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      Abnormal Entropy Modulation of the EEG Signal in Patients With Schizophrenia During the Auditory Paired-Stimulus Paradigm

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          Abstract

          The complexity change in brain activity in schizophrenia is an interesting topic clinically. Schizophrenia patients exhibit abnormal task-related modulation of complexity, following entropy of electroencephalogram (EEG) analysis. However, complexity modulation in schizophrenia patients during the sensory gating (SG) task, remains unknown. In this study, the classical auditory paired-stimulus paradigm was introduced to investigate SG, and EEG data were recorded from 55 normal controls and 61 schizophrenia patients. Fuzzy entropy (FuzzyEn) was used to explore the complexity of brain activity under the conditions of baseline (BL) and the auditory paired-stimulus paradigm (S1 and S2). Generally, schizophrenia patients showed significantly higher FuzzyEn values in the frontal and occipital regions of interest (ROIs). Relative to the BL condition, the normalized values of FuzzyEn of normal controls were decreased greatly in condition S1 and showed less variance in condition S2. Schizophrenia patients showed a smaller decrease in the normalized values in condition S1. Moreover, schizophrenia patients showed significant diminution in the suppression ratios of FuzzyEn, attributed to the higher FuzzyEn values in condition S1. These results suggested that entropy modulation during the process of sensory information and SG was obvious in normal controls and significantly deficient in schizophrenia patients. Additionally, the FuzzyEn values measured in the frontal ROI were positively correlated with positive scores of Positive and Negative Syndrome Scale (PANSS), indicating that frontal entropy was a potential indicator in evaluating the clinical symptoms. However, negative associations were found between the FuzzyEn values of occipital ROIs and general and total scores of PANSS, likely reflecting the compensation effect in visual processing. Thus, our findings provided a deeper understanding of the deficits in sensory information processing and SG, which contribute to cognitive deficits and symptoms in patients with schizophrenia.

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          Most cited references57

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          What does the PANSS mean?

          Despite the frequent use of the Positive and Negative Syndrome Scale (PANSS) for rating the symptoms of schizophrenia, the clinical meaning of its total score and of the cut-offs that are used to define treatment response (e.g. at least 20% or 50% reduction of the baseline score) are as yet unclear. We therefore compared the PANSS with simultaneous ratings of Clinical Global Impressions (CGI). PANSS and CGI ratings at baseline (n = 4091), and after one, two, four and six weeks of treatment taken from a pooled database of seven pivotal, multi-center antipsychotic drug trials on olanzapine or amisulpride in patients with exacerbations of schizophrenia were compared using equipercentile linking. Being considered "mildly ill" according to the CGI approximately corresponded to a PANSS total score of 58, "moderately ill" to a PANSS of 75, "markedly ill" to a PANSS of 95 and severely ill to a PANSS of 116. To be "minimally improved" according to the CGI score was associated with a mean percentage PANSS reduction of 19%, 23%, 26% and 28% at weeks 1, 2, 4 and 6, respectively. The corresponding figures for a CGI rating "much improved" were 40%, 45%, 51% and 53%. The results provide a better framework for understanding the clinical meaning of the PANSS total score in drug trials of schizophrenia patients with acute exacerbations. Such studies may ideally use at least a 50% reduction from baseline cut-off to define response rather than lower thresholds. In treatment resistant populations, however, even a small improvement can be important, so that a 25% cut-off might be appropriate.
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            Characterization of surface EMG signal based on fuzzy entropy.

            Fuzzy entropy (FuzzyEn), a new measure of time series regularity, was proposed and applied to the characterization of surface electromyography (EMG) signals. Similar to the two existing related measures ApEn and SampEn, FuzzyEn is the negative natural logarithm of the conditional probability that two vectors similar for m points remain similar for the next m + 1 points. Importing the concept of fuzzy sets, vectors' similarity is fuzzily defined in FuzzyEn on the basis of exponential function and their shapes. Besides possessing the good properties of SampEn superior to ApEn, FuzzyEn also succeeds in giving the entropy definition in the case of small parameters. Its performance on characterizing surface EMG signals, as well as independent, identically distributed (i.i.d.) random numbers and periodical sinusoidal signals, shows that FuzzyEn can more efficiently measure the regularity of time series. The method introduced here can also be applied to other noisy physiological signals with relatively short datasets.
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              Sensorimotor gating and schizophrenia. Human and animal model studies.

              Human and animal model studies of sensorimotor gating allow us to understand the functional significance of attentional abnormalities and monoaminergic alterations in patients with schizophrenic disorders. Clinically, schizophrenic patients report oversensitivity to sensory stimulation that theoretically correlates with stimulus overload and leads to cognitive fragmentation. Paradigms using cortical event-related potentials and the prepulse inhibition of startle responses show that schizophrenic patients also have impaired central nervous system inhibition (sensorimotor gating). Animal model studies demonstrate that increased systemic aminergic activity and increased nucleus accumbens dopamine tone causes sensorimotor gating failure, similar to that seen in schizophrenic patients. The time course of the observed schizophrenic and animal model deficits is compatible with the "temporal map" of monoaminergic neuron functions (le, several hundred milliseconds). Studies of sensorimotor gating allow investigators to comment on the spatial and temporal mapping of neurons, trait and state deficits, and vulnerability factors in the schizophrenic spectrum of disorders. By translating attentional theories into testable hypotheses, the neurobiology of schizophrenic disorders becomes clearer.
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                Author and article information

                Contributors
                Journal
                Front Neuroinform
                Front Neuroinform
                Front. Neuroinform.
                Frontiers in Neuroinformatics
                Frontiers Media S.A.
                1662-5196
                19 February 2019
                2019
                : 13
                : 4
                Affiliations
                [1] 1College of Information and Computer, Taiyuan University of Technology , Taiyuan, China
                [2] 2Translational Medicine Research Center Shanxi Medical University, Taiyuan, China
                [3] 3Psychiatry Research Center, Beijing Huilongguan Hospital, Peking University , Beijing, China
                Author notes

                Edited by: Tianyi Yan, Beijing Institute of Technology, China

                Reviewed by: Zehong Cao, University of Technology Sydney, Australia; Peng Xu, University of Electronic Science and Technology of China, China

                *Correspondence: Bin Wang wangbin01@ 123456tyut.edu.cn
                Article
                10.3389/fninf.2019.00004
                6390065
                30837859
                f512abc3-0264-463d-9472-8be5c1d604b1
                Copyright © 2019 Xiang, Tian, Niu, Yan, Li, Cao, Guo, Cui, Cui, Tan and Wang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 16 October 2018
                : 22 January 2019
                Page count
                Figures: 6, Tables: 2, Equations: 8, References: 65, Pages: 11, Words: 8168
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 61741212
                Award ID: 61876124
                Award ID: 61873178
                Funded by: Natural Science Foundation of Shanxi Province 10.13039/501100004480
                Award ID: 2015021090
                Award ID: 201601D202042
                Award ID: 201801D121135
                Categories
                Neuroscience
                Original Research

                Neurosciences
                schizophrenia,electroencephalogram,fuzzy entropy,sensory gating,complexity
                Neurosciences
                schizophrenia, electroencephalogram, fuzzy entropy, sensory gating, complexity

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