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This article is cited in 2 scientific papers (total in 2 papers)
Neurophysiology as a subject domain for data intensive problem solving
D. O. Bryukhov, S. A. Stupnikov, D. Yu. Kovalev, I. A. Shanin Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Abstract:
The goal of this survey is to analyze neurophysiology as a data intensive domain. Nowadays, the number of researches on the human brain is increasing. International projects and researches are aimed at improvement of the understanding of the human brain function. The amount of data obtained in typical laboratories in the field of neurophysiology is growing exponentially. The data are represented using a large number of various formats. This requires creation of infrastructures, databases, and websites that provide unified access to data and support the exchange of data between researchers all over the world. Specific methods and tools forming the field of neuroinformatics (that is, an intersection of neurophysiology and computer science) are used to analyze collected data and to solve neurophysiological problems. These methods include, in particular, statistical analysis, machine learning, and neural networks.
Keywords:
neurophysiology, neurophysiological resources, neuroinformatics, data intensive research, analysis of neurophysiological data.
Received: 14.11.2019
Citation:
D. O. Bryukhov, S. A. Stupnikov, D. Yu. Kovalev, I. A. Shanin, “Neurophysiology as a subject domain for data intensive problem solving”, Inform. Primen., 14:1 (2020), 40–47
Linking options:
https://www.mathnet.ru/eng/ia643 https://www.mathnet.ru/eng/ia/v14/i1/p40
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