Mapping the dynamics of idiographic network models to the network theory of psychopathology

Ising model only partially aligns with the network theory, as increased connectivity is related to both high and low symptom severity. In contrast, connectivity in the GVAR model is independent of symptom severity but instead reflects symptom variability over time. These findings demonstrate that the theoretical implications of network connectivity depend strongly on the chosen statistical model and its parameterization. Together, our results emphasize the need for systematic investigations that link theory to statistical models, and present stability landscapes as a useful tool to do so.