Features Editor
Spectrum
Ingrid Wickelgren edits Deep Dives, Spectrum’s long-form stories on important topics in autism research.
Before joining the foundation in 2015, Ingrid was senior editor at Scientific American Mind and wrote the Streams of Consciousness blog for ScientificAmerican.com. She has also authored three popular science books and has written for Science, Discover, Health and The New York Times.
Ingrid has a B.S. in biological sciences from Stanford University.
An electrical brain implant all but erased the obsessions that had consumed Becky Audette, years after her autism diagnosis. Could similar implants help other people with severe autism?
Scientists dish about the biggest challenges they face as they tackle tough questions about autism.
A European initiative that aims to provide a framework for clinical trials in autism has developed tools to track treatment responses.
An analysis of blood samples from nearly 17,000 individuals with autism points to new regions of the genome likely to be involved in the disorder.
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.
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.
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
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.
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.