Impact of differences between real and predicted time series on GLM fMRI analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F06%3A00017067" target="_blank" >RIV/00216224:14110/06:00017067 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Impact of differences between real and predicted time series on GLM fMRI analysis
Original language description
In functional magnetic resonance imaging (fMRI) detection of activation is often realized using massively univariate statistical methods. The measured signal is modeled using convolution of stimulus time-course and hemodynamic response function (HRF). For accurate fitting the data to the model it is necessary to know both HRF and stimulus time-course. The aim of this work is to find how much the results are depended on inaccurate knowledge of stimulus time-course.
Czech name
—
Czech description
—
Classification
Type
O - Miscellaneous
CEP classification
FH - Neurology, neuro-surgery, nuero-sciences
OECD FORD branch
—
Result continuities
Project
—
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů