Raphael Bernier is professor of psychiatry at the University of Washington and clinical director of the Seattle Children’s Autism Center.

Raphael Bernier
Assistant Professor
University of Washington, Seattle
From this contributor
Through play, children with autism can hone thinking skills
Clinicians can use play to deliver therapies that could improve a child’s social skills, language and certain cognitive capacities.

Through play, children with autism can hone thinking skills
Best practices
Guidelines for the use of electroencephalography in autism will ensure that researchers have a common set of standards, which will speed up discovery, say Sara Jane Webb and Raphael Bernier.
How do we measure autism severity?
Accurately measuring the severity of autism remains a challenge for the field. The answer may lie in using more than one approach that varies depending on whether it is being applied in a clinical or research context, says Raphael Bernier.
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.