Effects of imprecise signal extraction on posterior DCM parameters.

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU109308" target="_blank" >RIV/00216305:26220/14:PU109308 - isvavai.cz</a>
Result on the web
<a href="https://ww4.aievolution.com/hbm1401/index.cfm?do=abs.viewAbs&abs=3095" target="_blank" >https://ww4.aievolution.com/hbm1401/index.cfm?do=abs.viewAbs&abs=3095</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Effects of imprecise signal extraction on posterior DCM parameters.
Original language description
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.
Czech name
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Czech description
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Project
<a href="/en/project/GAP103%2F12%2F0552" target="_blank" >GAP103/12/0552: Comparison and inference of methods for evaluation of functional and effective connectivity in fMRI</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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