Gottschalk et al. ([1995]) analysed daily mood records from 7 patients with bipolar disorders and 28 normal controls. The 7 patients with bipolar disorders all had a rapid cycling course; that is, they had all experienced at least 4 affective episodes in the previous 12 months. Patients kept mood records on a daily basis (controls on a twice-daily basis) by marking mood on an analogue scale each evening to reflect average mood over the previous 24 h. The selected participants kept records for a period of 1 to 2.5 years.
Out of the seven patients, six had correlation dimensions which converged at a value less than five, while for controls, the convergence occurred no lower than eight. Equivalent surrogate time series did not show convergence with dimension. From these results, the authors inferred the presence of chaotic dynamics in the time series from patients with bipolar disorder. They noted the unreliability of correlation dimension as an indicator of chaos, but adduced the results from time plots, spectral analysis and phase-space reconstruction to demonstrate the difference from controls. The claim was challenged by Krystal et al. ([1998]) who pointed out that the power-law behaviour is not consistent with chaotic dynamics. In their reply (Gottschalk et al. [1998]), Gottschalk et al. commented that the spectra could equally be fitted by an exponential model. The authors did not investigate the Lyapunov spectrum, which can provide evidence of chaotic dynamics. Their claim of deterministic chaos rested mainly on the convergence of correlation dimension and, as they acknowledged, this is not definitive (McSharry [2005]). Their change of model for spectral decay weakened the original claims further - the evidence does not support nor deny it.