Multiscale ApEn and SampEn in Quantifying Nonlinear Complexity of Depressed MEG

Depression is a neurophysiological disorder with recurrent dysregulations of self-mental states. Multiscale Approximate entropy (ApEn) and Sample entropy (SampEn) are employed to characterize nonlinear complexity of Magnetoencephalography (MEG) of depressive patients in our contribution. SampEn shares similarities with ApEn while has better distinctions between the MEGs of depression patients and normal people. Test results prove that nonlinear complexity of the depressive MEG is lower than that of the normal subjects, indicating weaker response of depression patients to emotional stimuli, and the optimum discriminations between the depressive and healthy people lie in frontal lobe of brain which is related to emotional regulation. Our findings provide valuable information about depression, highlight the loss of nonlinear complexity in MEG of depressive patient and can be used as clinical diagnostic aids.