Abstract
FMRI retinotopic mapping is a non-invasive technique for the delineation of low-level visual areas in individual subjects. It generally relies upon the analysis of functional responses to periodic visual stimuli that encode eccentricity or polar angle in the visual field. This technique is used in vision research when the precise assignation of brain activation to retinotopic areas is an issue. It involves processing steps computed with different algorithms and embedded in various software suites. Manual intervention may be needed for some steps. Although the diversity of the available processing suites and manual interventions may potentially introduce some differences in the final delineation of visual areas, no documented comparison between maps obtained with different procedures has been reported in the literature. To explore the effect of the processing steps on the quality of the maps obtained, we used two tools, BALC, which relies on a fully automated procedure, and BrainVoyager, where areas are delineated “by hand” on the brain surface. To focus on the mapping procedures specifically, we used the same SPM pipeline for pretreatment and the same tissue segmentation tool. We document the consistency and differences of the fMRI retinotopic maps obtained from “routine retinotopy” experiments on 10 subjects. The maps obtained by skilled users are never fully identical. However, the agreement between the maps, around 80% for low-level areas, is probably sufficient for most applications. Our results also indicate that assigning cognitive activations, following a specific experiment (here, color perception), to individual retinotopic maps is not free of errors. We provide measurements of this error, that may help for the cautious interpretation of cognitive activation projection onto fMRI retinotopic maps. On average, the magnitude of the error is about 20%, with much larger differences in a few subjects. More variability may even be expected with less trained users or using different acquisition parameters and preprocessing chains.
Highlights
In humans, the visual cortex is organized into different functional areas where adjacent neurons have receptive fields sensitive to adjacent positions in the visual field
The most popular technique for functional Magnetic Resonance Imaging (fMRI) retinotopic mapping relies upon analysis of functional responses to periodic visual stimuli that encode eccentricity or polar angle in the visual field (Engel et al, 1994)
Functional retinotopic mapping has become the current method for non-invasive delineation of visual cortical areas
Summary
The visual cortex is organized into different functional areas where adjacent neurons have receptive fields sensitive to adjacent positions in the visual field. The most popular technique for fMRI retinotopic mapping relies upon analysis of functional responses to periodic visual stimuli (annulus or wedge, both centered on a fixation point) that encode eccentricity or polar angle in the visual field (Engel et al, 1994) These stimuli associate each position in the visual field to a delay of the periodic stimulation of the neurons with the corresponding receptive fields. Phase analysis can be performed in a 3D-space (Dumoulin et al, 2003) or in the surface to detect more precisely and possibly automatically where the inversion of the visual field sign occurs This often called phase-encoded functional design (Engel, 2012) is largely used in vision research, when the precise assignation of functional activation to specific retinotopic areas is an issue. Despite some limitations notably in the foveal region (Wandell and Winawer, 2011) or beyond V3v (Winawer et al, 2010), retinotopic maps are measured reliably by phase-encoded designs both in ventral (Wade et al, 2002; Arcaro et al, 2009) and dorsal (Larsson and Heeger, 2006; Pitzalis et al, 2006; Hansen et al, 2007; Amano et al, 2009) streams
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