Multiscale multidimensional recurrence quantitative analysis for analysing MEG signals in patients with schizophrenia

Abstract

Schizophrenia is a very serious chronic disease with very high hazards. Its pathogenesis is still unclear, and searching for its potential biomarkers has always been a popular issue in the field of schizophrenia research. Nonlinear dynamic analysis of magnetoencephalogram (MEG) signals in patients with schizophrenia is helpful to solve this problem. To quantitatively analyse multiscale recurrence information of MEG signals in patients with schizophrenia, this investigation propose a novel approach termed the multiscale multidimensional recurrence quantitative analysis (MsMdRQA). We first employed two sets of model series, which were generated by Lorenz and Rössler systems, to test the effectiveness of MsMdRQA in nonlinear analysis and to analyse the effects of dimension. Then we applied MsMdRQA to analyse MEG signals in schizophrenia. The test results suggest that both the Lorenz system and the Rössler system have different recurrence states at different scales; therefore, they effectively reflect the internal structure information of the Lorenz system and the Rössler system. Furthermore, we found that the recurrence values of the MEG signals in patients with schizophrenia were significantly lower (p < 0.001) than those of healthy control subjects. Overall, MsMdRQA provides a better analysis method for exploring the nonlinear characteristics of complex systems with different scales.