David Linhardt

The paper shows that large-scale simulations can replicate in vivo pRF mapping variability patterns, offering insights into retinotopic mapping paradigms.

This study characterizes the topographic organization of the human visual claustrum zone using population receptive field analysis, revealing both similarities to and distinctions from other visually responsive brain regions.

GEM-pRF accelerates population receptive field mapping in fMRI by reformulating the GLM and using GPU computation, achieving faster and accurate results than existing methods.

This paper introduces a deep learning tool to predict functional topography of the human visual cortex from anatomy, demonstrating its utility across diverse conditions and large-scale datasets.

The paper compares volumetric and surface-based pRF mapping analyses, finding that surface upsampling increases pRF coverage in the central visual field due to cortical magnification.

This study uses 7T fMRI to show distinct visual responses in the human claustrum, supporting its role in sensory processing.