Pseudo-real fMRI data generation and its utility toward quantitative evaluation of analytical methods

Dong Youl Kim, Jong-Hwan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Functional magnetic resonance imaging (fMRI) modality has been widely employed to measure neuronal activations of the human brain using such as a model-based general linear model (GLM) and data-driven independent component analysis (ICA) approaches. In this study, we were motivated to investigate the performance of two popular methods with a hypothesis that these methods would have advantages and disadvantages depending on the variability of the fMRI data across subjects in both temporal and spatial domain. To quantitatively evaluate two methods, the pseudo-real fMRI data were generated by combining the decomposed non-neuronal components estimated from real resting-state fMRI data and artificially generated neuronal components with varying degree of temporal and spatial pattern variability of task related activation patterns in an individual level. Using the pseudo-real fMRI data, the assessment of each method was conducted by comparing the estimated activations to reference neuronal activations. Our results indicated that the degree of spatial overlap size across subjects and degree of temporal pattern variability would be important factor to choose a proper analytical method.

Original languageEnglish
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages1095-1099
Number of pages5
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012 - Seoul, Korea, Republic of
Duration: 2012 Oct 142012 Oct 17

Other

Other2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
CountryKorea, Republic of
CitySeoul
Period12/10/1412/10/17

Keywords

  • Functional magnetic resonance imaging
  • general linear model
  • group inference
  • independent component analysis
  • semi-artificial fMRI

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

Fingerprint Dive into the research topics of 'Pseudo-real fMRI data generation and its utility toward quantitative evaluation of analytical methods'. Together they form a unique fingerprint.

  • Cite this

    Kim, D. Y., & Lee, J-H. (2012). Pseudo-real fMRI data generation and its utility toward quantitative evaluation of analytical methods. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (pp. 1095-1099). [6377876] https://doi.org/10.1109/ICSMC.2012.6377876