Informatika i Ee Primeneniya [Informatics and its Applications]
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Impact factor

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Inform. Primen.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Informatika i Ee Primeneniya [Informatics and its Applications], 2020, Volume 14, Issue 1, Pages 40–47
DOI: https://doi.org/10.14357/19922264200106
(Mi ia643)
 

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
Full-text PDF (132 kB) Citations (2)
References:
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.
Funding agency Grant number
Russian Foundation for Basic Research 18-29-22096_мк
This research was partially supported by the Russian Foundation for Basic Research (project 18-29-22096).
Received: 14.11.2019
Document Type: Article
Language: Russian
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
Citation in format AMSBIB
\Bibitem{BryStuKov20}
\by D.~O.~Bryukhov, S.~A.~Stupnikov, D.~Yu.~Kovalev, I.~A.~Shanin
\paper Neurophysiology as~a~subject domain for~data intensive problem solving
\jour Inform. Primen.
\yr 2020
\vol 14
\issue 1
\pages 40--47
\mathnet{http://mi.mathnet.ru/ia643}
\crossref{https://doi.org/10.14357/19922264200106}
Linking options:
  • https://www.mathnet.ru/eng/ia643
  • https://www.mathnet.ru/eng/ia/v14/i1/p40
  • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Информатика и её применения
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024