{"id":201,"date":"2025-06-16T06:20:12","date_gmt":"2025-06-16T13:20:12","guid":{"rendered":"https:\/\/scienceblog.com\/neuroedge\/?p=201"},"modified":"2025-06-16T06:20:12","modified_gmt":"2025-06-16T13:20:12","slug":"ai-predicts-your-brain-speed-using-simple-health-data","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/neuroedge\/2025\/06\/16\/ai-predicts-your-brain-speed-using-simple-health-data\/","title":{"rendered":"AI Predicts Your Brain Speed Using Simple Health Data"},"content":{"rendered":"

Scientists have developed a machine learning algorithm that can predict how quickly your brain processes information using just a few basic health measurements.<\/p>\n

The new study<\/a> reveals that age, blood pressure, and body mass index are the strongest predictors of cognitive performance\u2014more powerful than diet or exercise habits. This discovery could transform how doctors identify people at risk for cognitive decline, potentially years before symptoms appear.<\/p>\n

The research, published in The Journal of Nutrition, analyzed data from 374 adults aged 19 to 82 years to determine which health factors best predicted performance on cognitive tests. Unlike traditional studies that examine one factor at a time, this approach used artificial intelligence to evaluate multiple variables simultaneously.<\/p>\n

Three Key Predictors Emerge<\/h2>\n

“This study used machine learning to evaluate a host of variables at once to help identify those that align most closely with cognitive performance,” said Naiman Khan, a professor of health and kinesiology at the University of Illinois Urbana-Champaign who led the research. “Standard statistical approaches cannot embrace this level of complexity all at once.”<\/p>\n

The algorithm tested participants on a flanker task\u2014a well-established cognitive test where people must focus on a central arrow while ignoring distracting arrows pointing in different directions. Faster reaction times indicate better brain function.<\/p>\n

After analyzing 18 different health and lifestyle factors, the machine learning model identified a clear hierarchy of importance. Age topped the list with an importance score of 0.208, followed by diastolic blood pressure at 0.169 and BMI at 0.079. Surprisingly, factors like sex and ethnicity had minimal predictive power, scoring just 0.003 and 0.005 respectively.<\/p>\n

Diastolic Pressure Matters More Than Systolic<\/h2>\n

One particularly intriguing finding that wasn’t highlighted in the initial research summary involves blood pressure measurements. The study revealed that diastolic blood pressure\u2014the bottom number in a blood pressure reading\u2014was significantly more predictive of cognitive performance than systolic pressure (the top number).<\/p>\n

This distinction matters because diastolic pressure reflects the constant pressure in arteries between heartbeats, potentially indicating how well blood vessels deliver oxygen to the brain during rest periods. The finding suggests that sustained vascular health may be more critical for brain function than peak blood pressure spikes.<\/p>\n

Key Findings Include:<\/h3>\n