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Rationale: Both attention deficit-/hyperactivity disorder (ADHD) and alcohol use disorder (AUD) are accompanied by deficits in response inhibition. Furthermore, the prevalence of comorbidity of ADHD and AUD is high. However, there is a lack of research on whether the same neuronal subprocesses of inhibition (i.e., interference inhibition, action withholding and action cancellation) exhibit deficits in both psychiatric disorders. Methods: We examined these three neural subprocesses of response inhibition in patient groups and healthy controls: non-medicated individuals with ADHD (ADHD; N = 16), recently detoxified and abstinent individuals with alcohol use disorder (AUD; N = 15), and healthy controls (HC; N = 15). A hybrid response inhibition task covering interference inhibition, action withholding, and action cancellation was applied using a 3T functional magnetic resonance imaging (fMRI). Results: Individuals with ADHD showed an overall stronger hypoactivation in attention related brain areas compared to AUD or HC during action withholding. Further, this hypoactivation was more accentuated during action cancellation. Individuals with AUD recruited a broader network, including the striatum, compared to HC during action withholding. During action cancellation, however, they showed hypoactivation in motor regions. Additionally, specific neural activation profiles regarding group and subprocess became apparent. Conclusions: Even though deficits in response inhibition are related to both ADHD and AUD, neural activation and recruited networks during response inhibition differ regarding both neuronal subprocesses and examined groups. While a replication of this study is needed in a larger sample, the results suggest that tasks have to be carefully selected when examining neural activation patterns of response inhibition either in research on various psychiatric disorders or transdiagnostic questions.
Rationale: Attention deficit/hyperactivity disorder (ADHD) is common in alcohol use disorder (AUD). Continuous performance tests (CPTs) allow to measure ADHD related deficits in a laboratory setting. Most studies on this topic focused on CPTs measuring inattention or impulsivity, disregarding hyperactivity as one of the core symptoms of ADHD.
Methods: We examined N = 47 in three groups (ADHD N = 19; AUD N = 16; ADHD + AUD N = 12) with questionnaires on ADHD core symptoms, executive functioning (EF), mind wandering, and quality of life (QoL). N = 46 (ADHD N = 16; AUD N = 16; ADHD + AUD N = 14) were examined with a CPT (QbTest®) that also measures motor activity objectively.
Results: Inattention and impulsivity were significantly increased in AUD vs. ADHD and in AUD vs. ADHD + AUD. Hyperactivity was significantly higher in ADHD + AUD vs. ADHD and ADHD + AUD vs. AUD, but not in ADHD vs. AUD. EF was lower in both ADHD groups vs. AUD. Mind wandering was increased in both ADHD groups vs. AUD. QoL was significantly lower in ADHD + AUD compared to AUD. In contrast, results of the QbTest were not significantly different between groups.
Conclusion: Questionnaires are more useful in assessing ADHD core symptoms than the QbTest®. Hyperactivity appears to be a relevant symptom in ADHD + AUD, suggesting a possible pathway from ADHD to AUD. The lower QoL in ADHD + AUD emphasizes the need for routine screening, diagnostic procedures and treatment strategies for this patient group.
Background: A link between attention-deficit/hyperactivity disorder (ADHD) and alcohol use disorder (AUD) has been widely demonstrated. In this study, we used neuroimaging to investigate the connectivity traits that may contribute to the comorbidity of these disorders.
Methods: The study included an AUD group (N = 18), an ADHD group (N = 17), a group with AUD + ADHD comorbidity (N = 12) and a control group (N = 18). We used resting-state functional connectivity in a seed-based approach in the default mode networks, the dorsal attention network, and the salience network.
Results: Within the default mode networks, all affected groups shared greater connectivity toward the temporal gyrus when compared to the control group. Regarding the dorsal attention network, the Brodmann area 6 presented greater connectivity for each affected group in comparison with the control group, displaying the strongest aberrations in the AUD + ADHD group. In the salience network, the prefrontal cortex showed decreased connectivity in each affected group compared to the control group.
Conclusions: Despite the small and unequal sample sizes, our findings show evidence of common neurobiological alterations in AUD and ADHD, supporting the hypothesis that ADHD could be a risk factor for the development of AUD. The results highlight the importance of an early ADHD diagnosis and treatment to reduce the risk of a subsequent AUD.