TY - GEN
T1 - RAFNI
T2 - 19th International Conference on Neural Information Processing, ICONIP 2012
AU - Bensmail, Halima
AU - Anjum, Samreen
AU - Bouhali, Othmane
AU - El Anbari, Mohammed
PY - 2012
Y1 - 2012
N2 - Functional Magnetic Resonance Imaging (fMRI) is a non-inasive neuro-imaging method that is widely used in cognitive neuroscience. It relies on the measurement of changes in the blood oxygenation level resulting from neural activity. The technique is widely used in cognitive neuroscience. fMRI is known to be contaminated by artifacts. Artifacts are known to have fat tails and are often skewed therefore modeling the error using a Gaussian distribution is a not enough. In this paper, we introduce RAFNI, an extention of AFNI, which is an fMRI open source software for the Analysis of Functional NeuroImages. We are modeling the error introduced by artifacts using α-stable distribution. We demonstrate the applicability and efficiency of stable distributions on real fMRI. We show that the α-stable estimator gives better results than the OLS-based estimators.
AB - Functional Magnetic Resonance Imaging (fMRI) is a non-inasive neuro-imaging method that is widely used in cognitive neuroscience. It relies on the measurement of changes in the blood oxygenation level resulting from neural activity. The technique is widely used in cognitive neuroscience. fMRI is known to be contaminated by artifacts. Artifacts are known to have fat tails and are often skewed therefore modeling the error using a Gaussian distribution is a not enough. In this paper, we introduce RAFNI, an extention of AFNI, which is an fMRI open source software for the Analysis of Functional NeuroImages. We are modeling the error introduced by artifacts using α-stable distribution. We demonstrate the applicability and efficiency of stable distributions on real fMRI. We show that the α-stable estimator gives better results than the OLS-based estimators.
KW - Functional Magnetic Resonance Imaging
KW - General Linear Model (GLM)
KW - α-stable distribution
UR - http://www.scopus.com/inward/record.url?scp=84869072356&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-34475-6_75
DO - 10.1007/978-3-642-34475-6_75
M3 - Conference contribution
AN - SCOPUS:84869072356
SN - 9783642344749
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 624
EP - 631
BT - Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings
Y2 - 12 November 2012 through 15 November 2012
ER -