Jill U. Adams is a freelance science journalist based in Albany, New York. She covers health, mental health and biomedical research for such publications as The Transmitter, The Washington Post, Scientific American, Undark and The Scientist. She has a Ph.D. in pharmacology from Emory University in Atlanta, Georgia.
Jill Adams
Contributing writer
From this contributor
Autism-linked genes alter sleep behavior, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 13 April.
Autism-linked genes alter sleep behavior, and more
By
Jill Adams
14 April 2026 | 2 min read
Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
Cortical evolution, ZBTB18, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 30 March.
Infant Brain Imaging Study findings, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 23 March.
Leucovorin, long-read sequencing, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 16 March.
Explore more from The Transmitter
This paper changed my life: Erin Calipari ponders the nuances of rewarding and aversive stimuli
A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.
This paper changed my life: Erin Calipari ponders the nuances of rewarding and aversive stimuli
A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.
By
Erin Calipari
14 April 2026 | 5 min read
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?
By
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.
By
Natalia Mesa
10 April 2026 | 5 min read