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Patients with schizophrenia frequently exhibit behavioral abnormalities associated with its pathological symptoms. Therefore, a quantitative evaluation of behavioral dynamics could contribute to objective diagnoses of schizophrenia. However, such an approach has not been fully established because of the absence of quantitative biobehavioral measures. Recently, we studied the dynamical properties of locomotor activity, specifically how resting and active periods are interwoven in daily life. We discovered universal statistical laws ("behavioral organization") and their alterations in patients with major depressive disorder. In this study, we evaluated behavioral organization of schizophrenic patients (n = 19) and healthy subjects (n = 11) using locomotor activity data, acquired by actigraphy, to investigate whether the laws could provide objective and quantitative measures for a possible diagnosis and assessment of symptoms. Specifically, we evaluated the cumulative distributions of resting and active periods, defined as the periods with physical activity counts successively below and above a predefined threshold, respectively. Here we report alterations in the laws governing resting and active periods; resting periods obeyed a power-law cumulative distribution with significantly lower parameter values (power-law scaling exponents), whereas active periods followed a stretched exponential distribution with significantly lower parameter values (stretching exponents), in patients. Our findings indicate enhanced persistency of both lower and higher locomotor activity periods in patients with schizophrenia, probably reflecting schizophrenic pathophysiology.
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