Emma Young is an award-winning science and health journalist and the author of Sane: How I shaped up my mind, improved my mental strength, and found calm. A former reporter and editor for New Scientist, working in London and Sydney, she now freelances from an attic in Sheffield. As E L Young (in the UK, Emma in the USA), she is also the author of the STORM series of science-based thrillers for kids.
Emma Young
From this contributor
For people with alexithymia, emotions are a mystery
One in 10 people struggle to recognize their emotions. New research suggests a vital link between our ability to sense our physical bodies and knowing how we feel.

For people with alexithymia, emotions are a mystery
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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.