Abstract
Population receptive field (pRF) analysis is a popular method to infer spatial selectivity of voxels in visual cortex. However, it remains largely untested how stable pRF estimates are over time. Here we measured the intersession reliability of pRF parameter estimates for the central visual field and near periphery, using a combined wedge and ring stimulus containing natural images. Sixteen healthy human participants completed two scanning sessions separated by 10–114 days. Individual participants showed very similar visual field maps for V1-V4 on both sessions. Intersession reliability for eccentricity and polar angle estimates was close to ceiling for most visual field maps (r>.8 for V1-3). PRF size and cortical magnification (CMF) estimates showed strong but lower overall intersession reliability (r≈.4–.6). Group level results for pRF size and CMF were highly similar between sessions. Additional control experiments confirmed that reliability does not depend on the carrier stimulus used and that reliability for pRF size and CMF is high for sessions acquired on the same day (r>.6). Our results demonstrate that pRF mapping is highly reliable across sessions.
Highlights
20% of the human cerebral cortex responds to visual stimuli and large parts of visual cortex are organized as visual field maps: neighboring points in the visual field are represented on neighboring parts of cortex (Saygin and Sereno, 2008; Sereno and Huang, 2006; Wandell et al, 2007)
This is in line with Dumoulin and Wandell (2008), who showed that the shape of the hemodynamic response function (HRF) only has a small effect on population receptive field (pRF) estimates
Our results suggest that the intersession reliability of eccentricity and polar angle estimates is very high, consistent with the assumption that the overall architecture of visual field maps is stable over time
Summary
20% of the human cerebral cortex responds to visual stimuli and large parts of visual cortex are organized as visual field maps: neighboring points in the visual field are represented on neighboring parts of cortex (Saygin and Sereno, 2008; Sereno and Huang, 2006; Wandell et al, 2007). In comparison to conventional phase encoded methods (e.g. Sereno, 1995), pRF mapping estimates both the location in the visual field to which a voxel is most responsive, and the extent of the area to which the voxel responds. Most commonly this entails fitting a forward model to a voxel's response time series Lee et al (2013), Greene et al (2014), de Haas et al (2014) for data-driven approaches). The pRF parameters of each voxel are fitted by minimizing the residuals between the predicted and observed BOLD time series
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