Jeremy Veenstra-VanderWeele uses molecular and translational neuroscience research tools in the pursuit of new treatments for autism.
Jeremy Veenstra-VanderWeele
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Why serotonin medications may yet help children with autism
A class of medications used to treat obsessive-compulsive disorder seems to ease compulsive behaviors in adults with autism. Why can't we tell if these medications work similarly in children with the condition?

Why serotonin medications may yet help children with autism
How to evaluate new medications for autism
There are no available medications for treating autism’s core symptoms, but there are several candidates in clinical trials. Jeremy Veenstra-VanderWeele describes the factors researchers must take into account when developing drugs for the disorder.

How to evaluate new medications for autism
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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.