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
fDate :
March 30 2011-April 2 2011
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;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-4127-3
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2011.5872701