Abstract
Population receptive field (pRF) modeling is a popular fMRI method to map the retinotopic organization of the human brain. While fMRI-based pRF-maps are qualitatively similar to invasively recorded single-cell receptive fields in animals, it remains unclear what neuronal signal they represent. We addressed this question in awake non-human primates comparing whole-brain fMRI and large-scale neurophysiological recordings in areas V1 and V4 of the visual cortex. We examined the fits of several pRF-models based on the fMRI BOLD-signal, multi-unit spiking activity (MUA) and local field potential (LFP) power in different frequency bands. We found that pRFs derived from BOLD-fMRI were most similar to MUA-pRFs in V1 and V4, while pRFs based on LFP gamma power also gave a good approximation. FMRI-based pRFs thus reliably reflect neuronal receptive field properties in the primate brain. In addition to our results in V1 and V4, the whole-brain fMRI measurements revealed retinotopic tuning in many other cortical and subcortical areas with a consistent increase in pRF-size with increasing eccentricity, as well as a retinotopically specific deactivation of default-mode network nodes similar to previous observations in humans.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Ethics statement
Animal care and experimental procedures were in accordance with the ILAR’s Guide for the Care and Use of Laboratory Animals, the European legislation (Directive 2010/63/EU) and approved by the institutional animal care and use committee of the Royal Netherlands Academy of Arts and Sciences and the Central Authority for Scientific Procedures on Animals (CCD) in the Netherlands.
Conflicts of interest
The authors declare that no financial or non-financial competing interests exist.
Data and code availability
All data and code are available on GIN: https://doi.org/10.12751/g-node.p8ypgv,
Unthresholded fMRI model fitting results are on Neurovault: https://identifiers.org/neurovault.collection:8082
This is a revision of the paper in response to reviewer questions and comments at eLife.
