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Nakwon Rim

@nwrim.bsky.social

Ph.D. student at the University of Chicago Psychology Department interested in what information we retain and discard, usually in the context of social information.

4 Posts89 Follower134 Folgt
Yuan Chang Leong@ycleong.bsky.social · 6d ago

Thank you for this feature! I'm admittedly awkward on video, but I really enjoyed working on the spotlight piece and taking a bigger picture view of my research trajectory!

Association for Psychological Science@psychscience.bsky.social · 6d ago

Meet @ycleong.bsky.social, assistant professor at the University of Chicago. His research focuses on how social context and affect construct subjective experience. Leong is also a 2026 APS Spence Award recipient www.psychologicalscience.org/publications...

Nakwon Rim@nwrim.bsky.social · 3mo ago

Looking forward to reading this preprint! I saw this project as a poster at VSS last year, and it was one of the most thought-provoking posters I’ve seen. It even prompted me to update my face memorability experiments, so I’m excited to think through how it connects with my results, too!

Joey Saito@jsaito25.bsky.social · 3mo ago

Memorability as an Emergent Property: How Representational Structure Creates Apparent Intrinsic Effects osf.io/preprints/ps...

Nakwon Rim@nwrim.bsky.social · 4mo ago

New paper in @commspsychol.nature.com, with @ycleong.bsky.social, Marc Berman, and @joshcjackson.bsky.social! Two-sentence summary: Political pundits often talk as if partisans are divided in how they feel about political issues, as in “Democrats love abortion” or “Republicans hate immigrants.” 1/2

Communications Psychology@commspsychol.nature.com · 4mo ago

This study finds partisan language to be less affectively divided over political issues than identity labels, suggesting meaningful affective alignment on contentious issues despite partisan animosity. @nwrim.bsky.social @joshcjackson.bsky.social @ycleong.bsky.social www.nature.com/articles/s44...

Hayoung Song@hayoungsong.bsky.social · 12mo ago

Preprint⭐ Our attention changes over time and differs across contexts—which is reflected in the brain🧠 Fitting a dynamical systems model to fMRI data, we find that the geometry of neural dynamics along the attractor landscape reflects such changes in attention! www.biorxiv.org/content/10.1...

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 mechan...

biorxiv.org

Noga Zaslavsky@nogazs.bsky.social · 12mo ago

If you missed us at #cogsci2025, my lab presented 3 new studies showing how efficient (lossy) compression shapes individual learners, bilinguals, and action abstractions in language, further demonstrating the extraordinary applicability of this principle to human cognition! 🧵 1/n

Yuan Chang Leong@ycleong.bsky.social · last yr.

CASNL member Jadyn Park @jadynpark.bsky.social presenting her work on arousal, functional network and memory during narrative perception at #SANS2025 Preprint here: www.biorxiv.org/content/10.1...

Emotional arousal enhances narrative memories through functional integration of large-scale brain networks

Emotional events tend to be vividly remembered. While growing evidence suggests that emotions have their basis in brain-wide network interactions, it is unclear if and how these whole-brain dynamics c...

biorxiv.org

SANS@sansmeeting.bsky.social · last yr.

First up is Jayden Park, discussing "Autonomic arousal predicts functional network integration and memory performance during story listening"

Jin Ke@jinke.bsky.social · last yr.

Now out in Plos Computational Biology! We identified a generalizable neural signature of emotional arousal across contexts and individuals during movie watching. work with the best team: @hayoungsong.bsky.social @Zihan Bai @monicarosenb.bsky.social @ycleong.bsky.social dx.plos.org/10.1371/jour...

Dynamic brain connectivity predicts emotional arousal during naturalistic movie-watching

Author summary This study explores how the brain represents two key dimensions of emotional experience: valence (how positive or negative an experience feels) and arousal (the level of emotional activ...

dx.plos.org

Hayoung Song@hayoungsong.bsky.social · last yr.

If you are curious about the brain🧠 on causal inference, insight💡, memory retrieval, and narrative comprehension🎬, this will be the one. work by dream team @jinke.bsky.social Rhea Madhogarhia @ycleong.bsky.social @monicarosenb.bsky.social ⭐

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · last yr.

Cortical reinstatement of causally related events sparks narrative insights by updating neural representation patterns https://www.biorxiv.org/content/10.1101/2025.03.12.642853v1

Chong Zhao@zhaochong.bsky.social · last yr.

Attention here! We found ind. diff. & fMRI evidence that sustained attention is more closely related to long term memory than to attentional control. With the best team @monicarosenb.bsky.social @edvogel.bsky.social @annacorriveau.bsky.social @jinke.bsky.social

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · last yr.

Sustained attention is more closely related to long-term memory than to attentional control https://www.biorxiv.org/content/10.1101/2025.03.13.643171v1

Jadyn Park@jadynpark.bsky.social · last yr.

Remember what your partner said during a heated argument? Or the rush of getting your first job offer? Why do these emotionally arousing moments stick? Across 3 studies, and 3 arousal measures, we found that emotional arousal enhances memory encoding by promoting functional integration in the 🧠 1/🧵

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · last yr.

Emotional arousal enhances narrative memories through functional integration of large-scale brain networks https://www.biorxiv.org/content/10.1101/2025.03.13.643125v1

Ziwei Zhang@zz112.bsky.social · 2y ago

Out now in @naturehumbehav.bsky.social: We developed a generalizable brain network model predicting moment-to-moment surprise. This edge-fluctuation-based predictive model (EFPM) of surprise works across tasks, from adaptive learning to watching basketball games or cartoons! rdcu.be/d4y3g

Brain network dynamics predict moments of surprise across contexts

Nature Human Behaviour - Zhang and Rosenberg built a model that predicts surprise from brain network dynamics measured with fMRI revealing similarities across distinct contexts (task learning,...

rdcu.be