Jacqueline Crawley is professor emeritus of psychiatry and behavioral sciences at the University of California, Davis.
Jacqueline Crawley
Professor
University of California, Davis
From this contributor
Optimizing behavioral assays for mouse models of autism
As the number of autism rodent models climbs, it is a good time for the field to step back and consider the best practices for assessing autism-like symptoms in rodents, says Jacqueline Crawley.
Optimizing behavioral assays for mouse models of autism
Transparent reports
New standards for animal studies, including an emphasis on replicating results and the publication of negative findings, are vital for research progress, says Jacqueline Crawley.
Promises and limitations of mouse models of autism
Good mouse models of autism, and accurate tests to assay their phenotypes, are key to both narrowing down a cause and developing effective treatments, argues expert Jacqueline Crawley.
Promises and limitations of mouse models of autism
Explore more from The Transmitter
The fast-expanding repertoire of mitochondria in the brain
More than cellular powerhouses, these organelles also seem to help synapses communicate, support memory formation and even shape behavior.
The fast-expanding repertoire of mitochondria in the brain
More than cellular powerhouses, these organelles also seem to help synapses communicate, support memory formation and even shape behavior.
When autistic kids grow up, Chapter 5: The war dial
“You have to reshape the whole system.” Tempest McDonald earns a measure of peace.
When autistic kids grow up, Chapter 5: The war dial
“You have to reshape the whole system.” Tempest McDonald earns a measure of peace.
Scientists decry conference’s use of hidden prompts to snare AI peer reviews
The invisible messages, which instruct large language models to use telltale phrases in a peer-review report, are effective in catching artificial-intelligence misuse but also erode trust, some say.
Scientists decry conference’s use of hidden prompts to snare AI peer reviews
The invisible messages, which instruct large language models to use telltale phrases in a peer-review report, are effective in catching artificial-intelligence misuse but also erode trust, some say.