AbstractRepeated exposure to perceptual tasks improves behavioral performance. Several neural mechanisms have been proposed to account for such perceptual learning. Computational modeling suggests that plasticity in the connectivity between cortical sites may be responsible, by increasing the fidelity with which task-relevant information is transmitted through sensory hierarchies. Here, we explore this theory in humans using fMRI, testing the hypothesis that perceptual learning at one location in space will increase functional connectivity between voxels in visual areas that are tuned to that retinotopic location. Participants learned to detect one of two novel visual shape contours embedded in a noisy background in different visual quadrants. At baseline, there was no difference in behavioral sensitivity for the two shapes, nor a difference in functional connectivity between voxels in V1 and V4 responsive to the retinotopic locations of the two shapes. After training, there was a robust and selective improvement in perceptual detection of the trained shape relative to the control shape, along with increased functional connectivity between V1 and V4 voxels coding for the location of the trained shape in retinotopic space. Moreover, this increase in functional connectivity for the trained versus control shape predicted the improvement in behavioral sensitivity across participants. These results are consistent with the proposal that perceptual learning alters network dynamics so as to enhance the processing of behaviorally relevant information.
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This post is Copyright: | September 1, 2026
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