Machine learning identify key lifestyle factors for healthy brain function

The new research will provide insights into health and lifestyle indicators, including diet, physical activity and weight, which are most closely aligned with healthy brain function across lifespans. In this study, machine learning was used to determine which variables best predicted their ability to quickly complete tasks without distraction.

It has been reported in Nutritional Journalthis study found that age, blood pressure, and body mass index were the most powerful predictors of success in a test called the flanker task.

Diet and exercise also played a smaller but relevant role in test performance.

“This study used machine learning to evaluate many variables at once to help identify the variables that are most closely aligned with cognitive performance,” said Nyman Khan, professor of health and kinesiology at the University of Illinois Urbana-Champaign, who led the work of Dr. Kinesiology. Student Shreya Berma. “Standard statistical approaches cannot accept this level of complexity at once.”

To build the model, the team used data collected from 374 adults aged 19 to 82. Data included participants' demographics such as age, BMI, blood pressure, and physical activity level, as well as dietary patterns and performance from the flanker test, which measured processing speed and accuracy when determining the orientation of the central arrows where other arrows pointed in the same or opposite directions were pinched.

“This is an established measure of cognitive function that assesses attention and inhibitory control,” Khan said.

Previous studies have found that several factors are related to cognitive conservation throughout life span, Khan said.

Compliance with the Healthy Diet Index, a measure of diet quality, is associated with superior executive function and processing speed in older adults. Other studies have found that diets rich in antioxidants, omega-3 fatty acids and vitamins are associated with improved cognitive function. ”

Nyman Kahn, Professor of Health and Kinesiology at the University of Illinois, Urbana-Champaign University

The dietary approaches to stop eating a combination of two known as the high blood pressure, or dash, Mediterranean diet, and mind diet, are all “related to protective effects against cognitive decline and dementia,” the researchers wrote. Physical factors such as BMI and blood pressure and increased physical activity are also powerful predictors of cognitive health or reduction in aging.

“Obviously, cognitive health is driven by a number of factors, but which one is most important?” Verma said. “We wanted to assess the relative strength of each of these factors in combination with everything else.”

Machine Learning provides a promising way to analyze large datasets with multiple variables and identify patterns that may not be clear through traditional statistical approaches,” the researchers write.

The team tested a variety of machine learning algorithms to optimally examine a variety of factors to predict the speed of accurate responses in flanker tests. Researchers tested the predictive capabilities of each algorithm and used a variety of approaches to verify what appeared to perform best.

They found that age was the most influential predictor of performance on the test, with persistent diastolic blood pressure, BMI and systolic blood pressure. Compliance with a healthy feeding index predicted less cognitive performance than blood pressure or BMI, but was also correlated with improved test performance.

“Physical activity appears as a moderate predictor of reaction time, and the results suggest that it may interact with other lifestyle factors, such as diet and weight, to affect cognitive performance,” Kahn said.

“This study reveals how machine learning can bring accuracy and nuance to the field of nutritional neuroscience,” he said. “By moving beyond traditional approaches, machine learning can help coordinate strategies for aging populations, individuals at metabolic risk, or those seeking to enhance cognitive function through lifestyle changes.”

I. of I. Personalized Nutrition Initiative and the National Center for Supercomputing Applications supported this study.

Kahn is a nutritionist and affiliate professor at Illinois Department of Nutrition Science, Neuroscience Programs and Beckman Institute of Advanced Science and Technology.