Now out in PNAS with @jaeyoungson.bsky.social, Alice Xia, @apaxon.bsky.social & @orielf.bsky.social. Medial temporal lobe encodes predictive representations of people's real-world social networks which afford them key advantages in social navigation. www.pnas.org/doi/10.1073/... 🧵
Posts by Bryan Hong
Curious what a representation of "everything" you know might look like? Wonder how you might fill it in?
Check out our demo and paper (led by @paxt0n4.bsky.social and now out in @natcomms.nature.com ), or read on to learn more!
Demo: context-lab.com/mapper/
Paper: www.doi.org/10.1038/s414...
New preprint! ✨ Do you and your partner have made-up words ("eggy" to mean awkward)? Do you and your bestie have an anecdote you love to tell together (that time one of you tripped over an acorn)? Do you and your closest colleague have a cherished ritual (weekly lunch at "the usual spot")? 🧵
Clarifying the conceptual dimensions of representation in neuroscience — a Perspective by Stephan Pohl, Edgar Y. Walker, David L. Barack, Jennifer Lee, Rachel N. Denison, Ned Block, Florent Meyniel & Wei Ji Ma
www.nature.com/articles/s41...
1/ 🚨 New preprint
Key Moments Scaffold the Semantic Structure of Narratives
Using spoken recall and annotations from three naturalistic datasets with topic modeling, we ask: which parts of a narrative contribute most to its semantic structure and subsequently memory?
Preprint: osf.io/dcfvw
🚨 New paper! Think of a place you feel deeply attached to. When you're in that place, do you feel like your life is more meaningful? New work from @ashleykrause.bsky.social suggests you probably do!
Just accepted at Journal of Environmental Psychology, we find places can give our life meaning 🧵
Are episodic and semantic memory really that different? Using closely matched tasks, we found no substantial neural differences between recalling personal experiences and general knowledge: https://www.nature.com/articles/s41562-025-02390-4
How do we balance external attention to the outside world and internal attention to our thoughts & memories?
We review evidence that external and internal attention can compete, unfold concurrently, or cooperate!
Loved working on this with @samversc.bsky.social & @tobiasegner.bsky.social!
What if we could tell you how well you’ll remember your next visit to your local coffee shop? ☕️
In our new Nature Human Behaviour paper, we show that the 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗮 𝘀𝗽𝗮𝘁𝗶𝗮𝗹 𝗿𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 can be measured with neuroimaging – and 𝘁𝗵𝗮𝘁 𝘀𝗰𝗼𝗿𝗲 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝘀 𝗵𝗼𝘄 𝘄𝗲𝗹𝗹 𝗻𝗲𝘄 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝘀 𝘄𝗶𝗹𝗹 𝘀𝘁𝗶𝗰𝗸.
Abstract When we empathize with someone going through something, we often draw on our past experiences with the someone and the something. These kinds of experiences ground "thick empathy", a form of empathy that has been largely overlooked in the psychology and neuroscience literature. Consider how a mother, empathizing with her daughter about to give birth, can draw on her own experience of childbirth, and her relationship with her daughter, to deeply grasp what her daughter is going through in a way that others who lack those experiences cannot. I argue that thick empathy deserves more empirical attention because it is associated with well-being and helps us build networks of effective mutual social support. My analysis highlights novel risks and dilemmas posed by "empathy machines" that promise to enhance or even replace human empathy and are becoming increasingly popular as a potential solution to widespread loneliness. Even when empathy machines provide value to individuals, their widespread adoption risks imposing collective emotional and epistemic costs that ultimately make it harder for us to empathize well. Keywords: empathy, understanding, experience, thick description, ethnography, phenomenal knowledge, interpersonal knowledge, virtual reality, artificial intelligence, chatbots
New preprint: Empathy, Thick and Thin
papers.ssrn.com/sol3/papers....
It is perhaps foolhardy to attempt to say something new about a topic as widely studied as empathy. I tried anyway! 1/
Excited to announce that I'll be officially starting a new role as an Assistant Professor at the University of Guelph as of today—looking forward to working with all the amazing students, faculty, and members of the Guelph community!! ✨
I'm surprised I only came across it now, but this review on improving communication in data visualization is excellent.
journals.sagepub.com/doi/10.1177/...
We strongly suggest using the following labels: praise: Praises highlight something positive. Try to leave at least one of these comments per review. Do not leave false praise (which can actually be damaging). Do look for something to sincerely praise. nitpick: Nitpicks are trivial preference-based requests. These should be non-blocking by nature. suggestion: Suggestions propose improvements to the current subject. It’s important to be explicit and clear on what is being suggested and why it is an improvement. Consider using patches and the blocking or non-blocking decorations to further communicate your intent. issue: Issues highlight specific problems with the subject under review. These problems can be user-facing or behind the scenes. It is strongly recommended to pair this comment with a suggestion. If you are not sure if a problem exists or not, consider leaving a question. todo: TODO’s are small, trivial, but necessary changes. Distinguishing todo comments from issues: or suggestions: helps direct the reader’s attention to comments requiring more involvement. question: Questions are appropriate if you have a potential concern but are not quite sure if it’s relevant or not. Asking the author for clarification or investigation can lead to a quick resolution. thought: Thoughts represent an idea that popped up from reviewing. These comments are non-blocking by nature, but they are extremely valuable and can lead to more focused initiatives and mentoring opportunities. chore: Chores are simple tasks that must be done before the subject can be “officially” accepted. Usually, these comments reference some common process. Try to leave a link to the process description so that the reader knows how to resolve the chore. note: Notes are always non-blocking and simply highlight something the reader should take note of.
I recently discovered Conventional Comments (conventionalcomments.org) for providing a pseudo-standard set of labels for feedback and just tried it for an article review and it was really helpful to specify issues vs. thoughts vs. suggestions, etc. Hopefully it's helpful for the authors too!
Thrilled to announce a new paper out this weekend in
@cognitionjournal.bsky.social.
Moral psychologists almost always use self-report scales to study moral judgment. But there's a problem: the meaning of these scales is inherently relative.
A 2 min demo (and a short thread):
1/7
A memory can be represented at different levels of granularity, from highly specific to generalized.
Different representational formats of a memory can be used at different times or in different contexts, and draw on different neural representations.
doi.org/10.31234/osf...
An arrow with a LaTeX equation
Trigonometric functions and a unit circle
A bivariate change model with structured residuals
A hierarchical model of cognitive abilities
Now on CRAN, ggdiagram is a #ggplot2 extension that draws diagrams programmatically in #Rstats. Allows for precise control in how objects, labels, and equations are placed in relation to each other.
wjschne.github.io/ggdiagram/ar...
On the left: an illustration from Brooke's 1904 rendition of Goldilocks and the Three Bears, where Little bear discovers their favourite chair is broken 😲. On the right, a sketch of what a corresponding "situation model" might contain.
How might stories shed light on brain function? Check out this opinion piece by @alexbarnett.bsky.social and I about the DMN and "situation models" -- our understanding of the current "state of affairs" in a story (or even experience).
www.sciencedirect.com/science/arti...
We make predictions based on general knowledge and/or specific memories. Different brain areas are active when these distinct predictions are violated – and hippocampus selectively responds to prediction errors based on episodic memory.
Cool work by @chrismbird.bsky.social @ayab.bsky.social et al!
Happy to share "The Dynamics of Caregiver Unpredictability Shape Moment-to-Moment Infant Looking During Dyadic Interaction," out now in Child Development thanks to a large team of people I worked on this with! srcd.onlinelibrary.wiley.com/doi/pdfdirec...
📣 New preprint from the SCIMaP team!
Across three studies, we show that communicating the economic impact of NIH funding cuts—especially with interactive quizzes and maps—decreases approval and motivates action to oppose the cuts, across the political spectrum. 🧵 1/8
osf.io/preprints/ps...
New paper with @mujianing.bsky.social & @prestonlab.bsky.social! We propose a simple model for human memory of narratives: we uniformly sample incoming information at a constant rate. This explains behavioral data much better than variable-rate sampling triggered by event segmentation or surprisal.
Comment: Rethinking behavior change interventions in policymaking
📢 New commentary out today in Nature Human Behaviour!
We argue that behavior change interventions often suffer from a one-sided success focus. But failures may reveal structural barriers people face.
🔗 rdcu.be/ex8hR
#BehavioralScience #PublicPolicy
Excited to ✨share✨ that our paper on ✨sharing✨ is published! Across 3 studies that build on one another, we show that perceived alignment with one's peers increases the likelihood of information sharing.
www.nature.com/articles/s41...
Experimentology cover: title and curves for distributions.
Experimentology is out today!!! A group of us wrote a free online textbook for experimental methods, available at experimentology.io - the idea was to integrate open science into all aspects of the experimental workflow from planning to design, analysis, and writing.
Sharing our new paper published today in Nature Communications. In my view, this is our clearest demonstration to date that something profoundly changes in how infants encode the world around them before and after the emergence of self-representation. www.nature.com/articles/s41...
Proud to share the first preprint of my PhD w/ @barense.bsky.social & Mursal Jahed:
“Putting the testing effect to the test in the wild: Retrieval enhances real-world memories and promotes their semantic integration while preserving episodic integrity”
See thread! 🧵 osf.io/preprints/ps...
In our first “Postdoc perspectives” essay, @fleabrained.bsky.social and @maribel-patino.bsky.social explain how grassroots organizations led by trainees are stepping up to provide career and mentorship guidance for neuroscience students from marginalized backgrounds.
#neuroskyence
bit.ly/4csFx0B
CNS 2025 presentations from the Barense lab
If you're at #CNS2025 come check out our lab's Sunday line-up of posters from @catalinayang.bsky.social, @bryanhong.bsky.social, @nellymatorina.bsky.social, and @laurenhomann.bsky.social.
Are you doing EMA research and wonder how to go about it? In recent work we've adressed some open questions and challenges, here is a brief summary of papers and materials.
🧵 #PsychSciSky 🧪 #StatsSky
Thrilled to see this paper out in @naturehumbehav.bsky.social after years of work by Drs. @diamondn.bsky.social and @stefsimpson.bsky.social, with Drs. Stuart Fogel, Daniel Baena, and Brian J Murray!
@baycrestfoundation.bsky.social