An international research team led by the University of Michigan has developed new methods to identify which regions of the brain are active at different times of day, using single-cell resolution in mouse models. The findings, published in PLOS Biology, provide a detailed look at how brain signaling changes during sleep and wakefulness.
The researchers designed both an experimental protocol and computational analysis to track neuronal activity across time. Their work could eventually lead to objective measures for assessing fatigue in humans, with possible applications for ensuring that individuals in critical roles—such as pilots and surgeons—are sufficiently rested before performing their duties.
“We undertook this difficult study to understand fatigue,” said Daniel Forger, senior author and professor of mathematics at the University of Michigan. “We’re seeing profound changes in the brain over the course of the day as we stay awake and they seem to be corrected as we go to sleep.”
Forger noted that current self-assessments of tiredness are unreliable: “We’re actually terrible judges of our own fatigue. It’s based on our subjective tiredness,” he said. “Our hope is that we can develop ‘signatures’ that will tell us if people are particularly fatigued, and whether they can do their jobs safely.”
The project received support from several organizations, including the U.S. National Science Foundation, the U.S. Army Research Office, and the Human Frontier Science Program (HFSP). International collaboration was central to the study’s success.
While University of Michigan researchers focused on data analysis methods, collaborators in Japan and Switzerland developed advanced experimental approaches. These included light sheet microscopy for creating 3D images of mouse brains and genetic tagging techniques that caused active neurons to glow under a microscope.
Konstantinos Kompotis, co-author and senior scientist at the Human Sleep Psychopharmacology Laboratory at the University of Zurich, commented on these advances: “We know from studies over the last 20 or 30 years, how to decipher how one aspect—a gene or a type of neuron, for instance—can contribute to behavior,” he said. “But we also know that whatever governs our behavior, it’s not just one gene or one neuron or one structure within the brain. It’s everything and how it connects and interacts at a given time.”
Teams from three countries participated: those led by Forger at Michigan; Kompotis in Zurich; and Hiroki Ueda at RIKEN Center for Biosystems and Dynamics Research in Japan.
Their results showed that as mice wake up, neural activity begins in subcortical layers before shifting toward cortical regions later in their waking period—a pattern described by Kompotis: “The brain doesn’t just change how active it is throughout the day or during a specific behavior,” he said. “It actually reorganizes which networks or communicating regions are in charge, much like a city’s roads serve different traffic networks at different times.”
Forger suggested these observations may lay groundwork for identifying reliable markers of fatigue or even connections with mental health conditions: “This study doesn’t touch on that,” he said. “But I do think the activity we saw in different regions is going to be important for understanding certain psychiatric disorders.”
Kompotis indicated plans to apply these experimental techniques with industry partners studying drug effects on brain activity.
Although some experimental tools cannot yet be used with humans, aspects of these findings may translate from mice to people. Co-author Guanhua Sun explained that while human imaging methods such as EEGs or MRIs offer less detail than what was achieved here, their computational approach could be adapted for use with human data sets.
“The mathematics behind this problem are actually quite simple,” Sun said.
Sun added: “The way we detect human brain activity is more coarse-grained than what we see in our study,” he said. “But the method we introduced in this paper can be modified in a way that applies to that human data. You could also adapt it for other animal models…that are being used to study Alzheimer’s and Parkinson’s. I would say it’s quite transferable.”
The team dedicated their publication to Steven Brown—a senior co-author who died during the project—in recognition of his role as professor and section leader for chronobiology and sleep research at University of Zurich.
“Steve was a perfect collaborator,” Forger said.
Kompotis added: “We learned how important one person can be in scientific research, be it in brainstorming or in bridging ideas and concepts. Steve was a core element of this collaboration…It is yet another reason for us to be very proud of this story.”
