iiinova — where your digital self keeps evolving

Reposted by Gabriel Fajardo

Josh de Leeuw @joshdeleeuw.bsky.social · 21/09/2026

DataPipe (pipe.jspsych.org) is ready for its post-OSF life. You can use it as before to save data from online experiments, but now the data can be sent to Zenodo, Google Drive, or a Dataverse instance. Existing OSF connections work until 11/16 I took this opportunity to do some major updates...

pipe.jspsych.org

DataPipe

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Reposted by Gabriel Fajardo

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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Reposted by Gabriel Fajardo

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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Reposted by Gabriel Fajardo

Arshiya Aggarwal @whatsinertia.bsky.social · 25/04/2026

New paper in @jexpsocpsych.bsky.social!! 🧵 When people learn to fear one person, who else do they mistake for a threat, and does race shape the pattern? Read here: authors.elsevier.com/c/1m~aL51f8~...

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Reposted by Gabriel Fajardo

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

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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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Reposted by Gabriel Fajardo

Científico Latino @cientificolatino.com · 01/04/2026

Sign ups are ✨OPEN✨ for #GSMI2026! 🤩⁠ ➡️ www.cientificolatino.com/gsmi ⁠ The GSMI program supports 100 graduate school applicants through 1-on-1 mentorship, fee waivers, professional development, and community building!⁠ ⁠ Applications accepted until 5/31/26!⁠

Flyer for GSMI 2026 program: https://www.cientificolatino.com/gsmi

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Reposted by Gabriel Fajardo

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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Reposted by Gabriel Fajardo

Científico Latino @cientificolatino.com · 10/12/2025

Happy to introduce our 25 2025 Alumni Scholarship Recipients!! This year we have launched our 2025 Alumni Scholarship Fund to support 1st year grad students, graduates of our GSMI program, to cover educational expenses in their 1st year of graduate school.

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Reposted by Gabriel Fajardo

Stefano Anzellotti @steanze.bsky.social · 01/12/2025

Some new work from the lab: @yuzhu194.bsky.social and Aidas Aglinskas introduce a deep-learning based fMRI denoising method that outperforms CompCor by over 200%.

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Reposted by Gabriel Fajardo

Mark Thornton @markthornton.bsky.social · 03/10/2025

We're a month further into the job market - how are things looking? The good news is that the market does seem to have been delayed: ~150 new listings have appeared since my last post. The bad news is that the total is still substantially lower than what it was during the covid dip.

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Gabriel Fajardo @gabefajardo.bsky.social · 02/10/2025

I’m excited to share my 1st first-authored paper, “Distinct portions of superior temporal sulcus combine auditory representations with different visual streams” (with @mtfang.bsky.social and @steanze.bsky.social ), now out in The Journal of Neuroscience! www.jneurosci.org/content/earl...

Fig. 1. a. Visual and auditory regions of interest (ROIs). b. Responses in a combination of visual (e.g., early dorsal visual stream; Fig. 1a, middle panel) and auditory regions were used to predict responses in the rest of the brain using MVPN. c. In order to identify brain regions that combine responses from auditory and visual regions, we identified voxels where predictions generated using the combined patterns from auditory regions and one set of visual regions jointly (as shown in Fig. 1b) are significantly more accurate than predictions generated using only auditory regions or only that set of visual regions.

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Reposted by Gabriel Fajardo

Youngki Hong @youngkihong.bsky.social · 10/09/2025

I’m admitting 1–2 Ph.D. students to join my lab in the Department of Psychology and Neuroscience at CU Boulder, starting Fall 2026. We study person perception, stereotyping and prejudice, and intervention science. Application info: www.colorado.edu/psych-neuro/... Lab info: www.svmlab.org

svmlab.org

Colorado Social Vision & Mind Lab

The Social Vision & Mind Lab (Director: Youngki Hong, Ph.D.) at the University of Colorado Boulder explores how people perceive and make sense of the physica...

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Reposted by Gabriel Fajardo

Youngki Hong @youngkihong.bsky.social · 28/08/2025

Job alert: I'm hiring a postdoc for my lab at CU Boulder starting Fall 2026! We study person perception, stereotyping & prejudice, and intervention science using behavioral & neuroimaging methods. Link: jobs.colorado.edu/jobs/JobDeta... Review starts Nov 1 and continues until filled.

jobs.colorado.edu

Postdoctoral Associate

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Reposted by Gabriel Fajardo

Dan Oh (DongWon) | 오동원 @ohdanieldw.bsky.social · 23/09/2025

Six years in the making, a postdoc project with @freemanjb.bsky.social is finally now out in print. Many thanks to Jon and @hennavartiainen.bsky.social and everyone who made this important work possible.

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Reposted by Gabriel Fajardo

Landry Bulls @landrybulls.bsky.social · 16/09/2025

Excited to share the preprint for my 1st 1st-author manuscript! @markthornton.bsky.social and I show that people hold robust, structured beliefs about how individual mental states unfold in intensity over time. We find that these beliefs are reflected in other domains of mental state understanding.

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Mark Thornton @markthornton.bsky.social · 05/09/2025

Today, SCRAP Lab returned (right) to the Path of Life Garden in Windsor, VT - the site of our first in-person get-together as a lab 5 years ago (left) - to welcome our newest member, graduate student @gabefajardo.bsky.social!

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Reposted by Gabriel Fajardo

Mark Thornton @markthornton.bsky.social · 03/09/2025

The psych job market may not be dead... but it is gravely injured 😬 So far it's looking like the Trump administration's attacks on higher ed/research are going to have more than 2x the impact on the job market as the covid-19 pandemic. #psychjobs #neurojobs #academicjobs

Bar plot showing the number of psychology jobs posted each year by area. There are major dips in 2020 due to covid, and in 2025 (now).

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Reposted by Gabriel Fajardo

Jon Freeman @freemanjb.bsky.social · 18/06/2025

In a TiCS paper, @chujunlin.bsky.social & I propose a high-dimensional model of social impressions. Existing models focus on 2–4 latent dimensions (e.g. trustworthy/warm), but they often fall apart across different contexts, cultures, & perceivers. We need a paradigm shift. shorturl.at/7GD1n (1/8)

cell.com

A high-dimensional model of social impressions

People form social impressions from visual cues such as faces, which are argued by various models to arise from some limited set of fixed dimensions (e.g., trustworthiness and dominance). We argue tha...

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Youngki Hong @youngkihong.bsky.social · 02/06/2025

Excited to share that I’ll be joining the Department of Psychology and Neuroscience at @colorado.edu as an Assistant Professor this fall! My lab will study social cognition, focusing on the cognitive and neural bases of stereotyping and bias interventions.

colorado.edu

Home

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Reposted by Gabriel Fajardo

Jon Freeman @freemanjb.bsky.social · 21/05/2025

🚨 A new rule would let career scientists like NSF/NIH program officers be replaced by political appointees Already 14,000+ public comments, deadline is Friday 📣 Comments can be short. Courts consider them—and scientists with NSF/NIH experience are especially impactful Speak up! shorturl.at/WKuBj

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Reposted by Gabriel Fajardo

Chujun Lin @chujunlin.bsky.social · 21/05/2025

🥳Excited to share that I am joining Columbia July 2025 @columbiauniversity.bsky.social Looking for🚨lab managers🚨postdocs🚨grad students! Pls REPOST🙏 We study⭐️person perception⭐️social cognition using experimental, cross-cultural, & computational methods! App👉shorturl.at/5UVPl More👉shorturl.at/q18GM

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Reposted by Gabriel Fajardo

Emily Finn @esfinn.bsky.social · 09/05/2025

Despite everything going on, I may have funds to hire a postdoc this year 😬🤞🧑‍🔬 Open to a wide variety of possible projects in social and cognitive neuroscience. Get in touch if you are interested! Reposts appreciated.

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Reposted by Gabriel Fajardo

Mark Thornton @markthornton.bsky.social · 26/04/2025

SCRAP Lab had a great time at #SANS2025! Can't wait till next year!

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Gabriel Fajardo @gabefajardo.bsky.social · 21/04/2025

Now accepting applications! 🚨 As the current lab manager, I can confidently say this is an incredible opportunity to gain lots of hands-on research experience and prepare for grad school. You'll be part of a vibrant community (+ city) and work alongside many brilliant scientists - don't miss out!

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Reposted by Gabriel Fajardo

Científico Latino @cientificolatino.com · 08/04/2025

Applying to STEM grad programs? 🎓 Sign ups are ✨OPEN✨ for #GSMI2025! 🤩 The GSMI program supports applicants through 1-on-1 mentorship, fee waivers, professional development, and community building! Applications accepted on a ROLLING basis until 5/31! cientificolatino.com/gsmi MORE INFO in 🧵 1/

Graduate School Mentorship Intiative (GSMI). Our mission is to help STEM students from underserved communities get accepted into graduate programs. Apply by 5/31/25 to be one of our 100 scholars.
Program benefits:
* Personal STEM mentor
* Application Advice
* Supportive community
* Fee waivers
* Mock interviews
* Webinars and resources.
For more info: cientificolatino.com/gsmi
Cientifico Latino and Simons Foundation logos.

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Gabriel Fajardo @gabefajardo.bsky.social · 15/04/2025

I'm THRILLED to announce that this fall, I will be joining the Psychological and Brain Sciences department at Dartmouth as a PhD student!!! I'll will be working with the amazing @markthornton.bsky.social and the SCRAP Lab! 🌲🧠

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Reposted by Gabriel Fajardo

William J. Brady @williambrady.bsky.social · 20/02/2025

Gabriel Fajardo & @freemanjb.bsky.social have created a new connectionist model of trait formation (impression from faces). High dimension, dynamic models may buy us better model outcomes and situational variability #spsp2025 #comppsych

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