Human learning is a complex process in which future behavior is altered via the modulation of neural activity . Yet, the degree to which brain activity and functional connectivity during learning is constrained across subjects, for example by conserved anatomy andphysiology or by the nature of the task, remains unknown. Here, we measured brain activity and functional connectivity in a longitudinal  experiment in which healthy adult human participants learned the values of novel objects over the course of four days.  We assessed the presence of constraints on activity and functional connectivity using an inter-subject correlation approach. Constraints on activity and connectivity were greater in magnitude than expected in a non-parametric permutation-based null model, particularly in primary sensory and motor systems, as well as in regions associated with the learning of value. Notably, inter-subject connectivity in activity and connectivity displayed marked temporal variations, with inter-subject correlations in activity exceeding those in connectivity during early learning and visa versa in later learning . Finally, individual differences in performance accuracy tracked the degree to which a subject's connectivity, but not activity, tracked subject-general patterns. Taken together, our results support the notion that brain activity and connectivity are constrained across subjects in early learning, with constraints on activity, but not connectivity, decreasing in later learning .
Human learning is a complex process in which future behavior is altered via the URLanization of brain activity and connectivity. It remains unknown whether activity and connectivity differentially URLanize during learning, and, if so, how that differential URLanization tracks stages of learning across distinct brain areas . Here, we address this gap in knowledge by measuring brain activity and functional connectivity in a longitudinal fMRI experiment in which healthy adult human participants learn the values of novel objects over the course of four days. An increasing similarity in activity or functional connectivity across subjects during learning reflects URLanization toward a common functional architecture. We assessed the presence of URLanization in activity and connectivity both during value learning and during the resting-state, allowing us to differentiate common elicited processes from intrinsic processes. We found a complex and dynamic URLanization of brain connectivity and activity--as a function of time, space, and performance--that occurs while subjects learn. Spatially localized brain activity URLanizes across the brain to a common functional architecture early in learning, and this URLanization tracks early learning performance. In contrast, spatially distributed connectivity URLanizes across the brain to a common functional architecture as training progresses, and this URLanization tracks later learning performance. Particularly good performance is associated with a sticky connectivity, that persists into the resting state. Broadly, our work uncovers distinct principles of URLanization in activity and connectivity at different phases of value learning, which inform the ongoing study of learning processes more generally .
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modulation of neural activity
URLanization of brain activity and connectivity. It remains unknown whether activity and connectivity differentially URLanize during learning, and, if so, how that differential URLanization tracks stages of learning across distinct brain areas
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Yet, the degree to which brain activity and functional connectivity during learning is constrained across subjects, for example by conserved anatomy andphysiology or by the nature of the task, remains unknown.
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measured
address this gap in knowledge by measuring
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fMRI
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learned
learn
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An increasing similarity in activity or functional connectivity across subjects during learning reflects URLanization toward a common functional architecture.
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constraints on activity and functional connectivity using an inter-subject correlation approach. Constraints on activity and
URLanization in activity and
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were greater in magnitude than expected in a non-parametric permutation-based null model, particularly in primary sensory and motor systems, as well as in regions associated with the learning of value. Notably, inter-subject connectivity in activity and connectivity displayed marked temporal variations, with inter-subject correlations in activity exceeding those in connectivity during early learning
both during value learning and during the resting-state, allowing us to differentiate common elicited processes from intrinsic processes. We found a complex and dynamic URLanization of brain connectivity
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visa versa
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in later learning . Finally, individual differences in performance accuracy tracked the degree to which a subject's connectivity, but not activity, tracked subject-general patterns. Taken together, our results support the notion that brain
activity--as a function of time, space, and performance--that occurs while subjects learn. Spatially localized brain activity URLanizes across the brain to a common functional architecture early in learning, and this URLanization tracks early learning performance. In contrast, spatially distributed connectivity URLanizes across the brain to a common functional architecture as training progresses, and this URLanization tracks later learning performance. Particularly good performance is associated with a sticky connectivity, that persists into the resting state. Broadly, our work uncovers distinct principles of URLanization in
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are constrained across subjects in early learning, with constraints on activity, but not connectivity, decreasing in later learning
at different phases of value learning, which inform the ongoing study of learning processes more generally