🚨 Deadline this Friday!
We’re accepting abstracts for our Trainee Research Presentation on #MenstrualHealth.
Undergrad, grad, and postdoc researchers welcome.
🗓 Abstracts due Feb 27
📅 Presentation: April 24, 2026
Submit yours today: ow.ly/GWFZ50YkiCT
#WomensHealth
#Statistics thought of the day: If you think you can find new disease subtypes by empirically clustering patients, think again: www.fharrell.com/post/cluster... #StatsSky
I started making this R package 6 years ago. I finally have it in a state I'm happy with, thanks to Claude Code #Rstats github.com/MattCowgill/...
🚨 We’re recruiting a fully funded PhD student (from outside the UK) to join the lab with @tessamdekker.bsky.social 🌍👁️🧠 The PhD is part of IndiBrain.eu and will use cutting‑edge fMRI+qMRI+psychophysics to study information flow between eye and brain in ocular gene therapy. Apply by 27 Feb! t.ly/gahGB
The ‘how to draw an owl’ meme
Some tutorial papers be like
New paper in @elife.bsky.social led by Tianhe!
Motor errors shape everyday actions—from spilling milk to missing a hold while climbing. Why are some errors systematic?
We show motor biases arise from misalignment between visual and proprioceptive reference frames.
tinyurl.com/t7h786m5
If you can substitute "hungry ghost trapped in a jar" for "AI" in a sentence it's probably a valid use case for LLMs. Take "I have a bunch of hungry ghosts in jars, they mainly write SQL queries for me". Sure. Reasonable use case.
"My girlfriend is a hungry ghost I trapped in a jar"? No. Deranged.
New preprint! tinyurl.com/y6z57dsm
How do people discover an effective strategy when the environment shifts—say, when adapting to an unfamiliar trackpad?
Our take: strategic motor adaptation isn’t a smooth process of error reduction but rather a process of hypothesis testing.
🧵
This commentary will always remain one of my favourite. Well written and rings true to this day.
"You can't play 20 questions with nature and win" by Allen Newell, 1973
www.coli.uni-saarland.de/~crocker/doc...
Do you teach #rstats? Do your students complain about how lame and old-fashioned dplyr is? Don't worry: I have the solution for you: github.com/hadley/genzp....
genzplyr is dplyr, but bussin fr fr no cap.
L'audience vient d'être levée, et voici la Une de @mediapart.fr après le jugement historique rendu dans l'affaire Sarkozy-Kadhafi.
🚨Postdoc position open at @BarcelonaBeta🚨
We're looking someone to work on a project at the intersection of cardiovascular and neurodegenerative research 🫀🧠
Fully funded position!!!
More details: www.imim.cat/media/upload...
Please share!
#Alzheimer's #ENDALZ
"In a landmark study, OpenAI researchers reveal that large language models will always produce plausible but false outputs, even with perfect data, due to fundamental statistical and computational limits."
www.computerworld.com/article/4059...
I'm officially recruiting grad students in FIU's Cognitive Neuroscience PhD program! 🧠✨
The @bottenlab.bsky.social uses precision and population approaches to study neurodevelopmental variability. Reach out if interested! (contact info on bottenlab.github.io) Apps due 12/1! cn.fiu.edu
(pls share)
An M.I.T. study found that 95% of companies that had invested in A.I. tools were seeing zero return. It jibes with the emerging idea that generative A.I., “in its current incarnation, simply isn’t all it’s been cracked up to be,” johncassidysays.bsky.social writes.
Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities Abstract Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models).
Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve.
A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals). Illustrated are 1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals 2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and 3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.
Ever stared at a table of regression coefficients & wondered what you're doing with your life?
Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...
Why menstrual cycle irregularities belong in brain research www.nature.com/articles/s41...
Come to talk to me about parity, AD, and anything else at #AAIC25 today!!
Today at 3:30 my top PhD student @clara-gallay.bsky.social will present my poster at the amazing Guided Electronic Poster Tour about Sex and Gender in AD. Don’t miss it! @barcelonabeta.bsky.social #AAIC25
I have deleted
the data
that were in
the database
and which
you were probably
saving
for production
Forgive me
I was panicked
So artificial
And so intelligent
📊 Silent changes, serious risks: US gov datasets quietly altered
A new study found nearly half of 232 US health datasets were changed, mostly replacing 'gender' with 'sex', without logging or explanation.
🔗 www.thelancet.com/journals/lan...
#SciComm #Data 🧪
This is figure 1, which shows symptom patterns over menopause stages.
A Review in Nature Reviews Psychology approaches midlife and menopause as both a biological and a psychological transition and outlines behavioural approaches to managing menopausal symptoms and related mental health concerns. go.nature.com/44dBqSt #medsky 🧪
Defensive coding - the latest in my Better Code, Better Science series russpoldrack.substack.com/p/defensive-...
Balloon wall art inspired by the ggplot2 hex sticker. The display features a hexagonal frame made of black balloons, filled with white balloons inside and surrounded by a background of light and dark blue balloons. A line graph with black balloon segments and round coloured nodes runs across the centre, and the word “ggplot2” is spelled out in black balloon letters below the chart.
Happy 18th birthday ggplot2! #rstats
Thank you again @ibroorg.bsky.social for giving me the opportunity to go to the 2025 Biomarkers Course at UCL. This was hands down the best course I've ever attended! Massive thanks to Dr. Aitana Sorgov-Esteve, Dr. Ross Paterson and Dr. Michael Schöll.
Thanks for an amazing #ParentalBrain2025 meeting @susanacarmona.bsky.social and Prof. Oscar Vilarroya! It felt uplifting to have so many people from around the globe come together. One of the best conferences I've been to in a while 🧠✨
Yesterday we had the pleasure to have at @barcelonabeta.bsky.social two amazing reserchers @magdamartinezga.bsky.social and @grotzinger.bsky.social , from @emilyjacobs.bsky.social lab, talking about “Advancing the Neuroscience of Human Pregnancy”
Excited to be heading to Barcelona next week for the Parental Brain Conference! I’ll be speaking on “Promoting Big Datasets & Collaboration in Human Maternal Brain Research through @bowers-wbhi.bsky.social
” on Friday, May 9. Can’t wait to connect with this amazing community! #PB2025
