Decreased nonlinear complexity and chaos during sleep in first episode schizophrenia: a preliminary report

Schizophrenia is characterized by disturbed sleep architecture. It has been thought that sleep abnormalities may underlie information processing deficits associated with this disorder. Nonlinear analyses of sleep data can provide valuable information on sleep characteristics that may be relevant to the functions of sleep. This study examined the predictability and nonlinear complexity of sleep EEG time series in two EEG channels (C4 and F4) using measures of nonlinearity, such as symbolic dynamics and the largest Lyapunov exponent (LLE) in schizophrenia. A series of antipsychotic naive patients with first episode of schizophrenia or schizoaffective disorder and age-matched healthy controls were studied during awake period, stage 1/2, slow wave sleep (stage 3/4) and rapid eye movement (REM) sleep. Nonlinearity scores were significantly lower during awake stage in patients compared to controls suggesting that there may be a diminished interplay between various parameters for the genesis of waking EEG. Symbolic dynamics and LLE were significantly lower in patients during REM compared to healthy controls, suggesting decreased nonlinear complexity of the EEG time series and diminished chaos in schizophrenia. Decreased nonlinear complexity was also correlated with neurocognitive deficits as assessed by the Wisconsin card sorting test. Diminished complexity of EEG time series during awake and REM sleep in patients with schizophrenia may underlie the impaired ability to process information in psychotic disorders such as schizophrenia.