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Rising Stars Session

Saturday, March 29, 2025, 1:00 – 3:00 pm EDT, Constitution Ballroom
Moderator: Deepu Murty, University of Oregon

Talk 1, 1:00 pm

Abstract Internal Models for Sensorimotor Planning

Samuel McDougle¹; ¹Yale University

Internal models enable efficient motor planning by predicting the sensory consequences of movements. However, it is not well understood where and how these models are represented neurally, independent from lower-level features of movement control. We developed an fMRI reaching task where, in certain contexts, participants made the same movements to reach the same sensory goal, but under differently structured sensory perturbations (visuomotor rotation versus mirror reflection). This caused participants to plan identical movements using distinct abstract internal models, despite lower-level features (e.g. target locations and reaching kinematics) being identical. This allowed us to analyze BOLD data during motor planning to localize abstract internal models in the brain via decoding analyses. Our results help clarify where and how abstract internal models for movement are represented in the brain and reveal new clues about the neural correlates of the cognitive-motor interface.

Talk 2, 1:15 pm

Not just self-control: links between memory and temporal discounting

Karolina Lempert¹; ¹Adelphi University

Temporal discounting, the tendency to prefer smaller, sooner rewards over larger, later rewards, is a universal phenomenon. Yet people vary drastically in their temporal discounting rates, which reflect the extent to which they can tolerate delays. Higher temporal discounting rates, which indicate a relative preference for more immediate rewards, are associated with gambling, drug abuse, and other risky behaviors. It has long been assumed that high temporal discounting rates emerge from poor cognitive control, but evidence for this idea is scarce and mostly indirect. Recently, experimental research showing that episodic future thinking reduces temporal discounting has led to an increased interest in the role of the episodic memory system in this choice process. However, it is unknown if (and how) episodic memory contributes to individual differences in discounting. Here I will argue that temporal discounting rates are shaped by people’s concepts of time, which are formed via episodic memory processes. I will present some preliminary findings from my lab that support this idea. We find that individual differences in event segmentation – which influences memory for time duration – are associated with temporal discounting rates, such that people who segmented an audio narrative more normatively were more future-oriented. Moreover, people with more variability in pupil-linked arousal during time intervals (1) remember those intervals as longer, and (2) are less willing to wait for future rewards. This research advances our understanding of the adaptive functions of episodic memory, by demonstrating how it may be foundational to the formation of intertemporal preferences.

Talk 3, 1:30 pm

Respiration modulates sleep oscillations and memory reactivation in humans

Thomas Schreiner¹; ¹Department of Psychology, Ludwig-Maximilians-Universität, München, Germany

The beneficial effect of sleep on memory consolidation relies on the precise interplay of slow oscillations (SOs) and spindles. However, whether these rhythms are orchestrated by an underlying pacemaker has remained elusive. Here, I will argue that respiration, known to influence brain rhythms and cognition during wakefulness, might represent such a scaffold rhythm, enabling the precise coordination of sleep-related oscillations and memory reactivation in humans. We recorded electroencephalography and respiration throughout an experiment in which participants (N = 20) acquired associative memories before taking a nap. Our results reveal that respiration modulates the emergence of sleep oscillations. Specifically, slow oscillations, spindles as well as their interplay (i.e., SO-spindle complexes) systematically increase towards inhalation peaks. Moreover, the strength of respiration – SO-spindle coupling is linked to the extent of memory reactivation (i.e., classifier evidence in favour of the previously learned stimulus category) during SO-spindles. These results identify a clear association between respiration and memory consolidation in humans and highlight the role of brain-body interactions during sleep.

Talk 4, 1:45 pm

Hierarchical predictive coding in language: Limits and future directions

Trevor Brothers¹; ¹North Carolina A&T State University

Language is inherently hierarchical, and the brain must transfer sensory information from lower to higher cortical areas as we process the meaning of words and sentences. In my recent work, hierarchical predictive coding has provided a useful conceptual framework for understanding 1) how sensory inputs activate higher-order conceptual representations and 2) why language inputs give rise to specific patterns of evoked neural activity over time. Here, I present an implemented predictive coding model of the N400 that links this neural response to prediction error at the lexico-semantic level of representation. Next, I discuss late (post-N400) neural activity, which I interpret as a prediction error at the level of the discourse or situation model. Finally, I present event-related potential data from reading comprehension that demonstrates the limits of predictive coding. Specifically, I show that predictive context has no influence on early visual responses (0-200ms), and I discuss why these early processing stages may be informationally encapsulated.

Talk 5, 2:00 pm

How is task knowledge organized along an axis of complexity?

Jiefeng Jiang¹ (jiefeng-jiang@uiowa.edu); ¹University of Iowa

One hallmark of human intelligence is the ability to perform a diversity of complex tasks, such as driving a car, cooking a meal, or making financial decisions. How we live our lives depends heavily on this task knowledge, which encompasses the tasks we have learned to perform (i.e., our skillsets) and how well we perform them. Our lab works on a fundamental question in cognitive neuroscience: How does the brain organize and implement task knowledge to achieve adaptive behaviors? Specifically, we are interested in how different tasks can be organized based on their complexity. I will present two projects in this line of research. In the first project, we use theories of associative memory to study how simple tasks can be used as building block to facilitate the learning of complex tasks. We show that the brain not only encodes associations between subtasks of a complex task but also accelerates the learning of a novel complex task through associative inference. In a second project, we demonstrate how the brain decomposes a complex task into simple stimulus-response associations through practice. I will also introduce how we use computational modeling and tools of dynamic systems in these projects.

Talk 6, 2:15 pm

Neural mechanisms of attending to moments in time

Rachel Denison^1,2, Karen Tian^1,2, Jiating Zhu¹, David Heeger², Marisa Carrasco²; ¹Boston University, ²New York University

Our brains receive a continuous flow of sensory information but cannot process all of it. Attention allows us to prioritize the information that is most relevant for our behavioral goals. We can attend not only to locations in space but also to moments in time when we expect something relevant to appear. Here in two studies we investigated the neural mechanisms of attending to moments in time using MEG. Participants were cued to attend to one of two sequential grating targets with predictable timing. The first study used time-resolved steady-state visual evoked responses (SSVER) to investigate how temporal attention modulates anticipatory visual activity. In the pre-target period, visual activity measured with a background SSVER probe steadily ramped up as the targets approached. Furthermore, we found a low-frequency modulation of visual activity, which shifted approximately 180 degrees in phase according to which target was attended. The second study used time-resolved decoding and source reconstruction to examine how temporal attention affects the dynamics of target representations. Temporal attention to the first target enhanced its orientation representation within a left fronto-cingulate region just before the second target appeared, perhaps protecting it from interference from the second target within the visual cortex. Together these studies reveal how temporal attention flexibly shapes pre-target periodic dynamics and post-target routing of stimulus information to select a task-relevant stimulus within a sequence.

Talk 7, 2:30 pm

The default network prioritizes social memory consolidation during rest

Meghan Meyer¹; ¹Columbia University

Sociality is central to human experience—we rely on others for survival and navigate complex networks to thrive. Are there brain mechanisms that help us quickly learn about our social world? This talk reviews two recent fMRI studies testing whether social information is prioritized during memory consolidation during rest. Study 1 used the documentary Samsara, featuring real people and places. Participants watched “social” and “nonsocial” scenes, normed to control for confounding factors (e.g., valence, narrative processing). Afterward, they completed a rest scan and a surprise memory test. Participants showed better social (vs. nonsocial) memory performance, which was driven by neural pattern reinstatement during early rest in the dorsomedial prefrontal cortex (DMPFC), a key default network node—supporting a temporal “prioritization” account. Study 2 found that individual differences in default network connectivity during early rest predicted what features of social stimuli participants recall, again pointing to temporal prioritization. Together, these findings suggest portions of the default network prioritize social memory consolidation, influencing both how much and which social information we retain. This work updates theories of memory consolidation, which have largely overlooked social prioritization, and advances understanding of default network function. More broadly, it highlights our intrinsic drive to comprehend the social world.