[Neural networks in addiction].

Background: Substance use disorders (SUD) are among the most prevalent psychiatric disorders, with high illness costs. A disturbed balance between frontostriatal and stress brain circuitry influences the development of SUD, its continuation, and vulnerability for relapse.

Aim: To provide a concise overview of neural networks in SUD, and discuss implications for clinical practice.

Method: Narrative literature review on neurobiological mechanisms of neural networks in substance use disorders.

Results: Changes in frontostriatal circuitry play an important role for sensitivity to substance-related rewards, and can lead to loss of control over substance use. On the other hand, the use of substances affects the brain’s stress system, which affects frontostriatal network functioning. Substance use can activate stress circuitry in the brain, which can lead to an increase in use or relapse. The level at which neural network functioning is affected can differ highly between persons with SUD, and is dependent on the SUD stage and the presence of other psychiatric comorbidity.

Conclusion: Improved understanding of neural networks involved in SUD can lead to the development of new and more personalized treatment- and prevention strategies. Insights in neural networks also provide a transdiagnostic view from which to understand the phenomenological overlap between psychiatric disorders and frequent comorbidity.