PHHP researchers studying the use of a noninvasive brain stimulation treatment paired with cognitive training have found the therapy holds promise as an effective, drug-free approach for someday warding off Alzheimer’s disease and other dementias.
Yet determining optimal dosing for the treatment known as transcranial direct current stimulation, or tDCS, which is delivered by a safe and weak electrical current passed through electrodes placed on a person’s head, has been a challenge because of individual differences in anatomy.
“In the field of tDCS, a fixed dosing approach is the standard convention,” said Adam Woods, Ph.D., an associate professor of clinical and health psychology and associate director of the Center for Cognitive Aging and Memory at UF’s Evelyn F. and William L. McKnight Brain Institute. “All people receive exactly the same dose of tDCS, even though we know that individual differences in head and brain anatomy significantly alter how much current enters the brain and where it goes.”
Woods and his colleagues, including fellow principal investigator Ruogu Fang, Ph.D., an assistant professor of biomedical engineering at the UF College of Engineering, have received a $2.9 million grant from the National Institute on Aging to use AI technology to evaluate 16 million data points captured from research participants. The aim is to develop a precision dose for each individual who receives the treatment.
“AI methods allow analyses across multiple data types and sources. For example, analyzing multi-modal neuroimaging data such as MRI and fMRI data, and combining them with behavioral outcome data,” said team member Aprinda Indahlastari, Ph.D., a research assistant professor of clinical and health psychology. “Simply put, AI methods allow us to analyze big data sourced from different types of acquisition methods and enable us to find important characteristics across data sources that are unique to each person.”