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Dartmouth Psychological and Brain Sciences

@dartmouthpbs.bsky.social
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Official account of the Department of Psychological and Brain Sciences at Dartmouth College. Follow for research, learning resources, events, news, and job postings.

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Adam Steel @neurosteel.bsky.social · 23/09/2026
Out today with @pangeli95.bsky.social (co-lead) & @carolinerobertson.bsky.social ! The brain integrates internal thoughts with sensory information. Yet the networks serving functions are viewed as independent. How does the brain integrate across these systems? elifesciences.org/articles/110...
elifesciences.org
Retinotopic coding organizes the interaction between internally and externally oriented brain networks
Internally and externally oriented brain networks are functionally coupled at a voxel scale through a common visuospatial code.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 18/09/2026
"Curiosity really creates common ground across brains.” @dartmouthpbs.bsky.social professor Thalia Wheatley’s co-authored research on curiosity's role in relationships suggests that curiosity can help create consensus across differing perspectives.
upworthy.com
Stanford researchers find a single question could be the key to changing someone's mind
Curiosity goes a lot further than we might think.
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LT @lindseytepfer.bsky.social · 08/09/2026
We don’t just lock on to our first impression of someone and call it a day. Instead, we regularly revise our appraisals as we learn more about them. But *how* do our brains make this process possible? Check out this fresh pre-print to see how we went about answering this question!
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Context Lab @contextlab.bsky.social · 08/09/2026
In our latest study, led by @paxt0n4.bsky.social, we build a geometric framework to ask how our memories change with the passage of time ⏰ Title: Delayed recountings preserve but simplify the semantic geometry of earlier recountings Preprint: osf.io/mhxtd_v1 Code/data: github.com/ContextLab/m... 🧵
osf.io
OSF
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Mark Thornton @markthornton.bsky.social · 08/09/2026
Excited to share this new preprint from @lindseytepfer.bsky.social, @chujunlin.bsky.social, and me, in which we investigate the different ways our brains allow us to change our minds about people! "The neurocomputational mechanisms of naturalistic trait impression updating" osf.io/preprints/ps...
Schematics of scanner and online experimental designs. A) Scanner participants first completed individual difference surveys regarding their demographics, attitudes towards social groups, mood, and personality. In the MRI scanner, they then watched short autobiographical narrative videos. After the scan, they made ratings about the traits of the individuals in the videos they viewed. B) Online participants first made ratings about the traits of the individuals in the videos based on still frame images. They then made continuous ratings of the traits of these individuals over the course of the videos.Analysis schematic. A) Spatiotemporal representational similarity analysis was used to relate patterns of brain activity over the course of SEND videos to i) continuous ratings of the traits of the individuals in those videos, ii) multimodal annotations (face, voice, and speech semantics), and iii) representations learned by neural networks to support computational operations (compression, multimodal fusion, temporal integration, and prediction). B) Intersubject representational similarity analysis was used to relate intersubject correlations in brain activity to individual differences in trait impression updating, demographics, social group attitudes, mood, and personality. Computational operations of trait impression updating. The left column illustrates brain regions within which pattern similarity is uniquely associated with representations learned by neural networks trained to engage in the corresponding computational operation: compression, multimodal fusion, temporal integration, or prediction. The right column illustrates where these effects uniquely statistically mediate the association between brain activity and trait ratings. All results control for the raw annotations of face, voice quality, and speech semantics. Results are significant (p < .05) corrected for multiple comparisons across parcels via maximal statistic permutation testing.Individual differences in trait impression updating. IS-RSA results reflecting where individual differences were associated with ISC while watching SEND videos. A) Reflects where idiosyncratic trait impression updating was correlated with ISC. B) Likewise illustrates where four categories of potentially explanatory individual differences – social group attitudes, participant demographics, participant personality (Big 5), and participant mood (PANAS) predict ISC during SEND video viewing. C) Shows where social group attitudes statistically mediate the association between idiosyncratic trait impressions and ISC. Results are significant (p < .05) corrected for multiple comparisons across parcels via maximal statistic permutation testing.
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Context Lab @contextlab.bsky.social · 13/08/2026
Super excited to announce our next big project: an NSF-funded collaboration with the @exploratorium.bsky.social to build museum exhibits that adapt on-the-fly to visitor interests, goals, and background knowledge! 🧑‍🔬🩻🔬🥼🧪🧬🤓🤖🚀 www.nsf.gov/awardsearch/...
nsf.gov
Award Details - NSF Award Search
Find award details and explore award abstracts and publications.
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Mark Thornton @markthornton.bsky.social · 03/08/2026
Very excited to share this preprint from me, @emmatempleton.bsky.social, @lindseytepfer.bsky.social & @thaliawheatley.bsky.social! "Friends and strangers engage in distinct regimes of body motion synchrony during conversation" osf.io/preprints/ps...
 Forms of body motion synchrony. A) Motion quantity synchrony – synchrony in the amount of motion (orange) people engage in over time. This form of synchrony is agnostic to the direction of this movement, may be positive or negative, occurs at varying time lags, and is not specific to matched body parts across members of the dyad. B) Pseudo-synchrony – motion quantity synchrony between people who are not actually interacting. That is, members of different conversations engaging in similar amounts of motion at similar points in the conversation relative to its initiation. And C) directional synchrony – people moving the same body parts in the same direction (or along the same axis in the opposite direction) at the same time (or at some specific time lag). Mechanisms of synchrony. A) Turn-taking, which causes increases in motion around the time of speaker role exchanges, as participants gesture to hand over or take over the floor. B) Conservation of motion in which one participant moves less when the other moves more, holding the total motion quantity relatively constant over time (note that the total amount of motion across the dyad is similar in the two panels, because one person reduces their motion to balance out the increase in the other’s motion). C) Entrainment, in which mutual following of the same conversational script leads to synchronized movement among people who are not directly interacting (i.e. pseudo-synchrony). Greeting gestures such as the handshakes depicted are one acute manifestation of this entrainment. D) Station-keeping, which maintains proxemic distance and eye level between members of the dyad. This mechanism accounts for directional synchrony, particularly between strangers who feel uncomfortable within each other’s personal space.Motion quantity synchrony among friends and strangers. A) Friends displayed significant positive synchrony in total motion quantity at short time lags (< 2.5 s) and B) this effect generalized across the majority of body part pairs (each line represents one pair). For example, one series of points might represent the synchrony between the amount of motion in one participant’s left hand and the other’s right foot. C) Strangers displayed significant positive synchrony in total motion quantity at short time lags (< 1 s) and significant negative total motion quantity synchrony at longer time lags (2.5 – 16.6 s). D) Again, this effect generalized to most body part pairs.Directional synchrony among friends and strangers. A) Among friends, we observed statistically significant directional synchrony in only two body parts (nose and eye) and only in the vertical axis. B) Among strangers, we observed statistically significant directional synchrony in a large number of body parts in the horizontal, vertical, and depth axes.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 28/07/2026
“We are not getting AI empathy. We are getting a synthesis of human empathy.” @dartmouthpbs.bsky.social professor @markthornton.bsky.social argues AI “empathy” results from the averaging of human responses, not machine feeling.
psychologicalscience.org
Seeking Empathy in the Age of AI
Findings are pushing psychologists to ask not only whether AI can simulate empathy, but what empathy requires in the first place.
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Mark Thornton @markthornton.bsky.social · 23/07/2026
APS (@psychscience.bsky.social) Observer coverage of recent research and perspectives on AI empathy: www.psychologicalscience.org/publications... Including comments from me relating to my recent PoPS article: journals.sagepub.com/doi/full/10....
psychologicalscience.org
Seeking Empathy in the Age of AI
Findings are pushing psychologists to ask not only whether AI can simulate empathy, but what empathy requires in the first place.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 16/07/2026
"From the earliest moments of taking in a new environment, we make radically different choices about what we pay attention to.” @dartmouthpbs.bsky.social professor @carolinerobertson.bsky.social’s new study finds what our eyes seek out can identify us.
earth.com
What catches your eye in new places could identify you
The first things you notice in a new place create unique eye movement patterns that can identify you, highlighting risks from eye tracking.
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Mark Thornton @markthornton.bsky.social · 15/07/2026
Incredibly proud of my first PhD student @lindseytepfer.bsky.social for defending her dissertation yesterday! Lindsey was a founding member of SCRAP Lab, and her presence will always be felt here. We'll miss her greatly, but we're excited for her future endeavours, starting soon with @inquirer.com!
Me & Lindsey
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Mark Thornton @markthornton.bsky.social · 03/07/2026
Now in press at Cortex! "False discovery rate correction promotes confounded neuroimaging designs" Paper 🔓: www.sciencedirect.com/science/arti...
Effect of confound mass on true positive rates under test-wise FDR correction in completely arbitrary data. Confound mass represents how large a confound is in terms of the product of the number of tests it is present in, and its mean effect size across these tests. Results are shown at differing combinations of true effect size, number of tests with true (i.e., non-confound) effects, and sample size. Inflated surface maps of meta-analytic z-statistics from Neurosynth for low-level confounds (top) and high-level cognitive tasks (bottom). Red reflects positive activations, blue reflects negative (de)activations, and darker colors indicate larger z-statistics. Maps are thresholded at |z| = 1 for visualization purposes.The difference in integrated true positive rate between parcel-wise FDR and parcel-wise FWER (y-axis) is plotted as a function of confound effect size. Each point represents 1 out of 5000 studies simulated for each combination of task and confound. Smoothed loess lines are used to better show the overall trends.Effect of FDR-based publication bias on observed confound effects sizes. Simulated meta-analytic confound effect sizes are visualized through violin plots for each combination of task effect and confound effect examined in the neural data simulations. Meta-analyses featuring publication bias (orange) substantially inflate these effect size estimates in all cases, relative to meta-analyses featuring no publication bias (blue). Moreover, this bias was present – and in most cases larger – in the subset of studies that were included in the meta-analysis specifically when the publication bias was based on FDR instead of FWER integrated true positive rates (green).
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 30/06/2026
New research from #Dartmouth professor @carolinerobertson.bsky.social finds your eye movements are so distinctive that AI can identify you by your gaze alone—revealing the "conceptual priorities" that shape what each of us notices in a new scene.
fas.dartmouth.edu
Your Gaze Has a Signature | Faculty of Arts and Sciences
No two people take in a new scene quite the same way, a new Dartmouth study finds, using AI to map where we look.
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Caroline Robertson @carolinerobertson.bsky.social · 12/06/2026
Very excited to share this paper, led by @ajhaskins.bsky.social ! We find that how people look around the world is stable and idiosyncratic — and that these gaze patterns are shaped in part by the conceptual priorities each person brings to a scene. 1/3 www.pnas.org/doi/10.1073/...
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Erica Busch @elbusch.bsky.social · 11/06/2026
Our new paper is out this week in Nature Neuroscience! www.nature.com/articles/s41... We built a BCI that works with the brain's natural geometry — and we found that people could learn to play a video game with their brains in <1 hr of training. This efficiency is groundbreaking & here's why:
nature.com
Human learning of noninvasive brain–computer interfaces via manifold geometry - Nature Neuroscience
Busch et al. use nonlinear neural manifolds to help humans gain rapid control over a noninvasive brain–computer interface, allowing them to learn how to play a video game with real-time fMRI neurofeed...
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Association for Psychological Science @psychscience.bsky.social · 26/05/2026
Meet @esfinn.bsky.social, Assistant Professor of Psychological & Brain Sciences @dartmouthpbs.bsky.social. Finn is a 2026 APS Spence Award recipient whose research focuses on individual variability in brain activity and behavior. www.psychologicalscience.org/publications...
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Emma Templeton @emmatempleton.bsky.social · 15/05/2026
Check out this 4-part series on a really rewarding collaboration with filmmakers @theskindeep.bsky.social We’ve been conducting research on their videos, and they created videos about our research! Excited to see what unfolds as we continue digging deeper together. www.youtube.com/playlist?lis...
youtube.com
The Science of Human Connection - YouTube
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Viola Störmer @violastoermer.bsky.social · 15/05/2026
Hello to everyone coming to @vssmtg.bsky.social: Come see what our lab and collaborators have been working on this past year. - Lots of interesting new work on visual working memory, feature- and object-based attention, cross-modal attention, ensemble perception!
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Context Lab @contextlab.bsky.social · 06/05/2026
Check out our latest collab with Manish Saggar, @richardfbetzel.bsky.social, et al. (lead: Chunyin Siu)! We use TDA to show that 2nd-order (edge) brain interactions more distinctly segregate task connections than other kinds of network patterns. Paper/code/data: www.biorxiv.org/content/10.6...
biorxiv.org
Global topology of brain-wide co-fluctuations links task states, personality, and behavioral symptom dimensions
Functional connectivity in network neuroscience is traditionally characterized using time-averaged correlations between brain regions. While these summaries capture stable large-scale organization, they do not fully reflect the temporal structure of moment-to-moment interactions. Here, we investigate how the order of interaction used to represent brain dynamics shapes the organization recovered from neural data. We compare three interaction representations of fMRI dynamics: regional activation (node time series), pairwise co-fluctuations (edge time series), and higher-order triplet interactions (triangle time series); within a common topological framework using Mapper from topological data analysis (TDA). Across task and resting-state data, Mapper representations derived from pairwise co-fluctuations more distinctly segregate task conditions than activation-based or higher-order representations. This organization reflects structured coordination patterns beyond activation polarity and is driven by high-amplitude interaction events. Beyond task states, modularity quality computed across all Mapper representations is highest for edge time series and selectively associated with stable individual differences: higher modularity relates to higher conscientiousness and lower internalizing and externalizing symptom dimensions. Together, these findings suggest that behaviorally relevant information is reflected in the topology of moment-to-moment brain interactions. Topological analysis of interaction-level dynamics therefore provides a complementary and interpretable framework for linking large-scale neural coordination to cognition, personality, and mental health. ### Competing Interest Statement The authors have declared no competing interest. National Institute of Mental Health, https://ror.org/04xeg9z08, MH127608 Stanford Maternal and Child Health Research Institute, https://ror.org/00yt0ea73, Faculty Scholar Award
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 05/05/2026
According to a new @dartmouthpbs.bsky.social study, what others say about an experience can shape how it actually feels. The findings, published in @pnas.org, show that social information can influence how people experience negative events and bias perceptions of pain and mental effort.
fas.dartmouth.edu
People's Opinions Can Shape How Negative Experiences Feel | Faculty of Arts and Sciences
Study finds what others say can bias perceptions of pain and mental effort.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 01/05/2026
The @nasonline.org has elected @dartmouthpbs.bsky.social professor James Haxby as a member, recognizing his distinguished research in computational cognitive neuroscience, including how thoughts and perceptions can be decoded from brain activity patterns.
fas.dartmouth.edu
James Haxby Elected to the National Academy of Sciences | Faculty of Arts and Sciences
The professor specializes in computational cognitive neuroscience and neural decoding.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 30/04/2026
.@dartmouthpbs.bsky.social researchers highlight the neural underpinnings of a rare face perception disorder in which the brain generates an overwhelming—and false—sense of familiarity, causing everyone, even complete strangers, to seem familiar.
fas.dartmouth.edu
When Every Stranger Feels Like a Friend | Faculty of Arts and Sciences
Dartmouth researchers highlight the neural underpinnings of a rare face perception disorder.
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Dartmouth Psychological and Brain Sciences @dartmouthpbs.bsky.social · 29/04/2026
Congratulations to Dartmouth PBS Professor James Haxby (@haxbylab.bsky.social) on being elected to the National Academy of Sciences!
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 22/04/2026
“The key concept is that not every child learns the same way.” @dartmouthpbs.bsky.social professor Caroline Robertson, director of the #Dartmouth Autism Research Initiative, talks about the prevalence of neurodiversity ahead of a panel with Temple Grandin about young neurodivergent learners.
bostonglobe.com
Temple Grandin returns to her N.H. school with a message for neurodivergent youth: ‘Sky’s the limit’ - The Boston Globe
Grandin considers the early years she spent in N.H. as one of the most formative experiences of her life.
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Mark Thornton @markthornton.bsky.social · 20/04/2026
New paper from me at Perspectives on Psychological Science! "Reframing the Performance and Ethics of Empathic AI: Wisdom of the Crowd and Placebos" I use analogies to two classic psychological effects to recast recent findings about the performance of empathy by LLMs. doi.org/10.1177/1745...
doi.org
Sage Journals: Discover world-class research
Subscription and open access journals from Sage, the world's leading independent academic publisher.
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SANS @sansmeeting.bsky.social · 17/04/2026
Next is @gabefajardo.bsky.social presenting on high dimensional neural representations of facial expressions
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SANS @sansmeeting.bsky.social · 16/04/2026
In the first #SANS2026 session on social learning @csavasegal.bsky.social shows that self-generated interpretations anchor how we remember ambiguous social info, even when others offer a different take, and how neural shifts help us make the shift
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Gabriel Fajardo @gabefajardo.bsky.social · 15/04/2026
I’m thrilled to share that I was awarded the NSF Graduate Research Fellowship! Thanks to all my mentors and lab mates for the incredible support :)
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Context Lab @contextlab.bsky.social · 02/04/2026
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...
context-lab.com
Knowledge Mapper
An interactive tool that maps out everything you know. Answer questions and watch your personalized knowledge map take shape.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 01/04/2026
.@dartmouthpbs.bsky.social professor Brad Duchaine discusses his research into prosopagnosia, also known as face blindness, and prosopal metamorphopsia, a condition in which the perception of faces are distorted, on a recent episode of The Face with Masoud Saman.
podcasts.apple.com
Episode 3: When Faces Look Distorted |The Brain Disorder You’ve Never Heard Of w/ Dr. Brad Duchaine)
Podcast Episode · The Face with Masoud Saman · March 7 · 33m
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Shelley Warlow @accumbenshelley.bsky.social · 30/03/2026
We are hiring a post-bac fellow in Psychological & Brain Sciences at Dartmouth! This is a unique opportunity to collaborate across the labs of @katenautiyal.bsky.social, Kyle Smith, and myself. Please apply and share widely: apply.interfolio.com/182417
apply.interfolio.com
Apply - Interfolio {{$ctrl.$state.data.pageTitle}} - Apply - Interfolio
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 20/03/2026
"These findings have important implications for how people interpret others' experiences.” A new study by @dartmouthpbs.bsky.social professors Alireza Soltani and Tor Wager and Aryan Yazdanpanah, Guarini, shows how social information can change how people experience pain.
earth.com
What others say about pain shapes how our brain experiences it
New research from Dartmouth College shows that hearing about others’ experiences can change how people feel pain, effort, and difficulty.
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Emily Finn @esfinn.bsky.social · 16/03/2026
Very happy that this paper from our lab is now out in @pnas.org! What happens when the *same* person experiences the *same* information with a *different* interpretation? Nearly the whole 🧠—well, at least nearly all association cortex—changes how it represents that information! tinyurl.com/p8chj2j7
tinyurl.com
PNAS
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...
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Kate Nautiyal @katenautiyal.bsky.social · 16/03/2026
Please spread the word about a postbac position in Behavioral Neuroscience at Dartmouth with me, Shelley Warlow, and Kyle smith. The postbac will contribute to collaborative projects across the three labs aimed at studying the neuroscience of motivation and reward learning.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 06/03/2026
"I find that particularly exciting, because it reframes the amygdala not just as a fear-related structure, but as a key contributor to flexible cognition and behavior.” @dartmouthpbs.bsky.social professor Alireza Soltani discusses his recent study on the role of the amygdala.
thedebrief.org
Our Brain's “Fear Center” May Guide Complex Learning Decisions, New Research Reveals
The brain’s primitive “fear center” may be much more than that, according to new research on the amygdala.
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Alexis Cameron @alexismcameron.bsky.social · 25/02/2026
Excited to share that our lab will be presenting multiple projects at SPSP 2026! If you’re interested in social perception, race talk, intergroup dynamics, or collective action — come check us out! #SPSP2026 #SocialPsychology #PersonalityPsychology #AcademicResearch #RaceTalk
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 25/02/2026
Professor @esfinn.bsky.social of @dartmouthpbs.bsky.social received a 2026 Janet Taylor Spence Award for Transformative Early-Career Contributions from @psychscience.bsky.social for her groundbreaking work investigating the neural underpinnings of human behavior and cognition. bit.ly/4scvVxL
A photo of Emily Finn, with text that reads, “Emily Finn, assistant professor of Psychological and Brain Sciences. Janet Taylor Spence Award for Transformative Early-Career Contributions.”
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Dartmouth Psychological and Brain Sciences @dartmouthpbs.bsky.social · 23/02/2026
Congratulations to @dartmouthpbs.bsky.social Prof Emily Finn (@esfinn.bsky.social) on winning the APS Spence Award!
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Yong Hoon Chung @yonghoonchung.bsky.social · 09/02/2026
New preprint with @SamJung @timbrady.bsky.social and @violastoermer.bsky.social: osf.io/preprints/ps.... Here we uncover what might be driving the “meaningfulness benefit” in visual working memory. Studies show that real objects are remembered better in VWM tasks than abstract stimuli. But why? 1/
osf.io
OSF
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Mark Thornton @markthornton.bsky.social · 11/02/2026
New preprint from Lindsey Tepfer (@ltjaql.bsky.social) and me! We silenced portions of internal monologues in two films to manipulate participants' access to characters' thoughts. Using ISC and RSA, we found that this aligned later neural processing of the narrative & encoding of trait impressions.
Figure 1. Experimental stimuli and paradigm. 1A. Manipulation timeline. Each video features a total of 12 IM moments, half of which were silenced in version 1, and the other half silenced in version 2. This produces two versions of each video where only half of the IMs are audible to the participant. 1B. Voice removal. Background sounds were preserved in both versions, regardless of IM presence. 1C. fMRI paradigm. Participants were randomly assigned a version and watched both videos in a counter-balanced order. 1D. Afterwards, they made trait ratings on each video’s main character in random order before rating them on subsequent traits. Figure 2. Scanner and online participant trait rating results. A. Scanner participants arrive at similar conclusions about characters across versions by the end of each video. B. Trait ratings at the end of the videos are correlated between online and scanner participants. C. The IM manipulation had a significant effect on the trait ratings across the duration of the videos, such that different versions led to different trait impressions. D. Participants who saw different versions changed their ratings for both clip types but changed to a greater degree after seeing the IM segments relative to the NIM.  Figure 3. ISC results. Gaining access to the same mental state knowledge in earlier IM clips led to significantly (p < .05, corrected) more aligned neural activity in subsequent NIM clips across a wide swath of the temporal lobe, as well as the frontal pole and SPL. Figure 4. Representational similarity analysis results. 4A. RSA pipeline.  Clip-specific patterns of brain activity were correlated across movies within segment type (NIM or IM) to create a correlation distance matrix for each participant. Corresponding trait ratings were partitioned into components specific to each of the two versions of each film or shared across both versions. RDMs based on those traits were used to predict the neural RDMs. The resulting coefficients were sorted into matched (version), unmatched (version), and shared across version, and inference was performed via t-tests across participants. See methods section for further details of this analysis. 4B. Prior trait rating results. 1. While watching IM clips of the same version, the prior trait ratings predict activity in the bilateral A1, STS, STG, and right VLPFC. 2. Prior trait rating predicts activity in these regions again in the same-version NIM clips. 3. Across the two versions, while watching the NIM clips, the prior trait ratings predicted activity in the right occipitotemporal cortex. 4C. Trait updating results. 1. While watching NIM clips, the right STS & MTG predict version-matched trait updating. 2. In the unmatched NIM clips, STS & MTG again predict trait updating. 3. Across the two versions, the precuneus and LOC show pattern similarity for trait updating in participants.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 05/02/2026
.@dartmouthpbs.bsky.social professor @stolkarjen.bsky.social's latest research highlights why individualized communication approaches are crucial, with insights that could improve understanding of autism.
psychologytoday.com
Meeting People as Individuals, Not Assumptions
Why communication depends on updating our assumptions about others.
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Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · 26/01/2026
Congrats to @dartmouthpbs.bsky.social professor Tor Wager, who received the Atkinson Prize in Psychological and Cognitive Sciences from @nasonline.org. The prize recognizes Wager's pioneering research on the mind-body connection and innovative neuroimaging approaches. bit.ly/4k0glSM
Photo of Tor Wager with overlaid text, “Tor Wager, Diana L. Taylor Distinguished Professor in Neuroscience. Atkinson Prize in Psychological and Cognitive Sciences.”
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Jeremy Manning @jeremyrmanning.bsky.social · 07/01/2026
Excited to be teaching a new undergraduate course on Models of Language and Conversation this term! Check it out here: context-lab.com/llm-course/ I've added lots of fun interactive demos of chatbots and NLP techniques that let students dig into the approaches.
context-lab.com
Models of Language and Communication - PSYC 51.17
Course materials for PSYC 51.17: Language Models from Scratch - Dartmouth College
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Jeremy Manning @jeremyrmanning.bsky.social · 11/01/2026
I made a quirky little web app to help guide your lucid dreams: context-lab.com/dream-stream/ It's kind of like a "netflix" or "spotify" for lucid dreaming-- you select different narratives to form a playlist, and then it uses your device's microphone to start playing when it detects you're in REM.
context-lab.com
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Kate Nautiyal @katenautiyal.bsky.social · 21/12/2025
🧠 Why it matters 🧠 -The results challenge a prevailing view that 5‑HT2A activation alone drives psilocybin’s therapeutic actions. -Highlights the importance of polypharmacology 🥳, and points to the 1B receptor as a target for non‑hallucinogenic antidepressant and anxiolytic pharmacotherapies.
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Kate Nautiyal @katenautiyal.bsky.social · 21/12/2025
New paper drop! 🧠💊 Our new paper out in Molecular Psychiatry shows that the serotonin 1B receptor is important for the neural and antidepressant/anxiolytic behavioral responses to psilocybin in mice. www.nature.com/articles/s41...
nature.com
The serotonin 1B receptor is required for some of the behavioral effects of psilocybin in mice - Molecular Psychiatry
Molecular Psychiatry - The serotonin 1B receptor is required for some of the behavioral effects of psilocybin in mice
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Reposted by Dartmouth Psychological and Brain Sciences
Context Lab @contextlab.bsky.social · 06/11/2025
Remember when grinding leetcode was still a thing? If you'd like to hone your coding skills, or even just return to that simpler time for nostalgia's sake, you might enjoy this project from our group: github.com/ContextLab/l... Happy hacking! 👩‍💻
github.com
GitHub - ContextLab/leetcode-solutions: Leetcode discussions, brainstorming, musings, and solutions
Leetcode discussions, brainstorming, musings, and solutions - ContextLab/leetcode-solutions
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Reposted by Dartmouth Psychological and Brain Sciences
Kate Nautiyal @katenautiyal.bsky.social · 12/11/2025
Hope to see all of the serotonin enthusiasts at the ISSR mixer at SfN on Monday (people who find dopamine rewarding are welcome too). register here: pci.jotform.com/form/2528274...
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Reposted by Dartmouth Psychological and Brain Sciences
Context Lab @contextlab.bsky.social · 28/10/2025
🚨 New preprint alert! We use trained-from-scratch GPT-2 models to characterize & capture the unique writing styles of individual authors. We also develop a new LLM-based relative stylometric measure. Paper: arxiv.org/abs/2510.21958 Code/data: github.com/ContextLab/l... 🤗: huggingface.co/contextlab
A plot showing a 3D projection of 8 "authors" (each represented with a differently colored and labeled dot). Stylistic distances between authors are reflected by spatial distances in the plot.
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Reposted by Dartmouth Psychological and Brain Sciences
Jonathan Phillips @jsphillips.bsky.social · 23/10/2025
We're excited to announce that Cognitive Science at Dartmouth is recruiting PhD students to work collaboratively with me, Steven Frankland, and Fred Callaway. Come study the principles and mechanisms that enable us to understand, plan, and act in the world! Info: sites.dartmouth.edu/cogscigrad/
sites.dartmouth.edu
Cognitive Science Graduate Admissions – Information about graduate admissions from the cognitive science faculty
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