Bipolar disorder is a mental disorder characterized by manic episodes of elevated mood and overactivity, interspersed with periods of depression. Approximately 1% of adults in the general population have a lifetime prevalence of bipolar disorder. This is a chronic and lifelong condition often exacerbated by mood variation leading to further chronic impairment. Our research in this area uses mathematical tools to understand and characterize this mood variability.
We are interested in exploring how we can use statistical time series methods and non-linear mathematical models to characterize variability in mood fluctuations. Non-linear time series analysis provides a robust approach for describing the patterns of mood variability between different groups of patients and, more excitingly, for describing individual patient profiles.
Bonsall, M.B., J.R. Geddes, G.M. Goodwin and E.A. Holmes (2015) Bipolar disorder dynamics: affective instabilities, relaxation oscillators and noise. Journal of the Royal Society Interface, 12, 20150670. http://dx.doi.org/10.1098/rsif.2015.0670
Bonsall, M.B., S.M.A. Wallace-Hadrill, J.R. Geddes, G.M. Goodwin and E.A. Holmes (2012) Non-linear time series approaches in characterising mood stability and mood instability in bipolar disorder. Proceedings of the Royal Society Series B., 279, 916-924. http://dx.doi.org/10.1098/rspb.2011.1246
Holmes, E.A, C. Deeprose, C.G. Fairburn, S.M.A. Wallace-Hadrill, M. B. Bonsall, J.R. Geddes and G. M. Goodwin (2011) Mood stability versus mood instability in bipolar disorder: a possible role for emotional mental imagery. Behavioural Research and Therapy, 49, 707-713. http://dx.doi.org/10.1016/j.brat.2011.06.008