In crowding, the perception of a target is impeded by surrounding clutter. While traditional models are feedforward and local, there is increasing behavioral and neural evidence for a critical role of recurrent processing across the visual hierarchy in crowding. Our recent fMRI findings suggest that higher visual areas, sensitive to global context, determine whether target and flanker features are combined within a single population receptive field (pRF) or rather the target is separated from the flankers in a smaller pRF, likely through recurrent processing. Here, we investigated the neural correlates of perceptual learning to “de-crowd”. Twelve participants trained on an orientation discrimination task under crowding, with the stimulus always presented in the top-right quadrant. Performance on the crowding condition improved substantially in the trained quadrant, but only to a lesser extent in an untrained quadrant. No significant improvements were seen in a no-crowding condition. We used fMRI to estimate pRF sizes in visual areas V1 to V4, separately in areas representing the four visual quadrants. We used dynamic causal modeling to compare bottom-up, top-down, and recurrent models of learning-related modulation of connectivity between visual areas. We found a substantial decrease in pRF size only in left ventral V3, corresponding to the trained visual quadrant. Learning to de-crowd modulated recurrent connectivity across the visual hierarchy, whereas only bottom-up connectivity was modulated in no-crowding. Our findings suggest that improvements in target discrimination under crowding are mediated by top-down processing, which determines the segmentation of the target and flankers through pRF size adjustment. [We would like to thank our funding sources: Swiss National Science Foundation (NCCR Synapsy, project grant numbers 32003B_135679, 32003B_159780, 324730_192755, CRSK-3_190185, 176153), the Leenaards Foundation, Fondation ROGER DE SPOELBERCH, and the Partridge Foundation.]