U-M leads multi-university partnership that aims to predict cognitive fatigue in individuals

Researchers at the University of Michigan are leading a multi-university partnership that aims to understand and predict cognitive fatigue in individuals.

The five-year project will examine cognitive fatigue across multiple timescales, distinct aspects of cognition and in different individuals with multiscale whole cortex models, says Daniel Forger, the Robert W. and Lynn H. Browne Professor of Science, professor of mathematics, and research professor in computational medicine and bioinformatics.

The research will focus on the build-up fatigue in the brain, for example, during sleep deprivation and when individuals are working at times when their daily (circadian) clock is misaligned. The work will use mathematics and mathematical models to make predictions that researchers will experimentally test to have meaningful impacts on fatigue research and how it relates to sleep, depression and cognitive performance.

With a $6.25 million grant from the Department of Defense, Forger and colleagues will build personalized models of sleep, circadian rhythms, physical activity and mood, and assess and optimize the efficacy of objective mobile sensors to detect the onset of cognitive fatigue.

Forger and U-M researchers Xudong “Sherman” Fan and Srijan Sen are collaborating with William “Scott” Killgore of the University of Arizona College of Medicine Tucson and Brieann Sattefeld and Hans van Dongen of Washington State University’s Elson S. Floyd College of Medicine.

Understanding the basis of fatigue in the brain is one of the key scientific challenges of our time. Mathematical modeling offers us the best hope of understanding cognitive fatigue, but new mathematical tools are needed to capture the complexity of the brain. It is exciting to test these models in cutting-edge sleep and human performance labs and in the real world.”

Daniel Forger, the Robert W. and Lynn H. Browne Professor of Science, Professor of Mathematics, and Research Professor in Computational Medicine and Bioinformatics

The interest in cognitive fatigue at Michigan emerged from an Ideas Lab funded through Michigan’s Biosciences Initiative on predicting human performance. This ideas lab brought together researchers from 11 schools and institutes.

Predicting cognitive fatigue is an essential factor in predicting human performance, said Forger, who first partnered with Sen through a grant funded by a Michigan Institute for Data Science Challenge Grant on Depression.

This new research on cognitive fatigue can also help us identify objective, actionable predictors of depression, and to develop truly personalized models of depression risk.”

Srijan Sen, U-M Researcher

The project is being funded as a part of the DoD’s $195 million Multidisciplinary University Research Initiative, or MURI. Funding for the fiscal year 2022 competition was recently awarded to 28 research teams across 63 U.S. academic institutions to pursue basic research spanning multiple scientific disciplines.

“By supporting teams whose members have diverse sets of expertise, the MURI program acknowledges that the complexities of modern science and engineering challenges often intersect more than one discipline and require creative and diverse approaches to tackle these problems,” said Bindu Nair, director of the Basic Research Office within the Office of the Undersecretary of Defense for Research and Engineering.

“This cross-fertilization of ideas can accelerate research progress to enable more rapid R&D breakthroughs and hasten the transition of basic research findings to practical application. It is a program that signifies a legacy of scientific impact and remains a cornerstone of the DoD’s basic research portfolio.”

The group is leading a research forum Dec. 13 that is open to the public.

Source:

University of Michigan

Posted in: Medical Science News | Medical Research News

Tags: Bioinformatics, Brain, Cortex, Depression, Efficacy, Fatigue, Fertilization, Medicine, Physical Activity, Research, Sleep

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