How autism researchers are applying machine-learning techniques
Researchers are using machine learning to improve diagnostic predictions of autism, create interactive support robots, and more.
Researchers are using machine learning to improve diagnostic predictions of autism, create interactive support robots, and more.
A new technique allows researchers to analyze raw data across multiple studies that use electroencephalography.
People with autism may have patterns of brain activity that are similar to those in typical people when interpreting social interactions.
A custom-built machine can scan the brains of awake mice and may improve our understanding of conditions such as autism.
Autistic children who have behavioral problems tend to have an enlarged right amygdala, and in girls the size is associated with the severity of certain behaviors.
People with mutations in a gene called TBR1 have unusual features in several brain regions, along with autism traits and developmental delay.
Autistic adults may not experience the typical age-related decline in brain regions related to vision.
Can brain scans, in the wrong hands, compromise research participants’ identity? The risk is minimal.
Associated primarily with its role in movement, the striatum may also influence the social difficulties of autistic people.
Autism researchers who use brain scans may not be accounting for the head motion caused by study participants’ breathing.