Publication detail

Effects of imprecise signal extraction on posterior DCM parameters.

SLAVÍČEK, T. LAMOŠ, M. GAJDOŠ, M. MIKL, M. JAN, J.

Original Title

Effects of imprecise signal extraction on posterior DCM parameters.

Type

abstract

Language

English

Original Abstract

Dynamic causal modeling (DCM) is a method for analyzing effective connectivity in functional magnetic resonance imaging (fMRI) data. Specific parameters describing the generative model (involved regions, connections, modulatory effects, inputs, etc.) represent input to the DCM method. By inverting the forward model, DCM infers (hidden) neuronal processes using fitting to the experimentally measured signal (Kahan and Foltynie 2013). Then, correct localization and extraction of the brain signals from regions of interest (ROIs) directly influences the result. In our study, we compared two approaches for ROIs position specification (common vs. individual) and evaluated their sensitivity to random shifts of ROI position.

Keywords

fMRI, DCM, effective connectivity, signal extraction, group statistics

Authors

SLAVÍČEK, T.; LAMOŠ, M.; GAJDOŠ, M.; MIKL, M.; JAN, J.

Released

12. 6. 2014

Pages count

3

URL

https://ww4.aievolution.com/hbm1401/index.cfm?do=abs.viewAbs&abs=3095

BibTex

@misc{BUT107932,
  author="Tomáš {Slavíček} and Martin {Lamoš} and Martin {Gajdoš} and Michal {Mikl} and Jiří {Jan}",
  title="Effects of imprecise signal extraction on posterior DCM parameters.",
  booktitle="20th Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2014.",
  year="2014",
  pages="3",
  url="https://ww4.aievolution.com/hbm1401/index.cfm?do=abs.viewAbs&abs=3095",
  note="abstract"
}