Biology subjects

Mack, M. L.

Publications and source records attributed to Mack, M. L..

9 recordsLinked to original sources

bioRxiv2026

Task goals dynamically reconfigure neural working memory representations

A hallmark of human intelligence is the ability to flexibly shift between tasks and modify our behaviour according to current goals and context. Working memory (WM) is thought to be critical for this cognitive flexibility. A key unanswered question is how neural representations of WM are configured to support different task goals. Thirty-four participants performed a shape WM task with different task rules in interleaved blocks: delayed match-to-sample (DMS) and delayed match-to-category (DMC), while electroencephalography (EEG) was collected. Our results show that stimuli from a circular shape space can be decoded from EEG across the memory delay. Neural stimulus patterns initially generalised across tasks but reconfigured to integrate task and category information and became task-dependent in the later delay. In the DMC task, neural patterns for shapes within a category became more similar than across categories, controlling for their physical distance. This category-dependent shift was associated with greater task-dependency in the neural stimulus representation. Together, our results reveal a dynamic reconfiguration of neural WM representations over the course of the delay period to support distinct task demands. Significance statementAs humans, we regularly move between tasks and change our behaviour according to the situation. This cognitive flexibility critically depends on our working memory, the ability to keep information in mind in the short term. It remains poorly understood how working memory configures mental representations to support different tasks. In this study, participants performed two tasks that probed working memory for visual details or object category respectively. Neural representations were initially similar irrespective of task but became more task-dependent over time in memory. The task-dependence in the neural representation was explained by a neural category bias that emerged during the memory delay. Our results demonstrate how neural representations integrate prior knowledge with stimulus representations in a task-dependent manner, supporting flexible cognition.

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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.

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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.

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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.

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bioRxiv2024

Distinct hippocampal mechanisms support concept formation and updating

Learning systems must constantly decide whether to create new representations or update existing ones. For example, a child learning that a bat is a mammal and not a bird would be best served by creating a new representation, whereas updating may be best when encountering a second similar bat. Characterizing the neural dynamics that underlie these complementary memory operations requires identifying the exact moments when each operation occurs. We address this challenge by interrogating fMRI brain activation with a computational learning model that predicts trial-by-trial when memories are created versus updated. We found distinct neural engagement in anterior hippocampus and ventral striatum for model-predicted memory create and update events during early learning. Notably, the degree of this effect in hippocampus, but not ventral striatum, significantly related to learning outcome. Hippocampus additionally showed distinct patterns of functional coactivation with ventromedial prefrontal cortex and angular gyrus during memory creation and premotor cortex during memory updating. These findings suggest that complementary memory functions, as formalized in computational learning models, underlie the rapid formation of novel conceptual knowledge, with the hippocampus and its interactions with frontoparietal circuits playing a crucial role in successful learning. Significance statementHow do we reconcile new experiences with existing knowledge? Prominent theories suggest that novel information is either captured by creating new memories or leveraged to update existing memories, yet empirical support of how these distinct memory operations unfold during learning is limited. Here, we combine computational modeling of human learning behaviour with functional neuroimaging to identify moments of memory formation and updating and characterize their neural signatures. We find that both hippocampus and ventral striatum are distinctly engaged when memories are created versus updated; however, it is only hippocampus activation that is associated with learning outcomes. Our findings motivate a key theoretical refinement that positions hippocampus is a key player in building organized memories from the earliest moments of learning.

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bioRxiv2023

Differentiation of related events in hippocampus supports memory reinstatement in development

Adults are capable of either differentiating or integrating similar events in memory based on which representations are optimal for a given situation. Yet how children represent related memories remains unknown. Here, children (7-10 years) and adults formed memories for separate yet overlapping events. We then measured how successfully remembered events were represented and reinstated using functional magnetic resonance imaging (fMRI). We found that children formed differentiated representations in hippocampus--such that related events were stored as less similar to one another compared to unrelated events. Conversely, adults formed integrated representations, wherein related events were stored as more similar, including in medial prefrontal cortex (mPFC). Furthermore, hippocampal differentiation among children and mPFC integration among adults tracked neocortical reinstatement of the specific features associated with the individual events. Together, these findings reveal that the same memory behaviors are supported by different underlying representations across development. Specifically, whereas differentiation underlies memory organization and retrieval in childhood, integration exhibits a protracted developmental trajectory.

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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.

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bioRxiv2020

Scene wheels: Measuring perception and memory of real-world scenes with a continuous stimulus space

Precisely characterizing mental representations of visual experiences requires careful control of experimental stimuli. Recent work leveraging such stimulus control has led to important insights; however, these findings are constrained to simple visual properties like colour and line orientation. There remains a critical methodological barrier to characterizing perceptual and mnemonic representations of realistic visual experiences. Here, we introduce a novel method to systematically control visual properties of natural scene stimuli. Using generative adversarial networks (GAN), a state-of-art deep learning technique for creating highly realistic synthetic images, we generated scene wheels in which continuously changing visual properties smoothly transition between meaningful realistic scenes. To validate the efficacy of scene wheels, we conducted two behavioral experiments that assess perceptual and mnemonic representations attained from the scene wheels. In the perceptual validation experiment, we tested whether the continuous transition of scene images along the wheel is reflected in human perceptual similarity judgment. The perceived similarity of the scene images correspondingly decreased as distances between the images increase on the wheel. In the memory experiment, participants reconstructed to-be-remembered scenes from the scene wheels. Reconstruction errors for these scenes resemble error distributions observed in prior studies using simple stimulus properties. Importantly, perceptual similarity judgment and memory precision varied systematically with scene wheel radius. These findings suggest our novel approach offers a window into the mental representations of naturalistic visual experiences.

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bioRxiv2017

Medial prefrontal cortex compresses concept representations through learning

Prefrontal cortex (PFC) is thought to support the ability to focus on goal-relevant information by filtering out irrelevant information, a process akin to dimensionality reduction. Here, we test this dimensionality reduction hypothesis by combining a data-driven approach to characterizing the complexity of neural representation with a theoretically-supported computational model of learning. We find strong evidence of goal-directed dimensionality reduction within human ventromedial PFC during learning. Importantly, by using model predictions of each participants attentional strategies during learning, we find that that the degree of neural compression predicts an individuals ability to selectively attend to concept-specific information. These findings suggest a domain-general mechanism of learning through compression in ventromedial PFC.

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