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首页> 外文期刊>Clinical EEG and neuroscience: official journal of the EEG and Clinical Neuroscience Society (ENCS) >Abnormalities of Alpha Activity in Frontocentral Region of the Brain as a Biomarker to Diagnose Adolescents With Bipolar Disorder
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Abnormalities of Alpha Activity in Frontocentral Region of the Brain as a Biomarker to Diagnose Adolescents With Bipolar Disorder

机译：大脑前端地区α活性的异常作为生物标志物，以诊断双相障碍的青少年

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Objectives. To investigate brain abnormalities in adolescents with new-onset bipolar disorder (BD) during acute hypomanic and depressive episodes using electroencephalogram (EEG) analysis and to derive a computer-based method for diagnosis of the disorder. Methods. EEG spectral power and entropy of 21 adolescents with BD (included 11 patients in the hypomanic episode and 10 patients in the depressive episode) and 18 healthy adolescents were compared. Moreover, using significant differences and K-nearest-neighbors (KNN) classifier, it was attempted to distinguish the BD adolescents from normal ones. Results. The BD adolescents had higher values of spectral power in all frequency bands, particularly in the frontocentral, mid-temporal, and right parietal regions. Also, spectral entropy had significantly increased in delta, alpha, and gamma frequency bands for BD. A high accuracy of 95.8% was achieved by all significant differences in the alpha band in discriminating adolescents with BD. The depressive state showed higher values of spectral power and entropy in low-frequency bands (delta and theta) compared to the hypomanic state. Conclusion. Based on BD symptoms, especially inattention, increased alpha power is a rational finding which is associated with thalamus dysfunction. Thus, it seems that EEG alpha oscillation is the main source of abnormality in BD. Furthermore, EEG slowing in the depressive episode is related to inhibition of electrical activity and reduced cognitive functions.
机译：目标。使用脑电图（EEG）分析在急性低调和抑郁发作期间探讨青少年患有新发病双极障碍（BD）的青少年脑异常，并导出基于计算机的诊断疾病的方法。方法。 BD的21个青少年的EEG谱功率和熵（包括11名患者在抑郁情节中的10名患者）和18名健康青少年。此外，使用显着的差异和k离最近邻居（KNN）分类器，试图将BD青少年与正常的分类器区分开来。结果。 BD青少年在所有频带中具有较高的谱功率值，特别是在船长，中间时，中间和右翼间区域。此外，SpeltaLcopt在BD的Delta，alpha和伽马频带中显着增加。通过BD鉴别青少年的α带中的所有显着差异，实现了95.8％的高精度。与低副状态相比，抑郁状态显示出低频带（Delta和Theta）的光谱功率和熵值更高。结论。基于BD症状，特别注意，增加的alpha权力是与丘脑功能障碍相关的理性发现。因此，脑电图α振荡似乎是BD中异常的主要来源。此外，抑郁发作中的EEG减速与电活性的抑制和减少的认知功能有关。

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