Biology subjects

Gumus, M.

Publications and source records attributed to Gumus, M..

5 recordsLinked to original sources

bioRxiv2025

Concept Learning Builds Behaviourally Relevant Attentional Templates

Attention optimizes learning by filtering relevant information to build conceptual knowledge. However, how learned concepts, once encoded in memory, subsequently guide attentional processes remains an intriguing question. We propose that concept learning leads to the emergence of attentional templates that store goal-relevant representations, thereby actively guiding attention allocation. Participants completed two separate learning tasks and a test, wherein each trial began with a cue, indicating which learning task should be employed. Random test trials included a probe instead of concept specific features: a small arrow appeared at a feature location that was relevant (i.e., valid) or irrelevant (i.e., invalid) for the cued task. Successful learners were faster at responding to valid probes than invalid, demonstrating the deployment of concept-specific attentional templates. Importantly, the efficiency of this attention allocation was tied to concept learning success, with higher learning performance yielding greater response time benefits at test. Thus, our results reveal that learning builds behaviourally relevant attentional templates, and subsequently, learned concepts in memory guide attention by deploying these templates, a phenomenon that we introduce as learning-guided attention. This work provides novel insights into the dynamic interplay between learning, memory, and attention. Significance StatementExtensive work shows that attention selects the most relevant information while learning new knowledge. Theoretically, the interaction between learning and attention is bidirectional; learned knowledge, in turn, guides attention to relevant information for that context. However, the mechanism by which knowledge in memory directs attention has remained largely unexplored. By developing an experimental paradigm that bridges the learning and attention literatures, we demonstrate that learning builds "attentional templates" which capture what is relevant in a specific learning context. While utilizing learned knowledge, individuals deploy these templates to allocate their attention to the most relevant information for a given situation. We introduce this phenomenon as learning-guided attention, providing novel insights into the dynamic interplay between learning, memory, and attention.

neuroscience↗

bioRxiv2025

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

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 StatementTheories 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.

neuroscience↗

bioRxiv2025

In vivo Quantification of White Matter Pathways in the Human Hippocampus

The hippocampus is a key structure in cognition. Although much research has focused on defining the functions of its anatomically distinct subfields, the communication among these subfields within the hippocampal circuit, supported by white matter pathways, is theoretically key to emergent cognitive function. Yet, hippocampal white matter connections in humans have not been fully explored in vivo. By leveraging diffusion weighted imaging and a large healthy sample (N=831), we developed a processing pipeline for in vivo quantification of human hippocampal pathways. We provided evidence for monosynaptic and trisynaptic pathway-related connections in humans, supporting the described hippocampal circuit in ex vivo and animal studies. In addition to hemispheric and sex differences, the individual variability in hippocampal pathways was linked to cognitive abilities. Thus, in vivo characterization of human hippocampal pathways highlights the individual differences within these structures and paves the way for their implications in cognition, aging, and diseases. Conflict of interestThe authors declare no conflicts of interest.

neuroscience↗

bioRxiv2021

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↗

bioRxiv2020

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↗