Biology subjects

Zacks, J. M.

Publications and source records attributed to Zacks, J. M..

10 recordsLinked to original sources

bioRxiv2026

Age Differences in Hippocampal Neural Timescales During Movie-Viewing

Episodic memory requires integrating information across multiple scales, a process theorized to be supported by a gradient of neural timescales along the anterior-posterior axis of the hippocampus that enables both coarse-and fine-grained representations. Aging is associated with changes in hippocampal function and declines in fine-grained episodic memory, but whether this impacts the gradient organization of the hippocampus is unknown. Additionally, the relationship between the neural timescales of the hippocampus and memory specificity remains unclear. Here, we analyzed the length of timescales of individual voxels in the hippocampus during movie-viewing, along with subsequent recall data, in a sample of young and older participants. Younger adults showed the expected anterior-to-posterior timescale gradient, replicating prior work. In contrast, older adults exhibited a reversal of the expected gradient. Older adults recall was coarser and more gist-like than that of younger adults. In younger adults, longer neural timescales were associated with less specific, more gist-like recall; this was seen predominantly in the posterior-lateral hippocampus. In contrast, no relationship between neural timescales and recall were observed in older adults. An exploratory analysis revealed a similar relationship between neural timescales and memory specificity in cortical regions, in younger but not older adults. These findings suggest that aging alters the organization of neural activity throughout the hippocampus and that neural timescales in the hippocampus and cortex are related to the specificity of memory. Significance statementAs people age, episodic memories become more gist-like and less detailed. The hippocampus, which supports both gist and detailed memory, exhibits a neural timescale gradient--from slow-changing activity (longer timescales) to fast-changing activity (shorter timescales). This organization is theorized to support coarse-and fine-grained memory, respectively, yet a direct link to the age-related shift towards gist-like memory remains unestablished. Here, we identify an age-related shift in the hippocampal timescale gradient that parallels a decline in memory specificity. Furthermore, longer timescales in the hippocampus and cortical regions correlated with decreased memory specificity in younger adults. These findings demonstrate that aging is associated with a reorganization of hippocampal activity and that cortical timescales during encoding may relate to the specificity of memory.

neuroscience↗

bioRxiv2025

A neural network with episodic memory learns causal relationships between narrative events

Humans reflect on memories to make sense of ongoing events. Past work has shown that people retrieve causally related memories during comprehension, but the mechanisms underlying this process remain unclear. Here, we used a recurrent neural network augmented with a key-value episodic memory buffer and trained it to predict upcoming scenes while watching a television episode. At each time step, the model transformed the current scene into a value representing memory content and a key representing memory address, both stored as episodic memory. The model retrieved selective past values by applying self-attention over stored keys and integrated these memories with the current scene representation to generate predictions. The model retrieved memories similar to those retrieved by human participants watching the same episode during fMRI. Importantly, this similarity disappeared when causal relationships between events were controlled for. The model also represented causally related events with similar patterns, similar to how the human brain represents these events. These findings suggest that using two distinct memory representations allows the model to retrieve memories and organize events based on causal relationships, beyond semantic or perceptual similarities. Together, this work proposes a key-value episodic memory system as a candidate computational mechanism for how humans retrieve causally related memories to comprehend naturalistic events.

neuroscience↗

bioRxiv2025

Key moments in naturalistic events synchronize neural activity patterns and dominate memory reinstatement

Continuous experiences are experienced and remembered in terms of events that unfold over time. There is strong evidence that event boundaries segment experience during comprehension and that event representations are compressed in memory; however, this compression is poorly understood. We developed a novel storyboard paradigm to test the hypothesis that representations of continuous experiences are defined by a subset of key moments that capture the underlying narrative. Participants agreed on when key moments occurred; some key moments corresponded with event boundaries, but many did not. fMRI during encoding revealed that neural activity patterns throughout the default network synchronized across individuals at key moments. Further, comparing fMRI during encoding to fMRI during retrieval revealed that key moments are overrepresented in neural patterns that are reinstated during event recall in the posterior-medial cortex. These results suggest that continuous events are punctuated by a small subset of meaningful moments, which dominate neural representations during perception and memory.

neuroscience↗

bioRxiv2025

Geometry of neural dynamics along the cortical attractor landscape reflects changes in attention

The brain is a complex dynamical system whose activity reflects changes in internal states, such as attention. While prior work has shown that large-scale brain activity reflects attention, the mechanism governing this association in a time-varying and task-dependent manner remains unknown. Here, we tested a hypothesis that the geometry of neural dynamics on the attractor landscape, or the movement along the "hills and valleys", reflects changes in attentional states over time and variations across controlled and naturalistic contexts. We fit a parametric dynamical systems model to fMRI data collected during rest, task performance, and naturalistic movie-watching. The model decomposes neural dynamics into components that are intrinsic versus extrinsically driven by stimuli. Model parameters were biologically meaningful, reflecting both cognitive states and individual differences. Model simulations revealed a set of attractors that mirrored functional brain networks, spanning the canonical gradient from sensorimotor to default mode network regions. The speed and direction of neural trajectories toward these attractors systematically varied across attentional states in a context-dependent manner. When participants were paying attention to effortful tasks, neural dynamics converged directly toward a task-relevant attractor, suggesting that it occupied a steeper region of the attractor landscape. In contrast, when participants were engaged in sitcom episodes, neural dynamics were in a flattened region of the landscape, directed away from the attractors. These findings demonstrate that while the positions of the attractors are largely determined by the cortical organization, the geometry of neural dynamics on the attractor landscape changes systematically across attentional states and situational contexts.

neuroscience↗

bioRxiv2020

Bridges, not walls: the hippocampus builds narrative memories across distant events

Lifes events are scattered throughout time, yet we often recall different events in the context of an integrated narrative. Prior research suggests that the hippocampus, which supports memory for past events, can sometimes support integration of overlapping associations or separate events, but the conditions which lead to hippocampus-dependent memory integration are unclear. We used functional brain imaging to test whether the ability to form a larger narrative (narrative coherence) drives hippocampal memory integration. During encoding of fictional stories, the hippocampus supported patterns of activity, including activity at boundaries between events, which were more similar between distant events that formed one coherent narrative, compared with events taken from unrelated narratives. Twenty-four hours later, the hippocampus preferentially supported detailed recall of coherent narrative events, through reinstatement of hippocampal activity patterns from encoding. These findings reveal a key function of the hippocampus: the dynamic integration of events into a narrative structure for memory.

neuroscience↗

bioRxiv2019

Aging and the encoding of changes in events: The role of neural activity pattern reinstatement

When encountering unexpected event changes, memories of relevant past experiences must be updated to form new representations. Current models of memory updating propose that people must first generate memory-based predictions to detect and register that features of the environment have changed, then encode the new event features and integrate them with relevant memories of past experiences to form configural memory representations. Each of these steps may be impaired in older adults. Using functional MRI, we investigated these mechanisms in healthy young and older adults. In the scanner, participants first watched a movie depicting everyday activities in a day of an actors life. They next watched a second nearly identical movie in which some scenes ended differently. Crucially, before watching the last part of each activity, the second movie stopped, and participants were asked to mentally replay how the activity previously ended. Three days later, participants were asked to recall the activities. Neural activity pattern reinstatement in medial temporal lobe (MTL) during the replay phase of the second movie was associated with detecting changes and with better memory for the original activity features. Reinstatements in posterior medial cortex (PMC) additionally predicted better memory for changed features. Compared to young adults, older adults showed a reduced ability to detect and remember changes, and weaker associations between reinstatement and memory performance. These findings suggest that PMC and MTL contribute to change processing by reinstating previous event features, and that older adults are less able to use reinstatement to update memory for changed features.

neuroscience↗

bioRxiv2019

Predicting dysfunctional age-related task activations from resting-state network alterations

Alzheimers disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the timecourse of illness. Study of these fMRI correlates of unhealthy aging has been conducted in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC network alterations associated with Alzheimers disease disrupt the ability for activations to flow between brain regions, leading to aberrant task activations. We apply this activity flow modeling framework in a large sample of clinically unimpaired older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) risk factors for AD. We identified healthy task activations in individuals at low risk for AD, and then by estimating activity flow using at-risk AD restFC data we were able to predict the altered at-risk AD task activations. Thus, modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy aged activations. These results provide evidence that activity flow over altered intrinsic functional connections may act as a mechanism underlying Alzheimers-related dysfunction, even in very early stages of the illness. Beyond these mechanistic insights linking restFC with cognitive task activations, this approach has potential clinical utility as it enables prediction of task activations and associated cognitive dysfunction in individuals without requiring them to perform in-scanner cognitive tasks.\n\nSignificance StatementDeveloping analytic approaches that can reliably predict features of Alzheimers disease is a major goal for cognitive and clinical neuroscience, with particular emphasis on identifying such diagnostic features early in the timeline of disease. We demonstrate the utility of an activity flow modeling approach, which predicts fMRI cognitive task activations in subjects identified as at-risk for Alzheimers disease. The approach makes activation predictions by transforming a healthy aged activation template via the at-risk subjects individual pattern of fMRI resting-state functional connectivity (restFC). The observed prediction accuracy supports activity flow as a mechanism linking age-related alterations in restFC and task activations, thereby providing a theoretical basis for incorporating restFC into imaging biomarker and personalized medicine interventions.

neuroscience↗

bioRxiv2019

Structured event memory: a neuro-symbolic model of event cognition

Humans spontaneously organize a continuous experience into discrete events and use the learned structure of these events to generalize and organize memory. We introduce the Structured Event Memory (SEM) model of event cognition, which accounts for human abilities in event segmentation, memory, and generalization. SEM is derived from a probabilistic generative model of event dynamics defined over structured symbolic scenes. By embedding symbolic scene representations in a vector space and parametrizing the scene dynamics in this continuous space, SEM combines the advantages of structured and neural network approaches to high-level cognition. Using probabilistic reasoning over this generative model, SEM can infer event boundaries, learn event schemata, and use event knowledge to reconstruct past experience. We show that SEM can scale up to high-dimensional input spaces, producing human-like event segmentation for naturalistic video data, and accounts for a wide array of memory phenomena.

neuroscience↗

bioRxiv2018

Dynamic Prediction During Perception of Everyday Events

The ability to predict what is going to happen in the near future is integral for daily functioning. Previous research suggests that predictability varies over time, with increases in prediction error at those moments that people perceive as boundaries between meaningful events. These moments also tend to be points of rapid change in the environment. Eye tracking provides a method for continuous measurement of prediction as participants watch a movie of an actor performing a series of actions. In two studies, we used eye tracking to study the time course of prediction around event boundaries. In both studies, viewers looked at objects that were about to be touched by the actor shortly before the objects were contacted, demonstrating predictive looking. However, this behavior was modulated by event boundaries: looks to to-be-contacted objects near event boundaries were less likely to be early and more likely to be late, compared to looks to objects contacted within events. This result is consistent with theories proposing that event segmentation results from transient increases in prediction error.\n\nSignificance StatementThe ability to predict what will happen in the near future is integral for adaptive functioning, and although there has been extensive research on predictive processing, the dynamics of prediction at the second by second level during the perception of naturalistic activity has never been explored. The current studies therefore describe results from a novel task, the Predictive Looking at Action Task (PLAT) that can be used to investigate the dynamics of predictive processing. Demonstrating the utility of this task to investigate predictive processing, this task was applied to study the predictions made by Event Segmentation Theory, which suggests that people experience event boundaries at times of change and unpredictability in the environment. The results of these studies are of interest to communities investigating the dynamic comprehension and segmentation of naturalistic events and to communities studying visual perception of naturalistic activity.

neuroscience↗

bioRxiv2018

The influence of everyday events on prospective timing "in the moment"

We conducted two experiments to investigate how the eventfulness of everyday experiences influences peoples prospective timing ability. Specifically, we investigated whether events contained within movies of everyday activities serve as markers of time, as predicted by Event Segmentation Theory, or whether events pull attention away from the primary timing task, as predicted by the Attentional Gate theory. In the two experiments reported here, we asked participants to reproduce a previously learned 30 second target duration while watching a movie that contained eventful and uneventful intervals. In Experiment 2, reproduction also occurred during \"blank movies\" while watching a fixation. In both experiments, participants made shorter and more variable reproductions while simultaneously watching eventful as compared to uneventful movie intervals. Moreover, in Experiment 2, the longest reproductions were produced when participants had to watch the blank movies, which contained no events. These results support Event Segmentation Theory and demonstrate that the elapsing events during prospective temporal reproduction appear to serve as markers of temporal duration rather than distracting from the timing task.

animal behavior and cognition↗