Aprinda Indahlastari’s art shines in annual scientific computation image contest

illustration showing brain with colored patterns representing electrical stimulation
An illustration created by Dr. Aprinda Indahlastari is among the winners of the annual Coalition for Academic Scientific Computation image contest.

By Jill Pease

An illustration by Aprinda Indahlastari, Ph.D., an assistant professor of clinical and health psychology at the University of Florida College of Public Health and Health Professions, has been selected for the annual Coalition for Academic Scientific Computation image contest. Indahlastari’s image, which depicts electrical current being distributed across the brain during a non-invasive treatment designed to improve cognitive health, appears on page 12 of the coalition’s 2024 brochure.

“My inspiration came directly from my research on electrical stimulation as a safe, non-invasive therapy for the brain,” Indahlastari said. “Constructing models like this has been a passion of mine since my graduate studies, making it particularly inspiring to showcase my work to a general audience in a way that is both informative and artistic.”

Transcranial direct current stimulation, or tDCS, is delivered by a safe, weak electrical current passed through electrodes placed on a person’s head. The treatment holds promise as an effective, drug-free approach for someday warding off Alzheimer’s disease and other dementias, but determining optimal dosing has been a challenge because of individual differences in anatomy.

Indahlastari, Aprinda
Dr. Aprinda Indahlastari

Indahlastari is part of a study led by Adam Woods, Ph.D., PHHP’s associate dean for research, associate professor of clinical and health psychology and co-director of the Center for Cognitive Aging and Memory at UF’s Evelyn F. and William L. McKnight Brain Institute, and Ruogu Fang, Ph.D., an assistant professor of biomedical engineering at the UF College of Engineering. The team is using artificial intelligence to evaluate more than 16 million data points collected from previous studies in order to model how the electrical current is distributed across the brain during the procedure with a goal of creating personalized approaches for patients.

“By observing how this model output relates to measured behavioral changes, doctors can adjust treatment parameters to achieve the best results for each patient,” Indahlastari said.