  Visual field or retinotopic mapping is one of the most frequently used
paradigms in fMRI. It uses activity evoked by position-varying high luminance
contrast visual patterns presented throughout the visual field for determining
the spatial organization of cortical visual areas. While the advantage of using
high luminance contrast is that it tends to drive a wide range of neural
populations - thus resulting in high signal-to-noise BOLD responses - this may
also be a limitation, especially for approaches that attempt to squeeze more
information out of the BOLD response, such as population receptive field (pRF)
mapping. In that case, more selective stimulation of a subset of neurons -
despite reduced signals - could result in better characterization of pRF
properties. Here, we used a second-order stimulus based on local differences in
orientation texture - to which we refer as orientation contrast - to perform
retinotopic mapping. Participants in our experiment viewed arrays of Gabor
patches composed of a foreground (a bar) and a background. These could only be
distinguished on the basis of a difference in patch orientation. In our
analyses, we compare the pRF properties obtained using this new orientation
contrast-based retinotopy (OCR) to those obtained using classic luminance
contrast-based retinotopy (LCR). Specifically, in higher order cortical visual
areas such as LO, our novel approach resulted in non-trivial reductions in
estimated population receptive field size of around 30%. We discuss how OCR -
by limiting receptive field scatter and reducing BOLD displacement - may result
in more accurate pRF localization as well. We conclude that using our approach,
it is possible to selectively target particular neuronal populations, opening
the way to use pRF modeling to dissect the response properties of more
clearly-defined neuronal populations in different visual areas.
