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Research data supporting "Recurrent processing drives perceptual plasticity"

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Jia, Ke 


Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet, evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer-scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high field (7T) functional imaging at sub-millimetre resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. Our results provide evidence for recurrent plasticity, by contrast to sensory encoding vs. feedback mechanisms. We demonstrate that learning alters orientation-specific representations in superficial rather than middle V1 layers, suggesting changes in read-out rather than input signals. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer-scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro- circuits of experience-dependent plasticity.


See the file 'Description of uploaded data' for a detailed description of the dataset.


Software / Usage instructions

matlab, PTB, freesurfer, Brainvoyager


learning, experience-dependent plasticity, ultra-high field brain imaging


European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (840271)