The neurovisceral integration model proposes that people low in heart rate variability (HRV) are in a state with strong connections between symptoms of anxiety and depression. So far studies providing support for this hypothesis have relied on classifications or sum scores of a diverse range of symptoms, ignoring observations that anxiety and depression symptoms dynamically influence each other. Here we used network analyses to study if HRV moderates characteristics (density, structure, centrality indices) of network models of generalized anxiety disorder and depression symptoms. We used data (N = 495) from the Dresden Burnout Study where resting levels of HRV were obtained as well as self-reported symptoms of generalized anxiety and depression. Results showed that HRV did not moderate the density and structure of the overall symptom networks. Exploration of the centrality indices suggested that restlessness was a more central node for people low in HRV, a result that remains to be confirmed in larger samples. These findings demonstrate how a network perspective may aid in better understanding the complex relation between symptoms of psychopathology and physiological status.