Analysis of functional MRI signal complexity based on permutation fuzzy entropy in bipolar disorder

Abstract

Bipolar disorder is a manifestation of an emotional disease and is associated with emotional and cognitive dysfunction. The entropy-based method has been widely used to study the complexity of resting-state functional MRI (rs-fMRI) signals in mental diseases; however, alterations in the brain rs-fMRI signal complexities in bipolar disorder patients remain unclear, and previously used entropy methods are sensitive to noise. Here, we performed a work using permutation fuzzy entropy (PFEN), which has better performance than previously used methods, to analyze the brain complexity of bipolar disorder patients. Based on PFEN research, we obtained brain entropy maps of 49 bipolar disorder patients and 49 normal control, extracted the regions of interest to analyze the complexity of abnormal brain regions and further analyzed the correlation between the PFEN values of abnormal brain regions and the clinical measurement scores. Compared with the values in the normal control group, we found that significantly increased PFEN values mainly appeared in the middle temporal gyrus, angular gyrus, superior occipital gyrus and medial superior frontal gyrus, and the decreased PFEN values were found in the inferior temporal gyrus in bipolar disorder patients. In addition, the PFEN values of the angular gyrus was significantly negatively correlated with clinical scores. These findings improve our understanding of the pathophysiology of bipolar disorder patients.