Converging measures of neural change at the microstructural, informational, and cortical network levels in the hippocampus during the learning of the structure of organic compounds

The critical role of the hippocampus in human learning has been illuminated by neuroimaging studies that increasingly improve the detail with which hippocampal function is understood. However, the hippocampal information developed with different types of imaging technologies is seldom integrated within a single investigation of the neural changes that occur during learning. Here we show three different ways in which a small hippocampal region changes as the structures and names of a set of organic compounds are being learned, reflecting changes at the microstructural, informational, and cortical network levels. The microstructural changes are sensed using measures of water diffusivity. The informational changes are assessed using machine learning of the neural representations of organic compounds as they are encoded in the fMRI-measured activation levels of a set of hippocampal voxels. The changes in cortical networks are measured in terms of the functional connectivity between hippocampus and parietal regions. The co-location of these three hippocampal changes reflects that structure’s involvement in learning at all three levels of explanation, consistent with the multiple ways in which learning brings about neural change.