![]() ![]() ![]() ![]() They found patterns of brain connections linked with behavioral traits in people with autism, such as verbal ability, social affect, and repetitive or stereotypic behaviors. The study, published on March 9 in the journal Nature Neuroscience, leveraged machine learning to analyze newly available neuroimaging data from 299 people with autism and 907 neurotypical people. People with autism spectrum disorder can be classified into four distinct subtypes based on their brain activity and behavior, according to a study from Weill Cornell Medicine investigators. Researchers at Weill Cornell Medicine identified four distinct subtypes of autism spectrum disorder through machine learning analysis of neuroimaging data, potentially paving the way for more personalized treatments. The painted background of a sequencing array represents the molecular associations of the autism subtypes. White light or “data” passes into the prism or “machine learning algorithm,” splitting into four colored light paths that represent the spectrum of autistic people in the four autism subtypes. Here, the 3D prism cube represents the machine learning of the three brain-behavior dimensions, etched onto the prism’s glass. Machine learning of brain-behavior dimensions reveals four subtypes of autism spectrum disorder linked to distinct molecular pathways. ![]()
0 Comments
Leave a Reply. |