Scale-free dynamics of microstate sequence in negative schizophrenia and depressive disorder

Abstract

ObjectiveNegative schizophrenia (NSZ) and depressive disorder (DE) have many clinical similarities (e.g., lack of energy, social withdrawal). The purpose of this study was to explore microstate (MS) and scale-free dynamics of microstate sequence (SFML) in NSZ patients, DE patients and healthy controls (HC). MethodsThe subjects included 30 NSZ patients, 32 DE patients and 34 age-matched healthy controls. A resting-state electroencephalogram (rsEEG) was recorded under two conditions: (1) resting state with eyes opened (EO) and (2) resting state with eyes closed (EC). First, rsEEG signals were filtered into 1–45 Hz. Then, MS analysis was performed using the Microstate EEGLAB toolbox. Finally, the SFML feature of the sequence, which was transformed from the MS label sequence, was extracted by the Hurst exponent (HE). ResultsThe rsEEG data of all subjects were clustered into six topographies. We could conclude that DE and NSZ patients show similar abnormalities in EO state. However, in the EC state, MS A, and B values were unique to NSZ patients, while DE patients had different values for MS C D and F. We also found a large correlation between these features and clinical information. In SFML, the Hurst exponent of the EO state might be more useful in assessing the characteristics of NSZ, while that of EC state can be used to understand these disorders with different random walk classifications. SignificanceThe methods are associated with the ability to dynamically change of brain and information processing system. The MS and SFML of the EO state can be used to reflect the similar abnormalities of NSZ and DE patients. We recommend the EC state as the appropriate state to study the difference between the disorders. By combing the two states and these method, we can learn and study more similarities and differences between NSZ and DE.