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Gumus, M.

Publications and source records attributed to Gumus, M..

2 recordsLinked to original sources

The structure of hippocampal trisynaptic pathway relates to rapid category learning in humans

Prior work suggests that complementary white matter pathways within the hippocampus differentially support learning of specific versus general information. In particular, while the trisynaptic pathway (TSP) rapidly forms memories for specific experiences, the monosynaptic pathway (MSP) slowly learns generalities. However, despite the theorized significance of such circuitry, characterizing how information flows within hippocampus (HPC) to support learning in humans remains a challenge. We leveraged diffusion-weighted imaging as a proxy for individual differences in white matter structure linking key regions along TSP (HPC subfields CA3 and CA1) and MSP (entorhinal cortex and CA1) and related these differences in hippocampal structure to category learning ability. We hypothesized that learning to categorize the "exception" items that deviated from category rules would benefit from TSP-supported mnemonic specificity. Participant-level estimates of TSP- and MSP-related integrity were constructed from HPC subfield connectomes of white matter streamline density. Consistent with theories of TSP-supported learning mechanisms, we found a specific association between the integrity of CA3-CA1 white matter connections and exception learning. These results highlight the significant role of HPC circuitry in complex human learning.

neuroscience↗

Linking minimal and detailed models of CA1 microcircuits reveals how theta rhythms emerge and how their frequencies are controlled

The wide variety of cell types and their inherent biophysical complexities pose a challenge to our understanding of oscillatory activities produced by cellular-based computational models. This challenge stems from the high-dimensional and multi-parametric nature of these systems. To overcome this issue, we implement systematic comparisons of minimal and detailed models of CA1 microcircuits that generate intra-hippocampal theta rhythms (3-12 Hz). We leverage insights from minimal models to guide detailed model explorations and obtain a cellular perspective of theta generation. Our findings distinguish the pyramidal cells as the theta rhythm initiators and reveal that their activity is regularized by the inhibitory cell populations, supporting an inhibition-based tuning mechanism. We find a strong correlation between the pyramidal cell input current and the resulting LFP theta frequency, establishing that the intrinsic pyramidal cell properties underpin network frequency characteristics. This work provides a cellular-based foundation from which in vivo theta activities can be explored.

neuroscience↗