Nicholette Zeliadt manages The Transmitters’s staff reporters and interns, and she commissions and edits news articles. She joined The Transmitter as news writer in 2014. Before that, she was a freelance writer and editor. Her work has appeared in The New York Times, Scientific American, Nature Medicine, Science and The Scientist.
Nicholette Zeliadt
Managing editor
The Transmitter
From this contributor
Leaving lasting marks with Tessa Montague
By
Nicholette Zeliadt
9 February 2024 | 7 min read
Spotted around the web: INSAR; cerebellar gene expression; pangenome
By
Jill Adams, Giorgia Guglielmi, Nicholette Zeliadt, Kristin Ozelli
12 May 2023 | 4 min read
Spotted around the web: Mapping histones; COVID-19 births; acetaminophen lawsuits
By
Jill Adams, Katharine Gammon, Peter Hess, Nicholette Zeliadt
4 November 2022 | 3 min read
New diagnostic code for PTEN syndrome may spur research
By
Nicholette Zeliadt
3 October 2022 | 4 min read
Education
- Ph.D. in environmental health, University of Minnesota
- B.A. in biochemistry, University of Iowa
Fellowships
- AAAS Mass Media Fellowship
Explore more from The Transmitter
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
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Juan Gallego
13 April 2026 | 8 min read
Error equation predicts brain’s ability to generalize
Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.
Error equation predicts brain’s ability to generalize
Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.
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Natalia Mesa
10 April 2026 | 5 min read
Embrace complexity to improve the translatability of basic neuroscience
Researchers must learn to view heterogeneity as an essential feature of the systems they study and a central consideration in experimental design, not a variable to control for or reduce.
Embrace complexity to improve the translatability of basic neuroscience
Researchers must learn to view heterogeneity as an essential feature of the systems they study and a central consideration in experimental design, not a variable to control for or reduce.
By
Linda Douw, Klaus Eyer, Lara Keuck
9 April 2026 | 5 min read