Assessing attentional bias and inhibitory control in cannabis use disorder using an eye-tracking paradigm with personalized stimuli.

Abstract

Individuals with cannabis use disorders (CUD) show inhibitory control deficits and differential attention toward marijuana (MJ) stimuli. The robustness and utility of these measures in the CUD literature are somewhat equivocal. The present study was designed to increase measurement sensitivity by capitalizing on (a) individually calibrated stimulus selection based on cue reactivity patterns and (2) eye-tracking based measurement. CUD (n = 42) and non-CUD controls (n = 11) served as subjects. Subjects were first exposed to MJ and neutral pictures while measuring physiological and subjective responses on a trial by trial basis. A single reactivity index was created for each stimulus (L2 vector norm). Subject-unique high-reactivity MJ and low-reactivity neutral stimuli were then used in an eye-tracking task (pro-/antisaccade). The stimulus calibration procedure produced large reactivity differences between high/MJ and low/neutral stimuli (p < .001, effect size >7). CUD subjects made more overall antisaccade errors than controls (inhibitory control, p < .02, effect size >1), and CUD subjects (but not controls) made more errors on MJ trials versus neutral trials (attentional bias, p < .002, effect size >1). Within CUD subjects, L2 vector norm scores were associated with antisaccade errors (p < .04), and antisaccade errors were correlated with the Perceived Stress Scale (p < .03) and marginally with CUD severity (p < .07). Because of precise understanding of the neural circuitry governing antisaccades (a marker in several neuro/psychiatric disorders), eye movement–based measures combined with individually determined stimuli may provide an efficient and robust marker in CUD research.

Eye Tracking Studies Exploring Cognitive and Affective Processes among Alcohol Drinkers: a Systematic Review and Perspectives

“…The evolution of this field towards an optimized use of eye movements' measures across the whole spectrum of alcohol consumption habits should help eye tracking to become a key tool in the exploration of alcohol-related disorders, by contributing to their experimental exploration and theoretical conceptualization. Beyond alcohol-related disorders, eye tracking explorations have recently emerged in other addictive states like nicotine (e.g., Baschnagel, 2013;Lochbuehler et al, 2018), cannabis (e.g., Alcorn et al, 2019;Yoon et al, 2019), cocaine (e.g., Dias et al, 2015Strickland et al, 2018) or gaming/gambling use (e.g., Kim et al, 2019;McGrath et al, 2018), showing similar results than those reported in the present review. Some deficits indexed with eye tracking tools (e.g., modified cue salience, reduced inhibitory abilities) might thus constitute transdiagnostic processes, and studies directly comparing eye movements' characteristics across addictive disorders should be promoted.…”

Electrophysiological responses to emotional and cocaine cues reveal individual neuroaffective profiles in cocaine users.

“…Higher overall error rate indicates failure in visual inhibitory control (Dias et al, 2015; Suchting et al, 2020; Tannous et al, 2019). Attentional bias was calculated as errors on cocaine-stimulus trial divided by total errors, whereby a value greater than 0.50 indicates visual inhibitory failures specific to cocaine-related stimuli (i.e., more than 50% of errors occurring on cocaine-stimulus trials) (Dias et al, 2015; Yoon et al, 2019). Due to participant scheduling and equipment failures, a total of 35 participants completed both the EEG and eye-tracking tasks; as such, analyses with eye-tracking data reflect this sample size.…”

“…Specifically, antisaccade tasks instruct participants to look at the hemifield opposite of a presented stimulus and measure inhibitory visual control (Everling & Fischer, 1998). Attentional bias toward drug cues is operationally defined as a higher antisaccade error rate for drug cues compared to neutral cues (Dias et al, 2015; Suchting et al, 2020; Tannous et al, 2019; Yoon et al, 2019). We reasoned that if the two LPP reactivity profiles that we identified reflect individual differences in the tendency to attribute incentive salience to drug-related cues, then, in the antisaccade task, individuals with the C > P profile should have higher attentional bias toward drug cues than individuals with the P > C profile.…”

What Does Your Gaze Reveal About You? On the Privacy Implications of Eye Tracking

“…2.8), eye tracking data may contain information about a user's longer-term drug consumption habits and addictions. Numerous eye tracking studies have reported a strong attentional bias towards drug-related visual cues in addicts of cocaine [16], alcohol [67], cannabis [90], and tobacco [18,70].…”