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Paper Detail

Paper:	SS-8.4
Session:	Advanced Methods for Mapping Brain Functions from Functional MRI Datasets
Time:	Thursday, May 18, 15:00 - 15:20
Presentation:	Special Session Lecture
Topic:	Special Sessions: Advanced methods for mapping brain functions from functional MRI datasets
Title:	Correction of structured noise in fMRI using spatial component analysis : CORSICA
Authors:	Vincent Perlbarg, Pierre Bellec, INSERM U678, France; Jean-Luc Anton, CNRS - Centre IRMf, CHU La Timone, France; Habib Benali, INSERM U678, France
Abstract:	The physiological fluctuations (breathing and heartbeat) and brain movements are the main sources of confounds in activation and functional connectivity studies in functional magnetic resonance imaging (fMRI). The main difficulty to cope with these effects is the aliasing of cardiac and possible respiration signals for acquisitions with long TR (typically TR>1s). We proposed a method of structured noise correction based on spatial Independent Component Analysis, able to extract components linked to cardio-respiratory activity and brain movements. The automatic selection of noise-related components was based on a stepwise regression procedure using "true" physiological noise time courses as reference (extracted from regions of interest in the cerebro-spinal fluid and near major blood vessels). We evaluated the sensitivity of the selection on long-TR and short-TR datasets and we showed that our method was efficient even for long-TR datasets.