Abstract
Object: Brain entropy is a potential index in the diagnosis of mental diseases, but there are some differences in different brain entropy calculation, which may bring confusion and difficulties to the application of brain entropy. Based on the resting-state function magnetic resonance imaging (fMRI) we analyzed the differences of the three main brain entropy in the statistical significance, including approximate entropy (ApEn), sample entropy (SampEn) and fuzzy entropy (FuzzyEn), and studied the physiological reasons behind the difference through comparing their performance on obsessive-compulsive disorder (OCD) and the healthy control (HC).Method: We set patients with OCD as the experimental group and healthy subjects as the control group. The brain entropy of the OCD group and the HC are calculated, respectively, by voxel and AAL region. And then we analyzed the statistical differences of the three brain entropies between the patients and the control group. To compare the sensitivity and robustness of these three kinds of entropy, we also studied their performance by using certain signal mixed with noise.Result: Compare with the control group, almost the whole brain's ApEn and FuzzyEn of OCD are larger significantly. Besides, there are more brain regions with obvious differences when using ApEn comparing to using FuzzyEn. There was no statistical difference between the SampEn of OCD and HC.Conclusion: Brain entropy is a numerical index related to brain function and can be used as a supplementary biological index to evaluate brain state, which may be used as a reference for the diagnosis of mental illness. According to an analysis of certain signal mixed with noise, we conclude that FuzzyEn is more accurate considering sensitivity, stability and robustness of entropy.
Highlights
Entropy is a physical concept proposed by the German physicist Clausius in 1865, which is used to measure the complexity, randomness, or predictability of a dynamic process
Shi et al [4] found that there was a significant positive relationship between creativity and the brain entropy values of dorsolateral prefrontal cortex (DLPFC) and DACC brain functional areas, which are responsible for cognitive flexibility and inhibitory control
Song et al [5] found that brain entropy can be enhanced through caffeine intake, this study verifies the sensitivity of brain entropy to drug regulation, supports that brain entropy can sensitively reflect the neural effects of caffeine, and supports that brain entropy can be used as an indicator to detect changes in brain activity
Summary
Entropy is a physical concept proposed by the German physicist Clausius in 1865, which is used to measure the complexity, randomness, or predictability of a dynamic process. Other researchers reported changes in entropy in brain conditions such as normal aging [6,7,8,9], multiple sclerosis [10], schizophrenia [11], Alzheimer’s disease [12], and Attention deficit hyperactivity disorder [13]. These studies show that brain entropy can reflect information of the brain activity, and can be used as a tool for diagnosis and treatment of brain diseases, and can provide a potential way to explore complex brain function. The accuracy and sensitivity of the three different calculation methods in measuring the degree of brain dysfunction are not clear
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