Evan Gordon

@gordonneuro.bsky.social

Assistant Professor of Radiology at Washington University in St. Louis. Neuroscientist studying human brain organization with fMRI, functional connectivity, and DTI. https://sites.wustl.edu/evangordon/

“I have done all of the things that one is supposed to do to earn a tenure-track position. And I have done approximately 85% of them by typing prompts into a large language model and then moderately editing the output.” 🤣🤣🤣 brilliant 👌🏽 open.substack.com/pub/inprepar...

Opinion: I Was Not Allowed To Type Prompts Into ChatGPT During My Chalk Talk And This Is Discrimination

By Dr. Rachel Simmons, Postdoctoral Fellow, Stanford University

open.substack.com

A new Science study suggests variables linked to socioeconomic status—increased stress and reduced sleep—have strong relationships to brain structure and function in children. Brain differences observed are unrelated to genetic ancestry and may not be permanent. https://scim.ag/4opL5PF

Brain-wide associations in the Adolescent Brain Cognitive Development (ABCD) Study revealed that socioeconomic status exhibited the strongest associations with brain organization. Socioeconomic status dominated population-level variation through arousal-related patterns linked to sleep and stress, specifically norepinephrine and stimulant effect maps. Socioeconomic status models demonstrated robust generalizability across different groups, highlighting its importance as the primary variable in childhood BWAS. [Figure created by Lucy Reading-Ikkanda]

Is zip code everything? A new study involving U.S. children found it influences brain function and structure—specifically, kids in lower socioeconomic opportunity areas had sleep deprived and stressed brains. New on @sciam.bsky.social www.scientificamerican.com/article/chil...

Children's zip codes change their brains

Children living in areas with low socioeconomic opportunities have more tired and stressed brains, a new study finds

scientificamerican.com

This is one of the most socially important scientific findings I've ever been a part of. SES has a larger cross-sectional effect on brain function than any other variable. Prediction of IQ from brain data is actually mostly just predicting SES. Mind blowing.

Scott Marek@smarek0502.bsky.social · 2mo ago

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/...

In sum, SES dominates childhood brain organization. Zip code matters most. These findings have been at the forefront of my mind daily, with Darwin’s quote living rent free in my head: “if the misery of the poor not be caused by the laws of nature, but by our institutions, great be our sin.”

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This was evidence of shortcut learning, a well-known problem in machine learning & AI. Rather than models learning brain-IQ associations, they are learning links between the brain and SES. So much so that models trained to predict brain-IQ associations were better at predicting SES than IQ.

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When the correlation between SES and IQ was r<0.1, brain-IQ prediction performance was poor (out of sample r < 0.1). This was not the case for varying the training sample by the p-factor. Brain-IQ predictions only performed well when IQ & SES were correlated in the training sample.

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We first asked what happens if we control for SES in regression models? Tldr; the majority of brain-IQ associations became much weaker, so that 70% were no longer statistically significant. The strongest IQ associations were those most affected by SES.

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The BWAS maps of SES, exposome, and IQ did not match those of known neurobiology related to higher-order cognition (fronto-parietal). Rather, they overlapped with arousal - norepinephrine receptors, sleep, & stimulant use.

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I’ve officially resigned as Associate Editor for Frontiers in Systems Neuroscience. It used to be a reputable journal, but became a case study in how forced automation destroys academic integrity. 👇

I assigned random gender/ethnicity labels to scientific abstracts from the literature and then asked Claude to do a thematic analysis. Claude identified a clinical versus computational split for female/male authors and a DEI focus for Black/URM authors. All in completely random data.

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On second thought, the functional connectivity results make more sense. The electrically determined connections are a subset of the functional connectivity estimates. The correlation derived maps likely reflect recurrent connectivity of broader networks. Which is what a lot of us assume anyway.

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