Analysis of oscillatory pattern based on neural network and its applications

Neural oscillatory phenomenon generally exists in the nervous system through a dynamic form. It plays a very important role in the brain, especially in the higher cognitive activities, such as information processing, transfer and integration, consolidating memory and so on. Furthermore, the specific...

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Bibliographic Details
Published inSheng li hsüeh pao Vol. 67; no. 2; p. 143
Main Authors Li, Qun, Cheng, Ning, Zhang, Tao
Format Journal Article
LanguageChinese
Published China 25.04.2015
Subjects
Brain - physiology
Cognition
Humans
Memory
Nerve Net - physiology
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Summary:Neural oscillatory phenomenon generally exists in the nervous system through a dynamic form. It plays a very important role in the brain, especially in the higher cognitive activities, such as information processing, transfer and integration, consolidating memory and so on. Furthermore, the specific activity pattern of neural oscillations is often associated with cognitive functions and their alterations. Accordingly, how to quantitatively analyze the pattern of neural oscillations becomes one of the fundamental issues in the computational neuroscience. In this review, we addressed a variety of analytic algorithms, which are commonly employed in our recent studies to investigate the issues of neurobiology and cognitive science. In addition, we tried to classify these analytic algorithms by distinguishing their different metrics, synchronization and coupling modes. Finally, multidimensional analytic algorithms for potential application have also been discussed.
ISSN:0371-0874