Jane Lee is a freelance writer based in Washington, D.C.
Jane Lee
Freelance Writer
SFARI.org
From this contributor
Diagnosis eludes many girls with autism, study says
Girls are less likely to be diagnosed with autism than boys are, unless they also have intellectual or behavioral problems, according to a study published 26 June in the Journal of the American Academy of Child and Adolescent Psychiatry.
Diagnosis eludes many girls with autism, study says
By
Jane Lee
3 September 2012 | 5 min read
Tuberous sclerosis gene loss triggers autism-like features
Losing one or both copies of TSC1, one of the two genes responsible for tuberous sclerosis complex, in specific cells of the cerebellum can trigger several autism-like behaviors in mice, according to research published 1 July in Nature.
Tuberous sclerosis gene loss triggers autism-like features
By
Jane Lee
26 July 2012 | 5 min read
Explore more from The Transmitter
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
By
Lauren Schenkman
20 May 2025 | 6 min read
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
By
Jill Adams
20 May 2025 | 2 min read
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
By
Alona Fyshe
19 May 2025 | 7 min read