Over the past 30 years, investigators have used nonlinear and so-called chaos theory-based techniques to examine a wide range of phenomena ranging from electroencephalogram and cardiac rate and rhythm analyses to stock market and weather predictions. Psychiatric neuroscientists are now beginning to apply nonlinear methods to mental disorders such as schizophrenia. These applications are relevant from the level of complex genetic architecture and calcium channel dynamics to the symptomatic, behavioral, and functional outcome of schizophrenia. The key point of this surge of interest is distinguishing complex, nonlinear but lawfully mediated systems from truly random systems. The application of these methods to studies in schizophrenia has yielded findings that are consistent with the general hypothesis that an altered sequential or temporal architecture is a key feature of this disorder. Specifically, we propose that the temporal architecture of schizophrenia is characterized by bursts of complex, nonlinear phenomena alternating with truly random events. Analyzing these patterns of molecular (e.g., calcium channel activity) to molar (e.g., symptom level) phenomena via nonlinear systems methods can provide new approaches to understanding complex temporal and sequential shifts in neural substrate activity, pathophysiology, and the course and treatment and outcome of schizophrenia.