psychiatry and behavioral science
Duke Awarded $12M Research Grant to Use Artificial Intelligence to Detect Autism
The grant, from the National Institute of Child Health and Human Development, extends the Duke Autism Center of Excellence research program for an additional 5 years. Geraldine Dawson, Ph.D., director of the Duke Center for Autism and Brain Development and professor of psychiatry and behavioral sciences, will lead a team of researchers that includes Duke faculty from psychiatry, pediatrics, biostatistics and bioinformatics, computer and electrical engineering, and civil and environmental engineering. "We are thrilled to receive this award, which allows Duke to remain at the forefront of autism research," Dawson said. "Our goal is to use advanced computational techniques to develop better methods for autism screening that will reduce known disparities in access to early diagnosis and intervention." In a project led by Dawson and Guillermo Sapiro, Ph.D., professor of electrical and computer engineering, researchers will test a digital app, used by parents at home on a smart phone, to videotape young children's behavior and interactions with their caregivers.
- Health & Medicine > Therapeutic Area > Neurology > Autism (1.00)
- Health & Medicine > Therapeutic Area > Genetic Disease (1.00)
Adolescents with autism may engage neural control systems differently, study finds: Researchers used brain scans to measure proactive and reactive executive control
Executive control difficulties are common in individuals with autism and are associated with challenges completing tasks and managing time. The study, published in Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, sought to tease out whether these difficulties represent a disruption in proactive executive control (engaged and maintained before a cognitively demanding event) or in reactive executive control (engaged as the event occurs). Using functional magnetic resonance imaging (fMRI), the researchers took brain scans of 141 adolescents and young adults ages 12-22 (64 with autism, 77 neurotypical controls) enrolled in the Cognitive Control in Autism Study. During the scan, the participants completed a task that required them to adapt their behavior. They were shown a green or red cue, followed by a white arrow (probe) pointing left or right.
Good sense of smell may indicate lower risk of dementia in older adults: study
Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. "Stop and smell the roses" may actually be important when it comes to detecting your risk for dementia and getting early treatment for the condition, according to a new study. A study out of the University of California San Francisco found that older Americans who can identify odors like roses, lemons, onions, paint-thinner, and turpentine may have half the risk of developing dementia compared to those with significant sensory loss, according to researchers performing the study. "The olfactory bulb, which is critical for smell, is affected fairly early on in the course of the disease," said first author Willa Brenowitz, Ph.D., of the UCSF Department of Psychiatry and Behavioral Sciences and the Weill Institute for Neurosciences, in a statement.
- Health & Medicine > Therapeutic Area > Neurology > Dementia (1.00)
- Health & Medicine > Therapeutic Area > Neurology > Alzheimer's Disease (0.94)
VUMC study to use artificial intelligence to explore suicide risk
With the help of a five-year, $2.7 million grant from the National Institute of Mental Health, researchers at Vanderbilt University Medical Center will use computational methods to shed light on suicidal ideation and its relationship to attempted suicide, predict suicidal ideation and suicide attempt using routine electronic health records (EHRs) and explore the genetic underpinnings of both. From 1999 to 2017, the all-ages suicide rate in the United States increased 33%, from 10.5 to 14.0 per 100,000 population. In 2017 there were 47,173 recorded suicides, making it the nation's 10th leading cause of death. The principal investigators for the study are internist and clinical informatician Colin Walsh, MD, MA, assistant professor of Biomedical Informatics, Medicine, and Psychiatry and Behavioral Sciences, and geneticist and computational biologist Douglas Ruderfer, PhD, MS, assistant professor of Medicine, Psychiatry and Behavioral Sciences, and Biomedical Informatics. In previous work Walsh and colleagues used EHR data and machine learning techniques to develop predictive algorithms for attempted suicide.