• Irina Knyazeva
  • Vyacheslav Orlov
  • Vadim Ushakov
  • Nikolay Makarenko
  • Boris Velichkovsky

This work aimed at comparing two different approaches (classical general linear model based on the Bayesian approach and the method of algebraic topology) for fMRI data processing in a simple motor task. Subjects imposes block paradigm, consisting of three identical blocks. The duration of each block was 40 s (20 s of rest and 20 s of right hand fingers busting). To obtain statistically significant results were carried out 20 sessions of experiment. The results obtained by both methods were very close to each other, but correspondence between statistically significant changes in BOLD-signal was not quite complete. TDA (topologic data analyses) allocated additional voxels in Post central gyrus right. This region could be revealed with the changing in the level of confidence in the GLM model, but with this lower level of confidence too much additional voxels appeared. Combination of two approaches could be used for verification of results.

Original languageEnglish
Title of host publicationBiologically Inspired Cognitive Architectures BICA for Young Scientists - Proceedings of the 1st International Early Research Career Enhancement School, FIERCES 2016
PublisherSpringer Nature
Pages107-113
Number of pages7
Volume449
ISBN (Print)9783319325538
DOIs
StatePublished - 2016
Externally publishedYes

Publication series

NameAdvances in Intelligent Systems and Computing
Volume449
ISSN (Print)2194-5357

    Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

    Research areas

  • Activation detection, FMRI, General linear model, Time series analysis, Topological data analysis

ID: 9326384