ISA - an inverse surface-based approach for cortical fMRI data projection

Abstract

Surface-based approaches have proven particularly relevant and reliable to study cortical functional magnetic resonance imaging (fMRI) data. However projecting fMRI volumes onto the cortical surface remains a challenging problem. Very few methods have been proposed to solve it and most of them rely on a simple interpolation. We propose here an original surface-based method based on a model representing the relationship between cortical activity and fMRI images, and a resolution through an inverse problem. This approach shows interesting perspectives for fMRI data processing as it is highly robust to noise and offers a good accuracy in terms of activations localization.