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Population study downgrades some copy number variants’ impact on autism
Some copy number variants may boost a person’s chances of having autism, but to a lesser extent than previously thought.
Population study downgrades some copy number variants’ impact on autism
Some copy number variants may boost a person’s chances of having autism, but to a lesser extent than previously thought.
From 0 to 60 in 10 years
After a decade of fast-paced discovery, researchers are racing toward bigger datasets, more genes and a deeper understanding of the biology of autism.
From 0 to 60 in 10 years
After a decade of fast-paced discovery, researchers are racing toward bigger datasets, more genes and a deeper understanding of the biology of autism.
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.
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.
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.