Wavelet Entropy Measure to Quantify Information Transmission in Human Cerebral Cortex

R. Narayanam, Y. Ono, H. Dajani
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引用次数: 1

Abstract

The electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of brain dynamics. These current waveforms were decomposed into different approximation and details using the wavelet analysis. The wavelet entropy of such decompositions is analyzed, reaching a successful methodology for information transmission. The suggested approach is tested using different event-related potential conditions, and different types of cognitive disorders have proven to be successful in the identification of the transmission of information.
小波熵量化人脑皮层信息传递
脑电波分析多为定性分析,发展新的定量分析方法对限制脑电波研究的主观性至关重要。当这些方法与直观的物理概念紧密相关,从而更好地理解大脑动力学时,这些方法尤其富有成效。利用小波分析将这些电流波形分解成不同的近似和细节。对这种分解的小波熵进行了分析,得出了一种成功的信息传递方法。建议的方法使用不同的事件相关潜在条件进行了测试,不同类型的认知障碍已被证明在识别信息传输方面是成功的。
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来源期刊
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发文量
33
审稿时长
16 weeks
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