Biases in volumetric versus surface analyses in population receptive field mapping

Abstract

Population receptive field (pRF) mapping is a quantitative fMRI analysis method that links visual field positions with specific locations in the visual cortex. A common preprocessing step in pRF analyses involves projecting volumetric fMRI data onto the cortical surface, often leading to upsampling of the data. This process may introduce biases in the resulting pRF parameters. To investigate this, we present CON-pRF, a fully containerized pipeline for pRF mapping analysis that is designed to maximize reproducibility in pRF mapping studies. Using this pipeline, we compared pRF maps generated from original volumetric with those from upsampled surface data. Our results show substantial increases in pRF coverage in the central visual field of upsampled data sets. These effects were consistent across early visual cortex areas V1-3. Further analysis indicates that this bias is primarily driven by the non-linear relationship between cortical distance and visual field eccentricity, known as cortical magnification. Our results demonstrate that reproducible analysis pipelines enable the detection of potential biases introduced by varying processing steps, particularly when comparing across differently processed datasets. Key PointsO_LISpatial upsampling increases pRF coverage in the fovea due to enhanced CNR and cortical magnification. C_LIO_LIThe study highlights the need for careful consideration of data processing steps. C_LIO_LICON-pRF is a containerized pipeline for enhanced reproducibility in pRF analysis. C_LI