DocumentCode
3510479
Title
Quantifying information flowin fMRI using the Kullbakc-Leibler divergence
Author
Seghouane, Abd-Krim
Author_Institution
Canberra Res. Lab., Australian Nat. Univ., Canberra, ACT, Australia
fYear
2011
fDate
March 30 2011-April 2 2011
Firstpage
1569
Lastpage
1572
Abstract
Extracting the directional interaction between activated brain areas from functional magnetic resonance imaging (fMRI) time series measurements of their activity is a significant step in understanding the process of brain functions. In this paper, the directional interaction between fMRI time series characterizing the activity of two neuronal sites is quantified using a measure derived from the Kullback-Leibler divergence. A parametric approach based on the autoregressive (AR) and autoregressive exogenous (ARX) modelling is proposed for estimating this measure. The links between the proposed measure and other existing information measures for quantifying the directional interaction between neuronal sites is discussed. The significance and effectiveness of the proposed measure is illustrated on both simulated and real fMRI data sets.
Keywords
autoregressive processes; biomedical MRI; brain; data analysis; feature extraction; medical image processing; neurophysiology; parameter estimation; time series; Kullbakc-Leibler divergence; autoregressive exogenous modelling; brain; data sets; fMRI time series measurement; feature extraction; functional magnetic resonance imaging; information flow; neuronal sites; parameter estimation; Brain modeling; Current measurement; Magnetic resonance imaging; Mathematical model; Q measurement; Time series analysis; Functional MRI; Kullback-Leibler divergence; effective connectivity; information flow;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location
Chicago, IL
ISSN
1945-7928
Print_ISBN
978-1-4244-4127-3
Electronic_ISBN
1945-7928
Type
conf
DOI
10.1109/ISBI.2011.5872701
Filename
5872701
Link To Document