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Purpose: Minimal hepatic encephalopathy (MHE) is characterized by mild neuropsychological and neurophysiological alterations that are not detectable by routine clinical examination. Abnormal brain activity (in terms of the amplitude of low-frequency fluctuation (ALFF) has been observed in MHE patients. However, little is known concerning temporal dynamics of intrinsic brain activity. The present study aimed to investigate the abnormal dynamics of brain activity (dynamic ALFF; dALFF) and static measures [static ALFF; (sALFF)] in MHE patients and to strive for a reliable imaging neuromarkers for distinguishing MHE patients from cirrhosis patients. In addition, the present study also investigated whether intrinsic brain activity predicted the severity of liver damage. Methods: Thirty-four cirrhosis patients with MHE, 28 cirrhosis patients without MHE, and 33 age-, sex-, and education-matched healthy controls (HCs) underwent resting-state magnetic resonance imaging (rs-fMRI). dALFF was estimated by combining the ALFF method with the sliding-window method, in which temporal variability was quantized over the whole-scan timepoints and then compared among the three groups. Additionally, dALFF, sALFF and both two features were utilized as classification features in a support vector machine (SVM) to distinguish MHE patients from cirrhosis patients. The severity of liver damage was reflected by the Child-Pugh score. dALFF, sALFF and both two features were used to predict Child-Pugh scores in MHE patients using a general linear model. Results: Compared with HCs, MHE patients showed significantly increased dALFF in the left inferior occipital gyrus, right middle occipital gyrus, and right insula; increased dALFF was also observed in the right posterior lobe of the cerebellum (CPL) and right thalamus. Compared with HCs, noMHE patients exhibited decreased dALFF in the right precuneus. In contrast, compared with noMHE patients, MHE patients showed increased dALFF in the right precuneus, right superior frontal gyrus, and right superior occipital gyrus. Furthermore, the increased dALFF values in the left precuneus were positively associated with poor digit-symbol test (DST) scores (r = 0.356, p = 0.038); however, dALFF in the right inferior temporal gyrus (ITG) was negatively associated with the number connection test-A (NCT-A) scores (r = -0.784, p = 0.000). A significant positive correlation was found between dALFF in the left inferior occipital gyrus (IOG) and high blood ammonia levels (r = 0.424, p = 0.012). Notably, dALFF values yielded a higher classification accuracy than sALFF values in distinguishing MHE patients from cirrhosis patients. Importantly, the dALFF values predicted the Child-Pugh score (r = 0.140, p = 0.030), whereas sALFF values did not in the current dataset. Combining two features had high accuracy in classification in distinguishing MHE patients from cirrhotic patients and yielded prediction in the severity of liver damage. Conclusion: These findings suggest that combining dALFF and sALFF features is a useful neuromarkers for distinguishing MHE patients from cirrhosis patients and highlights the important role of dALFF feature in predicting the severity of liver damage in MHE. [ABSTRACT FROM AUTHOR]

Background Abnormal decision-making processes have been observed in patients with major depressive disorder (MDD). However, it is unresolved whether MDD patients show abnormalities in decision making in a social interaction context, in which decisions have actual influences on both the self-interests of the decision makers per se and those of their partners. Methods Using a well-studied ultimatum game (UG), which is frequently used to investigate social interaction behavior, we examined whether MDD can be associated with abnormalities in social decision-making behavior by comparing the acceptance rates of MDD patients (N = 14) with those of normal controls (N = 19). Results The acceptance rates of the patients were lower than those of the normal controls. Additionally, unfair proposals were accepted at similar rates from computer partners and human partners in the MDD patients, unlike the acceptance rates in the normal controls, who were able to discriminatively treat unfair proposals from computer partners and human partners. Conclusions Depressed patients show abnormal decision-making behavior in a social interaction context. Several possible explanations, such as increased sensitivity to fairness, negative emotional state and disturbed affective cognition, have been proposed to account for the abnormal social decision-making behavior in patients with MDD. This aberrant social decision-making behavior may provide a new perspective in the search to find biomarkers for the diagnosis and prognosis of MDD. [ABSTRACT FROM AUTHOR]