Vanessa Vogel-Farley is co-founder of the Commission on Novel Technologies for Neurodevelopmental Copy Number Variants.
Vanessa Vogel-Farley
Co-founder
Commission on Novel Technologies for Neurodevelopmental Copy Number Variants
From this contributor
Lumping versus splitting with autism-linked variants: A conversation with Vanessa Vogel-Farley and Yssa DeWoody
Researchers have long studied subgroups of people who share genetic variants, but the newly formed ‘CNV Commission’ is also looking at people with shared traits across different neurodevelopmental conditions.
Lumping versus splitting with autism-linked variants: A conversation with Vanessa Vogel-Farley and Yssa DeWoody
By
Peter Hess
22 August 2022 | 5 min read
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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.
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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.
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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.
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Alona Fyshe
19 May 2025 | 7 min read