Related Experiment Video
Updated: Jun 4, 2026
Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study
Published on: August 18, 2020
No differences in inhibitory control or prefrontal activation during a cannabis cue stop-signal task across
Christopher R Pickering1, Valentina Lorenzetti2,3, Andrew Jones4
1Department of Psychology, University of Liverpool, Eleanor Rathbone Building, Bedford Street South, Liverpool, L69 7ZA, UK. Christopher.Pickering@liverpool.ac.uk.
Rationale:
Cannabis use continues to increase globally, with a growing proportion of users exhibiting problematic patterns of use. Although neural differences in reward and inhibitory control systems are commonly reported in individuals who use cannabis relative to individuals not reporting cannabis use, findings using behavioural tasks are inconsistent. This is possibly due to lack of differentiation between regular and more problematic patterns of use.
Objectives:
This study investigated whether inhibitory control performance and associated prefrontal and orbitofrontal activation differed across CUDIT-R-stratified levels of CUD risk.
Methods:
Participants (N = 81) were divided into three groups based on CUDIT-R scores: 30 high-CUD-risk individuals who use cannabis (≥ 12), 21 low-CUD-risk individuals who use cannabis (< 8), and 30 individuals not reporting cannabis use. Individuals with a current substance use disorder, including cannabis use disorder, were excluded from participation. All completed a cannabis-cue specific Stop-Signal Task (SST) while functional near-infrared spectroscopy (fNIRS) was used to measure oxygenated (oxyHb) and deoxygenated haemoglobin (deoxyHb) concentrations in the prefrontal cortices. Behavioural performance and neural activation were compared across groups.
Results:
No significant behavioural or neural differences were found between the groups.
Conclusions:
The study found no evidence of impaired inhibitory control or differential prefrontal activation across CUDIT-R-stratified levels of CUD risk. The results suggest incorporating further diagnostic stratification, multimodal imaging, and ecologically valid methods in future research to better characterise cannabis-related neural adaptations and inform clinical practice.
