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Learning and experience have been shown to shape critical functions of the adult brain to support our interactions in complex and dynamic environment. Yet the neural underpinnings of learning-dependent plasticity remain controversial. Recent advances in brain imaging technology (i.e. ultra-high field 7T imaging) affords us the resolution to examine fMRI signals at the finer scale of cortical laminar layers advancing our understanding from macro- to micro-structure in the human brain. In this project, we measure fMRI signals across different cortical layers that are known to be involved in feedforward vs. feedback processing to discern between competing theories of learning-dependent plasticity. Further, by combining laminar fMRI with computational modelling, we investigate the neural population code across laminar layers and the fine-scale computations that mediate learning. Finally, we measure laminar connectivity across different brain areas to investigate how different brain areas work together to boost behavioural performance. This project will advance our understanding of how the brain optimises its capacity for adaptive behaviour through learning and experience and has potential practical implications for the design of training programmes for life-long development and disease.