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David Baranger

@davidbaranger.bsky.social
1.2K followers 1.1K following 512 posts

Assistant Professor at the Medical College of Wisconsin. 🧀 Substance use, neuroscience, genetics, & development. 🍺🧠🧬 Rock climber & dad. He/him. 🧗 Opinions my own. 🤔 bearlab.science 🐻

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David Baranger @davidbaranger.bsky.social · 12h
Wow, looks like exactly the right special issue for me!
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Luca Sclisizzo @luca-sclisizzo.bsky.social · 14/09/2026
🚨 New Preprint out! What if psychosis is not a single, homogeneous construct? "Parsing the functional heterogeneity of psychosis spectrum" addresses this question defining a genetic gradient across the spectrum. 🧬 www.medrxiv.org/content/10.6...
medrxiv.org
Parsing the Functional Heterogeneity of the Psychosis Spectrum: A Clinically Informed Application of Genomic Structural Equation Modeling
Schizophrenia, bipolar disorder, and major depression vary in their age of onset, cognitive impacts, degree of impairment, and clinical course. However, since psychosis is a transdiagnostic feature th...
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David Baranger @davidbaranger.bsky.social · 10/09/2026
Probably just shouting into the void but... participants in the Human Connectome Project (HCP-YA) are related! You can't just resample willy-nilly! #neuroskyence #neuroimaging
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David Baranger @davidbaranger.bsky.social · 08/09/2026
Data visualization is storytelling. After Elspeth Kirkman: www.instagram.com/reel/DcSlOws...
Plot of four charts, each showing time vs age, in years. Each plot shows a different aspect - actual (linear), reported (staircase), development (log age), and perception of time passage (log time).
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David Baranger @davidbaranger.bsky.social · 11/08/2026
Totally. The idea was more so to have a simple procedure to suggest to folk who test for a moderation (with a frequentist test) when that isn't their actual hypothesis.
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David Baranger @davidbaranger.bsky.social · 31/07/2026
Thank you Ashley!
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David Baranger @davidbaranger.bsky.social · 31/07/2026
Stoked to share that I was awarded a 2026 BBRF Young Investigator Grant for my proposal "Decoding the Comorbidity of Alcohol and Depression with Dense-sampling fMRI"! Huge thanks to @bbrfoundation.bsky.social and colleagues at @medicalcollegeofwi.bsky.social for their support.
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ethan whitman @ethanwhitman777.bsky.social · 13/07/2026
New preprint ! Poor sleep is correlated with accelerated aging. But is this relationship causal? We’re not so sure. www.medrxiv.org/content/10.6...
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Ashley Watts @ashleylwatts.bsky.social · 09/07/2026
Excited to share a paper recently accepted at Nature Mental Health! 😄 For decades, we've assumed that covariance among psychopathology informs comorbidity. What if we’ve been wrong?
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Scott Marek @smarek0502.bsky.social · 11/06/2026
What matters most for childhood brain organization? We analyzed 649 variables. The answer: Socioeconomics (SES); with brain patterns pointing at sleep & stress as drivers. Even brain-IQ associations were better explained by SES. In Science today: www.science.org/doi/10.1126/...
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Tayler Sheahan @taylersheahan.bsky.social · 01/05/2026
I'm recruiting a postdoc! The Sheahan Lab at the Medical College of Wisconsin is looking to add a postdoctoral fellow to our team to expand our work studying the neurobiology of itch and pain in the central nervous system. Please share and reach out if you have any questions!
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David Baranger @davidbaranger.bsky.social · 30/04/2026
Stoked for #SOBP2026! Come by poster F324 to chat about some new imaging genetics work - "Genetic Contributions to Working Memory Activation in Early Adolescence - Links to Psychopathology and Cognition"
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David Baranger @davidbaranger.bsky.social · 03/04/2026
These are fantastic, thanks for putting in the time to make this easy to follow!!
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David Baranger @davidbaranger.bsky.social · 24/03/2026
And if you're worried that we possibly missed an important regional association, we did some post-hoc analyses to show that more than 90% of all brain-wide associations with substance use (thickness, surface area, and volume) are explained by global thickness!
ortical Thickness Accounts for the Majority of Substance Use Associations.
A) The p values of associations between all available drug variables and brain measures before controlling for global brain thickness are pictured. Most of the significant drug variable associations are also strongly associated with global brain thickness, including mAUDIT-C and lifetime marijuana use. B) Analyses pictured in Panel A were repeated with global cortical thickness as an additional covariate.

 Colors indicate drug type. Shades of each color indicate a dimension of use (e.g., dependency, lifetime use, drug test). Individual points represent the p value of the association between a drug variable and a brain measure. Points outlined in black indicate survival of multiple test correction.
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David Baranger @davidbaranger.bsky.social · 24/03/2026
I'm particularly excited that we're seeing evidence for both exposure and risk effects in the same people at the same time! I hope this will help push the field toward stage‑based studies that incorporate risk effects and explore the timing of when risk effects emerge.
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David Baranger @davidbaranger.bsky.social · 24/03/2026
These results highlight the complexity of substance use associations. There are both shared and unique components across dimensions of use, which reflect a combination of genetic and environmental influences.
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David Baranger @davidbaranger.bsky.social · 24/03/2026
Comparing within- and between-families, we see evidence for predispositional risk with marijuana use (significant between family effect and genetic correlation), as well as evidence for exposure effects (possibly bi-directional) for both alcohol and marijuana (significant within-family effects).
Drug Use Associations With Brain Structure Reflect a Combination of Predispositional Risk and Exposure Effects. 
A) Regression estimates of within- and between-family drug use variables fit to predict whole brain thickness are pictured. Y-axis variables are split by mAUDIT-C and Marijuana Use. X-axis data are split by within- (left) and between- (right) family estimates. Color denotes the sample included in the analysis. B) Regression estimates of within- and between-family whole brain thickness fit to predict substance use variables are pictured. Y-axis variables are split by mAUDIT-C and Marijuana Use, the two drugs evidencing unique-effects on whole brain thickness. X-axis data are split by within- (left) and between- (right) family whole brain estimates. Color denotes the sample included in the analysis. Bold indicates significance. C) Standardized regression estimates of environmental variance (green) and heritability (pink) fit to predict mAUDIT-C, Marijuana Use, and Brain Thickness are pictured. D) Variance component correlations of additive genetics (blue) and non-shared environment (red) between mAUDIT-C and Marijuana Use are pictured. Points reflect estimates, lines indicate 95% confidence intervals. MJ Use = Marijuana Use. Bold indicates significance.
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David Baranger @davidbaranger.bsky.social · 24/03/2026
Looking across a several dimensions of substance use, age of onset of alcohol use, as well as lifetime marijuana and tobacco use, are also associated with global thickness. But only marijuana shows a unique effect over and above alcohol use (and vice versa)!
Shared- and Unique-Drug Associations with Attenuated Brain Thickness. 
Standardized regression estimates of alcohol, marijuana, tobacco, and illicit drug use variables predicting whole brain cortical thickness. Lines reflect the 95% confidence interval of the estimate. Note that these dimensions were not standardized across drug type, as collection of these data varied. Bold indicates survival of multiple test correction and evidence for shared-effects on global brain thickness. Starred indicates drug-specific, unique effects on global brain thickness.
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David Baranger @davidbaranger.bsky.social · 24/03/2026
In the HCP, which includes many people with moderate-severe alcohol use and polysubstance use, we replicate associations of hazardous alcohol use with many brain structures (onlinelibrary.wiley.com/doi/full/10....). But, these effects are largely attributable the association with global thickness!
A) Composite mAUDIT-C scores ranged from zero to 12 and were categorized into four levels of past-year hazardous risk: low (green; 0 to 3), moderate (yellow; 4 to 5), high (blue; 6 to 7), and severe (pink; 8 to 12). B) Color indicates the number of drugs used across the lifetime. Participant endorsement of having ever used any of the four major substance types are pictured. 65% (n = 726) of the sample endorsed a pattern of polysubstance use throughout the lifetime (i.e., 2+ substances).Global Brain Thickness Explains Regional Alcohol Effects on Brain Structure. 
Standardized regression estimate associations between brain ROI and mAUDIT-C are pictured. Brain structures on the y-axis are split by modality, i.e., volume, thickness, and global measures. X-axis panels are split before (left, blue) and after (right, red) controlling for global brain thickness (grey). Bold indicates significance following multiple test correction.Hazardous Alcohol Use Predicts Attenuated Global Brain Thickness.
Association of hazardous alcohol use (mAUDIT-C) with global cortical thickness, residualized for covariates and standardized (i.e., SD=1). Covariates included age, age2, sex, socioeconomic status, level of educational attainment, intracranial volume, and sibling status. Shading reflects the density of overlapping points. mAUDIT-C was uniquely associated with attenuated global brain thickness (β = -0.12, p < 0.001).
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David Baranger @davidbaranger.bsky.social · 24/03/2026
This is a paper of many firsts. My first senior-author paper, my first two-author empirical research paper 😁, and the first first-author paper from my fantastic Research Tech Daniella Fernandez, who did all of the heavy lifting, including all of the stats, figures, and writing the first full draft!
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David Baranger @davidbaranger.bsky.social · 24/03/2026
The first preprint from the lab is up! Are structural MRI correlates of substance use shared across substances, or are there unique associations? And do these reflect predispositional risk and/or possibly the effects of substance exposure? www.medrxiv.org/content/10.6... #neuroskyence
medrxiv.org
Brain Structure and Substance Use: Disentangling Risk, Exposure, and Drug-Specific Effects
Importance: Polysubstance use is common, but substance use associations with neuroimaging measures have largely been investigated within individual drug types. Whether effects are substance-specific o...
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David Baranger @davidbaranger.bsky.social · 23/02/2026
See david-baranger.shinyapps.io/InteractionP... for continuous variables! NB intxpower assumes your main effects are null, so will tend to be a bit conservative.
david-baranger.shinyapps.io
InteractionPoweR Shiny App for analytic power
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David Baranger @davidbaranger.bsky.social · 28/01/2026
So infuriating. www.nytimes.com/2026/01/24/u...
nytimes.com
Genetic Data From Over 20,000 U.S. Children Misused for ‘Race Science’
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David Baranger @davidbaranger.bsky.social · 09/01/2026
Please say hi at #ACNP if you'd like to chat with either of us about this opportunity!!
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David Baranger @davidbaranger.bsky.social · 06/01/2026
Toddler requested a "Master Yoda" bedtime story
media.tenor.com
darth vader is standing in front of a wall with the words join me below him
ALT: darth vader is standing in front of a wall with the words join me below him
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David Baranger @davidbaranger.bsky.social · 03/12/2025
See also palmerpenguins - allisonhorst.github.io/palmerpengui...
allisonhorst.github.io
palmerpenguins R data package
Data for three penguin species observed in the Palmer Archipelago, Antarctica, collected by Dr. Kristen Gorman with Palmer Station LTER. A great intro dataset for data science teaching and learning, a...
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David Baranger @davidbaranger.bsky.social · 25/11/2025
𝐘𝐨𝐮𝐭𝐡 𝐂𝐨𝐫𝐫𝐞𝐥𝐚𝐭𝐞𝐬 𝐨𝐟 𝐆𝐞𝐧𝐞𝐭𝐢𝐜 𝐋𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐭𝐨 𝐒𝐮𝐛𝐬𝐭𝐚𝐧𝐜𝐞 𝐔𝐬𝐞 𝐃𝐢𝐬𝐨𝐫𝐝𝐞𝐫𝐬. New from us, led by @sarahepaul.bsky.social. PheWAS in ABCD identifies many potentially modifiable substance use risk factors! www.medrxiv.org/content/10.1...
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David Baranger @davidbaranger.bsky.social · 20/11/2025
Certainly
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David Baranger @davidbaranger.bsky.social · 20/11/2025
Most people use MID contrasts (eg Big Win > Neut), which would be less reliable than any of these estimates. I'm also surprised by how low the PET reliability is, but I'm less familiar with that literature.
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David Baranger @davidbaranger.bsky.social · 20/11/2025
Thanks Nicola! Given that they're looking at activation relative to an implicit baseline, and not a contrast, the ICC here is around what I would expect. Certainly longer time between measurements lowers reliability in many of the adolescent samples. Harder to say if there are age effects.
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David Baranger @davidbaranger.bsky.social · 14/11/2025
Great work led by Andrew Castillo extending sample size stability analyses to interactions! We've also added a function implementing these analyses to the InteractionPoweR R package: dbaranger.github.io/InteractionP... #rstats
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PsyArXivBot @psyarxivbot.bsky.social · 12/11/2025
When do interaction/moderation effects stabilize in linear regression?: osf.io/35t84
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David Baranger @davidbaranger.bsky.social · 11/11/2025
Reliability and sample size have a non-linear relationship. Linear increases in reliability yield diminishing reductions in the required sample size.
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David Baranger @davidbaranger.bsky.social · 31/10/2025
If you are ever working on a project and see r=0.98 between variables that are supposedly different, your first thought should be "oh $&*! what went wrong?", NOT "I wonder what mediates this???"
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David Baranger @davidbaranger.bsky.social · 27/10/2025
Shout out to BEAR Lab research tech Daniella Fernandez (who only joined 4 months ago!) whose poster abstract was selected for a nanosymposium at the annual meeting of the Upper Midwest Chapter of SFN this weekend! #neuroskyence #MRI 🧠🍺
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David Baranger @davidbaranger.bsky.social · 15/10/2025
Applications for the Career Development Institute (CDI) in Psychiatry are open! Strongly recommend for senior grad students and postdocs. cdipsychiatry.org
cdipsychiatry.org
CDI Psychiatry |
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David Baranger @davidbaranger.bsky.social · 15/10/2025
Interesting approach that aligns mouse and human brain-wide data using transcriptomics and structural connectivity. I'm curious if anyone here has tried using it yet? #neuroskyence www.biorxiv.org/content/10.1... transbrain.readthedocs.io/en/latest/
biorxiv.org
TransBrain: A computational framework for translating brain-wide phenotypes between humans and mice
Despite remarkable advances in whole-brain imaging technologies, the lack of quantitative approaches to bridge rodent preclinical and human studies remains a critical challenge. Here we present TransB...
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David Baranger @davidbaranger.bsky.social · 15/10/2025
Official job ad is up! careers.peopleclick.com/careerscp/cl...
careers.peopleclick.com
Postdoctoral Researcher
Medical College of Wisconsin - Postdoctoral Researcher - Milwaukee WI 53201
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David Baranger @davidbaranger.bsky.social · 03/10/2025
A new favorite citation appeared!
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David Baranger @davidbaranger.bsky.social · 30/09/2025
TIL in Windows you can use PowerShell to search not only file names but also text file contents - including .R and .Rhistory files. In a moment of pure insanity, 1.5 years ago I did not save the code for a figure, but it was recorded in an old .Rhistory file!
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David Baranger @davidbaranger.bsky.social · 25/09/2025
Lol thanks!!!
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David Baranger @davidbaranger.bsky.social · 25/09/2025
Also, I will be at #SRP this week if anyone wants to chat!
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David Baranger @davidbaranger.bsky.social · 25/09/2025
Current projects in the lab include longitudinal neuroimaging of substance use at different time-scales, family-based studies of casual and genetic effects, and the development of new ML models for task fMRI. This is a funded position with up to 3 years of funding available.
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David Baranger @davidbaranger.bsky.social · 25/09/2025
Excited to share that I am officially recruiting a postdoc to study the neurobiology of addiction! Looking for someone who would be excited to lead current projects in the lab and develop new directions in related areas. More info: bearlab.science/opportunities/
bearlab.science
Opportunities
Interested in the neuroscience of addiction? We are recruiting at all levels!! Reach out to Dr. Baranger – dbaranger@mcw.edu Postdoctoral fellows/Senior Scientists: Please send an email conta…
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Jamie Hanson @jamielarsh.bsky.social · 22/09/2025
🧠📊 New research examines potential bias in brain age algorithms across racial groups 📈 Study of 6 popular algorithms found lower accuracy for African American participants (r=0.51-0.85) compared to White/Hispanic participants (r=0.57-0.89)/1
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David Baranger @davidbaranger.bsky.social · 17/09/2025
𝐓𝐡𝐞 𝐥𝐢𝐟𝐞𝐬𝐩𝐚𝐧 𝐭𝐫𝐚𝐣𝐞𝐜𝐭𝐨𝐫𝐢𝐞𝐬 𝐨𝐟 𝐛𝐫𝐚𝐢𝐧 𝐚𝐜𝐭𝐢𝐯𝐢𝐭𝐢𝐞𝐬 𝐫𝐞𝐥𝐚𝐭𝐞𝐝 𝐭𝐨 𝐜𝐨𝐧𝐟𝐥𝐢𝐜𝐭-𝐝𝐫𝐢𝐯𝐞𝐧 𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐯𝐞 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 | "The predominant lifespan trajectory is inverted U-shaped, rising from childhood to peak in young adulthood before declining in later adulthood" www.sciencedirect.com/science/arti...
sciencedirect.com
The lifespan trajectories of brain activities related to conflict-driven cognitive control
Cognitive control is fundamental to human goal-directed behavior. Understanding its trajectory across the lifespan is crucial for optimizing cognitive…
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David Baranger @davidbaranger.bsky.social · 17/09/2025
𝐀𝐝𝐝𝐢𝐭𝐢𝐯𝐞 𝐚𝐧𝐝 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐯𝐞 𝐑𝐞𝐥𝐚𝐭𝐢𝐨𝐧𝐬𝐨𝐟 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐂𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧 𝐖𝐢𝐭𝐡𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥𝐢𝐳𝐢𝐧𝐠 𝐁𝐞𝐡𝐚𝐯𝐢𝐨𝐫𝐬 | "Although interaction effects were detected, they were small and practically negligible in their explanation of variance in externalizing behaviors" journals.sagepub.com/doi/10.1177/...
journals.sagepub.com
Additive and Interactive Relations of Personality and Cognition With Externalizing Behaviors - Nathaniel L. Phillips, Nathan T. Carter, Kevin M. King, Courtland S. Hyatt, Max M. Owens, Donald R. Lynam...
Personality and cognition offer robust frameworks to understand the individual differences associated with externalizing behaviors. However, these literatures h...
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David Baranger @davidbaranger.bsky.social · 15/09/2025
Thanks! I was able to create an educator account on datacamp, which lets me give trainees access for free if then enroll in my 'class'. So far it looks like a useful supplement, particularly for programming concepts that might be new
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David Baranger @davidbaranger.bsky.social · 12/09/2025
Wooo NOA day! Phew.
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David Baranger @davidbaranger.bsky.social · 10/09/2025
If you're looking at pre-6.0 ABCD results with subcortical rs-fMRI correlations, the labels are all wrong! We reported a result as Auditory - L Putamen, but it it was actually Default Mode - L Cerebellum. docs.abcdstudy.org/latest/docum...
docs.abcdstudy.org
6.0 data release
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