A methodology for fMRI data analysis confined to the cortex, Cortical Surface Mapping (CSM), is presented. CSM retains the flexibility of the General Linear Model based estimation, but the procedures involved are adapted to operate on the cortical surface, while avoiding to resort to explicit

Abstract: A methodology for fMRI data analysis confined to the cortex, Cortical Surface Mapping (CSM), is presented. CSM retains the flexibility of the General Linear Model based estimation, but the procedures involved are adapted to operate on the cortical surface, while avoiding to resort

This paper introduces the general framework, concepts, and procedures of anatomically informed basis functions (AIBF), a new method for the analysis of functional magnetic resonance imaging (fMRI) data. In contradistinction to existing voxel-based univariate or multivariate methods the approach

fMRI retinotopic mapping provides detailed information about the correspondence between the visual field and its cortical representation in the individual subject. Besides providing for the possibility of unambiguously localizing functional imaging data with respect to the functional architecture

;oddball" attention task (23). A third experiment examined whether the network switching mechanism could be observed during task-free resting state where there was no overt task and no behavioral response (4). Our motivation for examining the resting-state fMRI data was the recent finding, based on computer

resonance imaging MRI to constrain the analysis of functional magnetic resonance imaging (fMRI) data, for independent assessment of functional activity change in each component of the MTL. With this method, increased activity was detected throughout the MTL in a group of participants (n 5) who encoded

Segregation of somatosensory activation in the human Rolandic cor-tex using fMRI. J Neurophysiol 84: 558–569, 2000. The segregation of sensory information into distinct cortical areas is an important organizational feature of mammalian sensory systems. Here, we pro-vide functional magnetic

for the original image volume. We present quantitative and visual comparisons between Talairach, mutual information-based volumetric matching and RPM on five subjects' MR images. 1 Introduction The recent development of brain imaging technologies (PET, MRI, fMRI) has provided rich information on the human

segmentation. Here, we describe a novel approach for data-driven analysis of single-subject fMRI time-series that combines techniques for reconstruction of the cortical surface of the subject’s brain and spatial independent component analysis (ICA) of functional time-courses (cortex-based ICA or cb

. This generalization is called diffusion smoothing and has been used in analysis of fMRI data on the cortical surface [1] and detecting cortical surface-area growth [3]. We give an exact mathematical formulation for the diffusion smoothing on triangulated cortical surfaces so that this technique can be used for any