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Mark Thornton

@markthornton.bsky.social
2.2K followers 753 following 328 posts

Social neuroscientist studying how people understand and predict each other. Assistant Professor at Dartmouth College. markallenthornton.com

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Mark Thornton @markthornton.bsky.social · 20h
What would you want to see in a textbook (free, online, jupyter/marimo style) about quantitative/computational approaches for analyzing naturalistic social interactions (e.g., face-to-face conversations)? I'm in the early phases of drafting one and would value external input on its audience's needs.
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Rob Chavez @robchavez.bsky.social · 29/09/2026
Our latest paper led by Taylor Guthrie with former undergrad RA Aussie Frost. We show that multivariate fMRI signals can decode the identity of specific individuals within the DMN and in the absence of visual features or other lower-level sensory information. link.springer.com/article/10.3...
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Mark Thornton @markthornton.bsky.social · 27/09/2026
There are still 3 months left in 2026, and I have already reviewed significantly more papers than in any past calendar year. Yet simultaneously I have had to decline more review requests than ever. Not saying it's all AI's fault, but I have encountered some very blatant and counterproductive uses.
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wimpouw @wimpouw.bsky.social · 21/09/2026
Here we go! We can finally share what Sharjeel Shaikh @sharjeelshaikh has been leading the work on with us! Consider participating in our detection challenge
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SANS @sansmeeting.bsky.social · 31/08/2026
Symposium submissions are now open for #SANS2027! Submissions must be made through the online submission portal by 23:59 (Eastern Time) on Tuesday, October 13, 2026. More details here: socialaffectiveneuro.org/symposia-sub...
socialaffectiveneuro.org
Symposia Submission - Social Affective Neuroscience Society
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Benedek Kurdi @benedek.bsky.social · 17/09/2026
🚀 Project Implicit’s critical work continues! Our website remains fully operational 24/7, collecting data and launching new studies. We are finalizing a new organizational structure to carry our research and educational mission forward. Thank you to our global community. ➡️ implicit.harvard.edu
September 17, 2026
Project Implicit Continues its Critical Work
We are more excited than ever to not only continue but to expand the scientific collabora-tion at the heart of Project Implicit. With the non-profit that served as our operational home for two decades shutting down, a new organizational structure is being finalized to carry our research and educational mission forward.
In the meantime, the Project Implicit website (http://implicit.harvard.edu/) remains fully operational and continues to collect data 24/7. New studies, programs, and educational ef-forts are actively underway. We expect public data to remain available in perpetuity, and new data from 2026 will be released in January of next year.
We express our deep gratitude to everyone who has helped create, sustain, and grow Pro-ject Implicit. This includes the founders, members of the Board of Directors and the Scien-tific Advisory Board, staff members of the non-profit, international collaborators, and the students across dozens of labs tending to tasks big and small. We are also thankful to our generous donors who have answered our calls and supported our mission, and especially the millions of annual visitors who continue to honor us with their curiosity, time, and data.
We look forward to providing more details in the weeks ahead.
Jordan Axt, McGill University
Yoav Bar-Anan, Tel-Aviv University
Benedek Kurdi, University of Illinois
Calvin Lai, Rutgers University
Ryan Lei, Haverford College
Curtis Phills, University of Oregon
Kate Ratliff, University of Waterloo
Colin Tucker Smith, Wilfrid Laurier University
Jennifer Steele, York University
Heidi Vuletich, University of Denver
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Christopher Honey @chrishoney.bsky.social · 16/09/2026
1/ How do we sustain mental continuity in the face of interruption? @xianl-explorer.bsky.social found that, while people listen to a story, posterior medial cortex expresses a slowly evolving "background" representation of the story's context, which survived through silence and interfering tasks.
A schematic figure showing an evolving timeline of mental context during an interrupted narrative.
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Mark Thornton @markthornton.bsky.social · 14/09/2026
Yes sorry for the lack of clarity if you're outside the US! I usually specify the data source as the psych job wiki in the image itself (e.g. bsky.app/profile/mark...) but I realize now, while putting this together in a hurry, I accidently bumped that off screen while adjusting the legend this time.
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Jonathan Peelle @jpeelle.bsky.social · 13/09/2026
"I like milk and sugar in my _______" Classic work on prediction has used violation paradigms to study context and prediction. New work from my lab, led by Ryan O'Leary, compares semantic distance and GPT-2 surprisal in natural speech. #neuroscienceoflanguage www.biorxiv.org/content/10.6...
biorxiv.org
Neural tracking of surprisal and semantic distance in naturalistic movie viewing
Understanding speech requires listeners to integrate incoming input with prior linguistic and thematic knowledge to access meaning, a task greatly aided by prediction. Surprisal and related phenomena ...
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Mark Thornton @markthornton.bsky.social · 11/09/2026
The psychology job market may be showing some early signs of regaining strength, relative to last year. A week ago last year, fewer than 200 jobs had been listed - today, it is nearly 300, a figure we didn't hit till early October in '25. #psychjobs #neurojobs #academicjobs
Bar graph showing the number of academic jobs in psychology by area over the years from 2007-2026.
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Mark Thornton @markthornton.bsky.social · 10/09/2026
Come join @elisabaek.bsky.social & me on the SANS social media committee!
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SANS @sansmeeting.bsky.social · 10/09/2026
Interested in becoming a social and affective neuroscience influencer? SANS will soon be launching a new media initiative, in which we make short-form video content to reach a wider audience. If you're interested in joining this initative, please DM us here or email sans.media.chair@gmail.com!
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jerrytang.bsky.social @jerrytang.bsky.social · 08/09/2026
Our new study on cross-participant cortical mapping (with @alexanderhuth.bsky.social) is out in @imagingneurosci.bsky.social! direct.mit.edu/imag/article... 1/7
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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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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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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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Ty @tyanna.bsky.social · 05/09/2026
Linguists! What are some sociophonetic variables typical among contemporary adolescence at extremely elite cosmopolitan boarding school-type institutions? Iconic New England WASP schools if we have to narrow.
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Brandon Woo @brandonwoo.bsky.social · 04/09/2026
New paper with Liz Spelke, @rebeccasaxe.bsky.social, and @ashleyjthomas.bsky.social! We find that when 4- to 6-month-old infants observe two individuals share saliva, they infer that those individuals have a close relationship. Free access link: authors.elsevier.com/a/1niQg_Oow0...
A conceptual schematic illustrating the logic of the studies. (A) Infants observe a central actor who shares saliva with one actor and does not share saliva with another actor. (B) From such observations, infants may infer and represent whether the actors are connected and how thick each connection is. (C) These representations support infants' expectations of who will respond to the central actor's distress.
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William J. Brady @williambrady.bsky.social · 04/09/2026
Registration is open for the 4th annual Computational Psychology preconference at @spspnews.bsky.social Annual conference in Philly 🎊 We are on for a full day on Thursday, Feb 11. 3 keynote themes + a debate that couldn't be more timely 🧵👇
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Harrison Ritz @hritz.bsky.social · 27/08/2026
Our task-switching paper is now out at Current Biology! www.cell.com/current-biol... We find that that our brains reset to a task-neutral state between trials, providing flexibility when the upcoming task is uncertain. RNNs also learn this strategy, but only when trained to switch tasks.
schematic of how a brain might reset to a neutral state between trials
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Rebecca Saxe @rebeccasaxe.bsky.social · 05/08/2026
When we started scanning human infants 13 years ago, it seemed likely that functional responses in infant cortex would be qualitatively different from adults. Instead we keep finding similarities between infants and adults. Even for scene perception, despite the slow development of navigation.
Image of brain activation when infants look at movies of visual scenes, showing activation in three cortical regions: OPA, PPA and MPA.
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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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Association for Psychological Science @psychscience.bsky.social · 30/07/2026
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...
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Association for Psychological Science @psychscience.bsky.social · 29/07/2026
Recent surveys suggest that nearly a quarter of American adults and 13% of adolescents have used #AI for socioemotional support or mental health advice. #LLMs  But can a machine provide empathy?
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 · 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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Benedek Kurdi @benedek.bsky.social · 17/07/2026
Are the mental contents underlying implicit evaluations accessible to conscious introspection? Prior studies show high predictive accuracy, leading to a growing consensus that people can introspectively access their implicit biases. New paper out in JPSP! 🧵🧵🧵
The tide is turning against a major idea in social psychology: that implicit evaluations reflect mental content that lies beyond conscious awareness. This view is being reconsidered in light of mounting evidence that people can predict their own implicit evaluations with high accuracy. However, there are reasons to question whether such predictive accuracy reflects introspective access. First, prior studies have relied almost exclusively on familiar targets (e.g., racial groups), allowing predictions to be informed by background knowledge (e.g., knowing that a group is stigmatized) rather than introspection. Second, implicit and explicit evaluations have been highly correlated in prior work, enabling accurate predictions simply by assuming that implicit evaluations mirror explicit ones. Here, we report eight experiments (five pre-registered; N = 6,794) designed to minimize these nonintrospective routes to predictive accuracy. We introduced participants to novel targets and shifted implicit and explicit evaluations of these targets in opposite directions, rendering explicit evaluations an unreliable cue. Under these conditions, predictive accuracy ranged from low to nonexistent; participants frequently anticipated shifts in their implicit evaluations in the opposite direction of the actual change. These results generalized across two learning paradigms (impression formation and attribute conditioning), two implicit evaluation measures (Implicit Association Test and evaluative priming task), and between-participant and within-participant designs. We consider multiple interpretations of these findings, including the possibility that implicit evaluations reflect mental content that is largely or even entirely inaccessible to conscious awareness.
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Mark Thornton @markthornton.bsky.social · 15/07/2026
As a surprise parting gift to Lindsey, we ended her thesis DEFENSE in a very literal way: by giving her a chance to exercise her muay thai skills and live out a dream many PhD students have had at least once or twice - giving their advisor a punch to the gut!
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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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Mark Thornton @markthornton.bsky.social · 28/06/2026
We're engaged! @tyanna.bsky.social
Two humans smiling, one holding up a ringed hand
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Hayley Dorfman @hayleydorfman.bsky.social · 08/06/2026
🌵🏜️🌵 Out now in @cognitionjournal.bsky.social with @rbhui.bsky.social! If your advisor sends you an unclear email, do you interpret it as good or bad? 😏😱 In a new paper, we show how people make inferences about this type of ambiguous feedback during learning. www.sciencedirect.com/science/arti...
sciencedirect.com
Ambiguity and confirmatory reward learning
We tend to interpret feedback in ways that confirm our pre-existing beliefs. Such confirmatory tendencies are often viewed as cognitive flaws, but mig…
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João Guassi Moreira @jfguassimoreira.bsky.social · 22/05/2026
Excited to share my latest preprint, with @jasilvers.bsky.social and @raziasahi.bsky.social! We applied hierarchical Bayesian modeling to an EMA dataset of emotion regulation to uncover how trait-like repertoires of emotion regulation relate to momentary emotion regulation and experiences of affect
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Lauren Atlas @laurenatlas.bsky.social · 20/05/2026
Our multiverse analysis of associations between skin conductance and acute pain is published! >550 participants x 18 SCR pipelines = 1 winning approach to SCR analysis! (Ledalab + artifact detection). thread below. We hope others find this useful! Please RT :) journals.lww.com/pain/fulltex...
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Jin Ke @jinke.bsky.social · 18/05/2026
Preprint alert! 🧠 Using movie-watching fMRI and NLP, we show that prior social impressions shape how new social information is processed and updated over time, while moments of sudden insight ("aha"!) accompany transient shifts in brain activity that predict impression updates. (1/10)
biorxiv.org
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Ty @tyanna.bsky.social · 17/05/2026
Carrot, Peach, Crocus, Goji Berry, Tulip, Asparagus, and Primrose in the garden 🐣 Kiwi, Eki, Barb, and Squash staying far away 🐓🐓🐓🐓
Chicks huddled Chicks charging the camera Chicks around my foot Chicks being cute
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Dr. Yin Wang @bruceyinwang.bsky.social · 12/05/2026
1/ I’m excited to share our new @NatureHumBehav paper “Social Functioning in Autism: A Systematic Review & Meta-analysis” 🧵We synthesized 35 yrs of autism research to ask a fundamental Question: How is social functioning organized, developed, and altered in autism? Free link: rdcu.be/figGl
rdcu.be
Social functioning in autism: a systematic review and meta-analysis
Nature Human Behaviour - Impaired social functioning is a core feature of autism spectrum disorders. This systematic review and meta-analysis synthesizes the evidence for this across studies...
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Mark Thornton @markthornton.bsky.social · 11/05/2026
For a while, folks have asked me about older psyc job market numbers, and how they might reflect the 2008 financial crisis. I've finally been able to put together some numbers to reflect that (below) though the raw estimates come with some important interpretational caveats 🧵👇
A bar chart reflecting the number of psychology jobs per year from 2007-2025 by area.
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Mark Thornton @markthornton.bsky.social · 05/05/2026
Where did this year's #psychjobs market end up? Thanks to an unusually high number late postings, not as bad as it was looking earlier in the year. Still, this is the smallest number of jobs posted since 2012, representing a 26% decline from last year (~2/3rds the size of the covid drop in 2020).
Bar graph showing tenure track psychology jobs posted each year since 2010 broken up by area.
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Neil Lewis, Jr. @neillewisjr.bsky.social · 30/04/2026
👀
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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 · 15/04/2026
#SANS2026 starts TODAY in San Diego! ☀️🧠 We can't wait to see everyone. If you are already here! Join us for the pre-conference workshops kick off this afternoon! socialaffectiveneuro.org/conference/
socialaffectiveneuro.org
Conference - Social Affective Neuroscience Society
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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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Erik Nook 🏳️‍🌈 @eriknook.bsky.social · 12/04/2026
New paper: Jamil Zaki and I integrate theories of empathy + emotion regulation to describe how therapists have to regulate a "therapeutic emotional circuit" in each session. Lots of applications and avenues for new research. Just published in CPS! journals.sagepub.com/doi/10.1177/...
journals.sagepub.com
Sage Journals: Discover world-class research
Subscription and open access journals from Sage, the world's leading independent academic publisher.
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Travis Lim @travislim.bsky.social · 14/04/2026
New paper out in JPSP with @erichehman.bsky.social! We asked: What is the framework underlying our impressions of environments? Our large bottom-up study shows that people pay attention to 4 factors. We’re calling it the Environment Impressions Model: doi.org/10.1037/pspa...
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Jae-Young Son @jaeyoungson.bsky.social · 14/04/2026
How do we represent maps of social relationships in the mind & brain? To find out, we tracked 1st-year university students’ friendships, as well as students’ *beliefs* about who was friends with whom in their network. Yang breaks down what we found in the quoted thread 👇🏻 Broader context below:
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OHBM Communications Committee (ComCom) @ohbm-com.com · 13/04/2026
How do we keep track of what different people are like and use that knowledge in the moment? 🧠🤓 Read our latest #BrainBites Based on work by @markthornton.bsky.social www.ohbm-com.com/brain-bites/...
ohbm-com.com
How Your Brain Makes Sense of the People You Know — OHBM Communications
Interacting with people you know often feels natural. You might sense that your friend is nervous before giving a presentation, or that your sibling is joking even when their words sound serious, and ...
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Nakwon Rim @nwrim.bsky.social · 10/04/2026
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
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Mark Thornton @markthornton.bsky.social · 07/03/2026
My father, Roy James Thornton, died on Wednesday. He was a scientist and educator, a gardener, a lifelong sportsman, an avid fiction reader, and an incomparable father, son, and husband. My mother and I are heartbroken. Read about his life here: markallenthornton.com/personal/roy...
Dad with me as a babyMe, Mom, and Dad in KokomoMe and Dad grillingThe three of us in Costa Rica
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