The network perspective on psychopathology suggests that mental disorders can be regarded as networks of elements that influence each other. In this study, we used network analysis to explore the temporal interactions of anxiety and depression symptoms at the level of day-to-day experiences and find potential explanatory pathways for their comorbidity. We collected intensive longitudinal data from a sample of undergraduate students and fitted a Multilevel Vector Autoregressive model on GAD and MDD DSM-5 symptoms. “Sad mood” and “Concentration difficulties” were responsible for the most connections between anxiety and depression symptoms and were also among the most central symptoms. It is possible that anxio-depressive comorbidity can be explained by the presence of “Sad mood” and “Concentration difficulties” and targeting these two symptoms in therapy can lead to beneficial effects in comorbid cases.