本文選題：血氧水平依賴功能磁共振成像信號 + 模糊近似熵�。� 參考：《物理學(xué)報(bào)》2016年21期

【摘要】：提出采用模糊近似熵的方法對功能磁共振成像(functional magnetic resonance imaging,fMRI)復(fù)雜度量化分析,并與樣本熵進(jìn)行比較.采用的22個成年抑郁癥患者中,11位男性,年齡在18—65歲之間.我們期望測量的靜息態(tài)fMRI信號復(fù)雜度與Goldberger/Lipsitz模型一致,越健康、越穩(wěn)健其生理表現(xiàn)的復(fù)雜度越大,且復(fù)雜度隨年齡的增大而降低.全腦平均模糊近似熵與年齡之間差異性顯著(r=-0.512,p0.001).相比之下,樣本熵與年齡之間差異性不顯著(r=-0.102,p=0.482).模糊近似熵同樣與年齡相關(guān)腦區(qū)(額葉、頂葉、邊緣系統(tǒng)、顳葉、小腦頂葉)之間差異性顯著(p0.05),樣本熵與年齡相關(guān)腦區(qū)之間差異性不顯著性.這些結(jié)果與Goldberger/Lipsitz模型一致,說明采用模糊近似熵分析fMRI數(shù)據(jù)復(fù)雜度是一個有效的新方法.
[Abstract]:A fuzzy approximate entropy method is proposed to quantify the complexity of functional magnetic resonance imagingfMRI in functional magnetic resonance imaging (fMRI), and to compare it with the sample entropy. Of the 22 adults with depression, 11 were men aged 18-65 years. We expect the measured fMRI signal complexity to be consistent with that of the Goldberger/Lipsitz model. The healthier the measurement is, the more robust the complexity of physiological performance is, and the lower the complexity is with the increase of age. The difference between the average fuzzy approximate entropy and the age of the whole brain is significant. In contrast, there was no significant difference between sample entropy and age. The difference between fuzzy approximate entropy and age-related brain regions (frontal lobe, parietal lobe, marginal system, temporal lobe, cerebellar parietal lobe) was significant (p 0.05), but there was no significant difference between sample entropy and age-related brain area. These results are consistent with the Goldberger/Lipsitz model, which shows that the fuzzy approximate entropy is an effective new method to analyze the complexity of fMRI data.
【作者單位】： 北京工業(yè)大學(xué)國際WIC研究院;前橋工業(yè)大學(xué)生命科學(xué)與信息工程系;首都醫(yī)科大學(xué)安定醫(yī)院;
【基金】：國家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃(批準(zhǔn)號:2014CB744600) 國家自然科學(xué)基金(批準(zhǔn)號:61272345,61105118)資助的課題~~
【分類號】：R445.2;R749.4

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