DOI 10.1016/j.comppsych.2025.152627
Investigating attentional bias in low-dependence smokers with steady-state visual evoked potentials (SSVEPs): Linking wanting, liking, and neural responses.
Аннотация
While traditional electrophysiological measures such as ERPs have been successfully used to study individual differences, their signal-to-noise ratio often limits the precision of single-subject analyses. To address this, the present study had two primary aims: (1) to explore the utility of steady-state visual evoked potential (SSVEP) method for investigating addiction-specific cognitive processes and (2) to examine the relationship between the imbalance of self-reported wanting and liking, and the neural correlates of tobacco smoking-related attentional bias. A total of 39 participants, including smokers (N = 22) and non-smokers (N = 17), were exposed to a passive visual oddball paradigm comprising rapidly flickering stimuli under two conditions: neutral (e.g., office tools) and smoking-related (e.g., cigarettes). Neural activity was recorded using EEG, and frequency-specific SSVEP responses were analyzed to assess attentional bias toward smoking-related stimuli. The results demonstrated that SSVEPs effectively captured the well-documented attentional bias effect between smokers and non-smokers. Furthermore, beyond group-level comparisons, SSVEPs proved suitable for examining attentional bias at the individual level, allowing for the investigation of correlations between neural responses to smoking cues and the difference between self-reported wanting and liking (WmL) imagined before, during and after smoking. A moderate to strong positive correlation was observed specifically for WmL-after and attentional-bias, supporting two conclusions: (1) SSVEPs represent a promising tool for assessing addiction-specific cognitive processes, and (2) self-reported assessments of incentive sensitization theory (IST) may be associated with attentional bias characteristic of addictive behaviors. These findings highlight the potential value of self-report measures in human IST research and underscore the need for further investigation.
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