Abstract
Mood instability is characteristic of bipolar (BD) and borderline personality (BPD) disorders. However, the optimal method(s) for measuring mood instability is not clear. One approach is to develop a generative model describing why mood changes over time and estimate the states of the model using an ideal Bayesian observer. We describe such a model here and use it to infer the cause of mood instability in BD and BPD patients as well as characterising the effect of lithium on mood instability.
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