Rachel Moseley is principal academic in psychology at Bournemouth University in the United Kingdom. Her research centers around issues that autistic adults face, including mental ill-health, suicidality, self-injury, aging and late diagnosis. She also investigates aspects of cognition and social communication in autistic people and how these differ depending on personal characteristics, such as sex.

Rachel Moseley
Principal academic
Bournemouth University
From this contributor
Autism and menopause: Q&A with Rachel Moseley and Julie Turner-Cobb
Menopause poses significant challenges for autistic people, according to a small survey published in 2020 — the first to explore the transition among people with autism traits.

Autism and menopause: Q&A with Rachel Moseley and Julie Turner-Cobb
Autism and eating disorders may have an emotional connection
Eating disorders have the highest mortality rates of any kinds of mental illness. They don’t discriminate, affecting people of all ethnicities, sexualities, gender identities, ages and backgrounds.

Autism and eating disorders may have an emotional connection
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.