Evaluating instrumental learning and striatal–cortical functional connectivity in adolescent alcohol and cannabis use

Abstract

Adolescence is a vulnerable time for the acquisition of substance use disorders, potentially relating to ongoing development of neural circuits supporting instrumental learning. Striatal–cortical circuits undergo dynamic changes during instrumental learning and are implicated in contemporary addiction theory. Human studies have not yet investigated these dynamic changes in relation to adolescent substance use. Here, functional magnetic resonance imaging was used while 135 adolescents without (AUD‐CUDLow) and with significant alcohol (AUDHigh) or cannabis use disorder symptoms (CUDHigh) performed an instrumental learning task. We assessed how cumulative experience with instrumental cues altered cue selection preferences and functional connectivity strength between reward‐sensitive striatal and cortical regions. Adolescents in AUDHigh and CUDHigh groups were slower in learning to select optimal instrumental cues relative to AUD‐CUDLow adolescents. The relatively fast learning observed for AUD‐CUDLow adolescents coincided with stronger functional connectivity between striatal and frontoparietal regions during early relative to later periods of task experience, whereas the slower learning for the CUDHigh group coincided with the opposite pattern. The AUDHigh group not only exhibited slower learning but also produced more instrumental choice errors relative to AUD‐CUDLow adolescents. For the AUDHigh group, Bayesian analyses evidenced moderate support for no experience‐related changes in striatal–frontoparietal connectivity strength during the task. Findings suggest that adolescent cannabis use is related to slowed instrumental learning and delays in peak functional connectivity strength between the striatal–frontoparietal regions that support this learning, whereas adolescent alcohol use may be more closely linked to broader impairments in instrumental learning and a general depression of the neural circuits supporting it.