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Mark Thornton

@markthornton.bsky.social

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

281 Posts2181 Follower 746 Folgt

Mark Thornton @markthornton.bsky.social · 2d ago

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.

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...

Association for Psychological Science @psychscience.bsky.social · last wk.

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?

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.

psychologicalscience.org

Dartmouth Arts and Sciences @dartmouthartsci.bsky.social · last wk.

“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.

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.

psychologicalscience.org

Mark Thornton @markthornton.bsky.social · 2w ago

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....

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.

psychologicalscience.org

Benedek Kurdi @benedek.bsky.social · 3w ago

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.

Mark Thornton @markthornton.bsky.social · 3w ago

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!

Mark Thornton@markthornton.bsky.social · 3w ago

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!

Mark Thornton @markthornton.bsky.social · 3w ago

Mark Thornton @markthornton.bsky.social · last mo.

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).

Mark Thornton@markthornton.bsky.social · 11mo ago

After 5 years, I finally carved out time to turn this blog post on FDR (markallenthornton.com/blog/fdr-pro...) into a manuscript. The preprint features a much broader range of simulations showing how FDR promotes confounds, and how this effect compounds with publication bias: osf.io/preprints/ps...

Effect of confound mass on true positive rates under FDR correction. Confound mass represents how large a confound is in terms of the product of its voxel extent and effect size. Results are shown at differing combinations of true effect size, true effect voxel extent, and sample size.

Mark Thornton @markthornton.bsky.social · last mo.

We're engaged! @tyanna.bsky.social

Two humans smiling, one holding up a ringed hand

Hayley Dorfman @hayleydorfman.bsky.social · 2mo ago

🌵🏜️🌵 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...

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…

sciencedirect.com

João Guassi Moreira @jfguassimoreira.bsky.social · 3mo ago

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

PsyArXivBot@psyarxivbot.bsky.social · 3mo ago

From Traits to Moments: How Emotion Regulation Repertoires Shape Daily Affective Experiences: https://osf.io/aextp

Lauren Atlas @laurenatlas.bsky.social · 3mo ago

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...

Lauren Atlas@laurenatlas.bsky.social · 8mo ago

I am so excited to share our newest preprint, inspired by @tinalonsdorf.bsky.social, “A multiverse approach to heat-evoked skin conductance analysis: Evaluating the influence of analytic pipeline on associations between skin conductance and pain osf.io/preprints/ps...

Jin Ke @jinke.bsky.social · 3mo ago

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

Ty @tyanna.bsky.social · 3mo ago

Carrot, Peach, Crocus, Goji Berry, Tulip, Asparagus, and Primrose in the garden 🐣 Kiwi, Eki, Barb, and Squash staying far away 🐓🐓🐓🐓

Dr. Yin Wang @bruceyinwang.bsky.social · 3mo ago

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

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...

rdcu.be

Mark Thornton @markthornton.bsky.social · 3mo ago

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.

Mark Thornton@markthornton.bsky.social · 3mo ago

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).

Mark Thornton @markthornton.bsky.social · 3mo ago

Bar graph showing tenure track psychology jobs posted each year since 2010 broken up by area.

Mark Thornton@markthornton.bsky.social · 9mo ago

Another ~monthly update on the state of the #psychjobs market: more jobs continue to trickle in, though at a decreasing pace. We've nearly hit parity with covid in absolute terms, although the prior year baseline was higher this year than that, so we still see a slightly larger relative decrease.

Neil Lewis, Jr.@neillewisjr.bsky.social · 3mo ago

👀

Berna Devezer@devezer.bsky.social · 3mo ago

📣 The difference between replicable and not replicable is not itself scientifically replicable. 📣 New work with Erkan Buzbas, showing that verdicts such as "X% of results replicated" are based on an inferential machinery that doesn't work. arxiv.org/abs/2604.26268

Screenshot of a paper's title page. Title: "The Difference Between 'Replicable' and 'Not replicable' is not Itself Scientifically Replicable". Authors: Berna Devezer and Erkan O. Buzbas, both at the University of Idaho — Devezer in the Department of Business and the Institute for Modeling Collaboration and Innovation, Buzbas in the Department of Mathematics and Statistical Science. Authors contributed equally. Corresponding author: bdevezer@uidaho.edu.
Abstract: Replication studies estimate the replicability rate of scientific results by aggregating binary verdicts of experiments. Exact replications are rarely attainable, so most replication sequences are non-exact. Experiments differ in ways that matter and do not share a single common data-generating process. We formalize two statistical interpretations of this non-exactness. In a shared latent rate model (benchmark), experiments are exchangeable and depend on a common random replicability rate. In a conditionally independent rates model (operational), each experiment has its own replicability rate drawn independently from a population distribution. Under the shared latent rate model, even small variability among replicability rates induces an irreducible variance floor on the estimated mean replicability rate that cannot be eliminated by adding more replications. Under the conditionally independent rates model, the degree of non-exactness is not identifiable from standard replication data, because one binary verdict per experiment contains no information about between-experiment heterogeneity. Researchers therefore cannot tell which precision regime they are operating in or whether high- and low-replicability sequences can be distinguished in principle. As a result, the usual data structure of one binary verdict per experiment cannot support reliable demarcation between "replicable" and "not replicable" results and systematically understates uncertainty, making high- and low-replicability sequences appear discrim…

Mark Thornton @markthornton.bsky.social · 4mo ago

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...

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SANS @sansmeeting.bsky.social · 4mo ago

Next is @gabefajardo.bsky.social presenting on high dimensional neural representations of facial expressions

SANS @sansmeeting.bsky.social · 4mo ago

#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/

Conference - Social Affective Neuroscience Society

socialaffectiveneuro.org

Gabriel Fajardo @gabefajardo.bsky.social · 4mo ago

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 :)

Erik Nook 🏳️‍🌈@eriknook.bsky.social · 4mo ago

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/...

Sage Journals: Discover world-class research

Subscription and open access journals from Sage, the world's leading independent academic publisher.

journals.sagepub.com

Travis Lim @travislim.bsky.social · 4mo ago

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...

Jae-Young Son @jaeyoungson.bsky.social · 4mo ago

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:

Yang Teoh@yyangteoh.bsky.social · 4mo ago

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/... 🧵

OHBM Communications Committee (ComCom)@ohbm-com.com · 4mo ago

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/...

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 ...

ohbm-com.com

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...

Mark Thornton @markthornton.bsky.social · 5mo ago

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...

Alexis Cameron @alexismcameron.bsky.social · 5mo ago

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