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Permutation Entropy for the Characterisation of Brain Activity Recorded with Magnetoencephalograms in Healthy Ageing

机译:磁熵图记录的健康衰老中脑活动特征的置换熵

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摘要

The characterisation of healthy ageing of the brain could help create a fingerprint of normal ageing that might assist in the early diagnosis of neurodegenerative conditions. This study examined changes in resting state MEG permutation entropy due to age and gender in a sample of 220 healthy participants (98 males and 122 females, ages ranging between 7 and 84). Entropy was quantified using normalised permutation entropy and modified permutation entropy, with an embedding dimension of 5 and a lag of 1 as the input parameters for both algorithms. Effects of age were observed over the 5 regions of the brain i.e. anterior, central, posterior, and left and right lateral, with the anterior and central regions containing the highest permutation entropy. Statistically significant differences due to age were observed in the different brain regions for both genders, with the evolutions described using the fitting of polynomial regressions. Nevertheless, no significant differences between the genders were observed across all ages. These results suggest that the evolution of entropy in the background brain activity, quantified with permutation entropy algorithms, might be considered an alternative illustration of a ‘nominal’ physiological rhythm.
机译:大脑健康衰老的特征可以帮助创建正常衰老的指纹,这可能有助于神经退行性疾病的早期诊断。这项研究检查了220位健康参与者(98位男性和122位女性,年龄介于7至84岁)的样本中由于年龄和性别导致的静止状态MEG排列熵的变化。使用归一化置换熵和修正置换熵对熵进行量化,其中嵌入维数为5,滞后量为1,这两种算法的输入参数。在大脑的5个区域(即前,中,后,左,右外侧)观察到了年龄的影响,其中前和中部区域具有最高的排列熵。在男女不同的大脑区域中,观察到了由于年龄引起的统计学显着差异,并且使用多项式回归拟合描述了进化。然而,所有年龄段的性别之间都没有发现显着差异。这些结果表明,用置换熵算法量化的背景大脑活动中的熵演化可能被视为“标称”生理节律的另一种说明。

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