Distinct contributions of hippocampal pathways in learning regularities and exceptions revealed by functional footprints

Abstract Fundamental aspects of learning are theorized to be supported by hippocampal pathways: monosynaptic pathway (MSP) extracts regularities whereas trisynaptic pathway (TSP) rapidly encodes exceptional items. Yet, the empirical evidence for the dynamic involvement of MSP and TSP in learning remains elusive. We leveraged diffusion-weighted imaging to estimate the end points of MSP- and TSP-related white matter structures (i.e., footprints) within hippocampal subfields and entorhinal cortex. We then measured the activation of pathway-specific footprints with functional magnetic resonance imaging while participants learned novel concepts defined by regularities and exceptions. The functional footprint method revealed links between MSP-related footprint activation and regularity encoding early in learning, and TSP-related footprint activation and exception encoding late in learning. These findings provide novel evidence that learning concept regularities and exceptions is distinctly supported by hippocampal pathways. Pathway footprint approach provides insights into the functional dynamics of the human hippocampus, translating theoretical and computational work into empirically testable questions in humans. Significance Statement Theories suggest that learning involves two main functions of the hippocampus: integrating commonly encountered information and distinctly encoding exceptional items. Yet, the theorized contributions of hippocampal pathways are yet to be empirically validated. We provide the first evidence of this in humans by introducing a multimodal technique (pathway footprints) that targets learning-related activations at the endpoints of hippocampal pathways. The more a pathway is engaged for a given learning experience, the more the pathway endpoints will be activated. This innovation reveals the dynamic involvement of hippocampal pathways in learning: one unites common information early in learning while another encodes exceptional items late in learning. The pathway footprint method offers precise estimates of neural signatures of cognition as refined by anatomy. Competing Interest Statement The authors have declared no competing interest. Footnotes Conflict of interest: The authors, MG and MLM, declare no conflict of interests.