Is smoking automatic? Demands of smoking behavior on attentional resources.

Baxter, Bruce W.; Hinson, Riley E.

doi:10.1037//0021-843x.110.1.59

Cited by 10 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, our findings in motor areas (also some regions in the cerebellum) might be related to automatised action schemata, 6 18 as a complement to incentive habits, which would match with previous findings that heavier substance users showed a more automatised consumption. 19 In many cue reactivity studies, motor-related areas also have been reported that activated differently towards substance‐related stimuli. 11 15 Here we would like to specifically note that the motor brain not only represents the reward values from visual analog scale scores but also the cue features from computer vision (dCNN model), which was not reward-mounted in our hypothesis.…”

Section: Discussionmentioning

confidence: 99%

Decoding fMRI alcohol cue reactivity and its association with drinking behaviour

et al. 2023

View full text Add to dashboard Cite

BackgroundCue reactivity, the enhanced sensitivity to conditioned cues, is associated with habitual and compulsive alcohol consumption. However, most previous studies in alcohol use disorder (AUD) compared brain activity between alcohol and neutral conditions, solely as cue-triggered neural reactivity.ObjectiveThis study aims to find the neural subprocesses during the processing of visual alcohol cues in AUD individuals, and how these neural patterns are predictive for relapse.MethodsUsing cue reactivity and rating tasks, we separately modelled the patterns decoding the processes of visual object recognition and reward appraisal of alcohol cues with representational similarity analysis, and compared the decoding involvements (ie, distance between neural responses and hypothesised decoding models) between AUD and healthy individuals. We further explored connectivity between the identified neural systems and the whole brain and predicted relapse within 6 months using decoding involvements of the neural patterns.FindingsAUD individuals, compared with healthy individuals, showed higher involvement of motor-related brain regions in decoding visual features, and their reward, habit and executive networks were more engaged in appraising reward values. Connectivity analyses showed the involved neural systems were widely connected with higher cognitive networks during alcohol cue processing in AUD individuals, and decoding involvements of frontal eye fields and dorsolateral prefrontal cortex could contribute to relapse prediction.ConclusionsThese findings provide insight into how AUD individuals differently decode alcohol cues compared with healthy participants, from the componential processes of visual object recognition and reward appraisal.Clinical implicationsThe identified patterns are suggested as biomarkers and potential therapeutic targets in AUD.

show abstract

Section: Discussionmentioning

confidence: 99%