A new AI algorithm can predict whether a person is on the autism spectrum by examining their brain scans. The algorithm can also predict the severity of symptoms and could be used as an early detection tool for ASD.
In children with autism, girls had different patterns of connectivity than boys in brain areas associated with motor, language, and visuospatial attention. Generally, girls display fewer repetitive behaviors than boys, which may contribute to delays in ASD diagnosis for females.
Around 25% of patients with multiple sclerosis have blood antibodies that bind to the Epstein-Barr virus and EBNA1, a protein made in the brain and spinal cord. Researchers say this is the first study to definitely show that the Epstein-Barr virus can cause multiple sclerosis in some patients.
SAINT, a new intensive and individualized form of transcranial magnetic stimulation reduces symptoms of depression within days of treatment. 80% of the people administered SAINT reported remission from depression symptoms that lasted for months following treatment.
Serotonin-producing neurons in the brainstem release serotonin throughout the brain during moments of novel social encounters. The release of serotonin stimulates neurons in the medial septum via a subtype of serotonin-sensitive receptor molecules. Blocking the release of this receptor molecule prevents the formation of new social memories.
Recent studies have found significant biases in artificial intelligence algorithms. Researchers are raising their concerns about AI biases associated with medical devices and algorithms used to analyze health risks. If left unchecked, they say, the technologies could continue to perpetuate sex, gender, and race biases that could exacerbate health care disparities.