Involving both maintenance and manipulation of information, working memory is essential for higher-order functions such as comprehension, learning, reasoning, and decision-making. Furthermore, deficits in working memory are fundamental problems associated with a wide range of progressive and nonprogressive conditions, including developmental disorders, learning disabilities, traumatic brain injury, stroke, and multiple sclerosis, according to presenter Sohae Chung, PhD, a research scientist at NYU Langone Medical Center in New York City.
Very little is known, however, about how working memory relates to underlying brain white-matter microstructure, Chung said.
"Our study elucidates the underlying relationship between white-matter microstructure as assessed by multishell diffusion MRI and performance on working memory tasks, and it raises the potential utility of diffusion metrics to predict impairment of working memory," she said.
The researchers concluded that machine-learning approaches using white-matter tract integrity (WMTI) metrics derived from MRI could be used to predict a brain white-matter microstructural association with working memory.
"Our findings of higher [axonal water fraction] with better performance on [the Wechsler Adult Intelligence Scale (WAIS) IV Letter-Number Sequencing test] go along with a greater number of axons and greater myelination in these regions, causing efficient and faster information processes," Chung told AuntMinnie.com. "Our results demonstrate the potential utility of diffusion [WMTI] metrics in combination with machine-learning approaches to serve as early biomarkers of working memory impairment."
How did they do it and what else did they find? Attend this presentation on Tuesday to learn more.
