David Skuse
Professor
University College London
From this contributor
Few people mourn Asperger syndrome’s loss from diagnostic manuals
Our concept of autism has evolved over the past 20 years, rendering redundant the diagnostic labels of Asperger syndrome and pervasive developmental disorder-not otherwise specified.
Few people mourn Asperger syndrome’s loss from diagnostic manuals
Defining language deficits across autism spectrum
We are on the verge of a seismic shift in the definition of autism spectrum disorders, says David Skuse. Under proposed guidelines for autism diagnosis, the canard that most people with the disorder cannot speak, or have such disordered language that they cannot sustain a conversation, has been abandoned.
Defining language deficits across autism spectrum
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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.