the task (i.e., they are not targets). This difference may be functionally important, as
Most and Junge (2008) recently showed that the interruption of T2 processing by emotionally charged stimuli disrupts lag-1-sparing, in which T2 detection is not impaired when it immediately follows T1. Here, in EXPERIMENT 1, in addition to lag-1-sparing, smokers more accurately detected T2s at lag 2 following a smoking T1, which is when the attentional blink usually peaks. These data would appear to support the idea that when smokers view a smoking-related T1, instead of experiencing a “rubbernecking” effect, in which their attention is preferentially held by that T1, they experience a general increase in attentional vigilance temporally extending to the detection of T2 beyond lag 1.
An alternative explanation to the increased vigilance theory is that, in our task design, the images appearing in the background are interrupting the foreground task of numeral detection, including processing of the T1 (numeral) stimulus. Supporting this interpretation is a recent study showing that visual processing resources were withdrawn from relevant foreground stimuli by an emotionally arousing image presented in the background (
Muller et al. 2008). If arousal caused by the smoking images interfered with smokers' processing of the T1 numerals, then T2 processing would be expected to be enhanced following a T1 superimposed on a smoking cue, as we observed here. While the preceding interpretation of our attentional blink results could be consistent with heightened attentional capture to the background task by smoking cues, two pieces of evidence argue against that interpretation. First, the bias effects measured at each lag of the attentional blink task were not correlated with any of the bias effects on the cueing task. This suggests that our attentional blink task is measuring an aspect of attentional allocation independent of reflexive attentional capture. Second, the effects of smoking cues on smokers' attention observed in the attentional blink task were similar to those of sports cues on sports enthusiasts' attention. Specifically, at lag 3, when the attentional blink should be near its peak, sports enthusiasts showed a larger blink for T2s following neutral T1s than for those following sports-related T1s. Another possibility is that stimulus familiarity effects are playing a role in the AB measured by our attentional blink paradigm. Indeed, recent evidence suggests that cue familiarity can alter T1 processing in attentional blink paradigms (
Parks and Hopfinger 2008). Thus, while the specific attentional blink paradigm used here may not provide a reliable measure of attentional hold, it seems to index some other experience-dependent measure of attentional allocation. The results of our multiple regression analysis, suggest that this aspect of attentional allocation may be related to addictive processes, as participants' reported time to next cigarette predicted the size of the observed bias effect.
In summary, the current study indicates that smokers' attention can be reflexively captured by smoking-related stimuli; however, much remains to be learned about addiction-related AB. For example, further investigation of attentional hold by smoking cues in nicotine users is needed. Moreover, the neural mechanisms of addiction-related AB remain virtually unknown. Elucidating these mechanisms via neuroimaging and behavioral pharmacology studies is particularly warranted. An open and critical question is whether medications that reduce drug craving do so in part via effects on attentional processing. The present spatial cueing paradigm may prove useful in this regard. Ultimately, laboratory-based studies testing the diminishment of the smoking-related AB in response to therapeutic interventions could prove critical for identifying novel effective treatments for addiction.
Chandler R. Sours, and Charlotte A. Boettiger
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