Non-Neural Factors Influencing BOLD Response Magnitudes within Individual Subjects.

To what extent is the size of the BOLD response influenced by factors other than neural activity? In a reanalysis of three neuroimaging datasets (male and female human participants), we find large systematic inhomogeneities in the BOLD response magnitude in primary visual cortex (V1): stimulus-evoked BOLD responses, expressed in units of percent signal change, are up to 50% larger along the representation of the horizontal meridian than the vertical meridian. To assess whether this surprising effect can be interpreted as differences in local neural activity, we quantified several factors that potentially contribute to the size of the BOLD response. We find relationships between BOLD response magnitude and cortical thickness, curvature, depth, and macrovasculature. These relationships are consistently found across subjects and datasets and suggest that variation in BOLD response magnitudes across cortical locations reflects, in part, differences in anatomy and vascularization. To compensate for these factors, we implement a regression-based correction method and show that, after correction, BOLD responses become more homogeneous across V1. The correction reduces the horizontal/vertical difference by about half, indicating that some of the difference is likely not because of neural activity differences. We conclude that interpretation of variation in BOLD response magnitude across cortical locations should consider the influence of the potential confounding factors of thickness, curvature, depth, and vascularization. The magnitude of the BOLD signal is often used as a surrogate of neural activity, but the exact factors that contribute to its strength have not been studied on a voxel-wise level. Here, we examined several anatomical and measurement-related factors to assess their relationship with BOLD signal magnitude. We find that BOLD magnitude correlates with cortical anatomy, depth, and macrovasculature. To remove the contribution of these factors, we propose a simple, data-driven correction method that can be used in any fMRI experiment. After accounting for the confounding factors, BOLD magnitude becomes more spatially homogeneous. Our correction method improves the ability to make more accurate inferences about local neural activity from fMRI data.