Researchers at Johns Hopkins Medicine have demonstrated a new approach to brain imaging that enables continuous monitoring of brain activity and the physiologic changes associated with neurological disease progression for more than 24 hours in freely moving mouse models. The cloud-based miniaturized microscope, called CloudScope, operates autonomously and allows scientists to access live imaging data remotely from anywhere in the world, creating new opportunities to study diseases as they develop over time.

The federally funded research, published in Nature Methods, addresses a long-standing challenge in neuroscience and neuropathology: how to continuously observe biological processes that unfold over hours, days and even weeks in the brain.

Researchers say the study demonstrates the ability to remotely capture and analyze changes in brain activity, blood flow, blood vessel remodeling, oxygenation and cellular behavior over extended periods, providing a more holistic picture of brain disease progression than conventional imaging approaches.

“We started with a fundamental question: If we wanted to image a seizure or brain tumor formation continuously in a preclinical or animal model over 24 hours or longer, how would we do that?” says Arvind Pathak, Ph.D., professor of radiology, oncology, and biomedical and electrical engineering at Johns Hopkins. “The consequence of us working through this question and its associated challenges is what resulted in this innovation.”

Researchers say the work establishes a new research paradigm they call “neurosurveillance,” which enables scientists to remotely follow and assess brain function and disease progression continuously and in unprecedented detail.

Using this approach, the team captured spontaneous seizures occurring several hours after a drug-induced seizure in mice, events that would have been missed using conventional short-term imaging methods. In separate studies of brain cancer, researchers were able to characterize the behavior of individual cancer cells and observe dynamic changes in the brain’s “microenvironment” as the disease progressed. These findings suggest that continuous monitoring may reveal critical biological events that occur outside the limited observation windows typically used in laboratory research.

“Most central nervous system diseases develop over hours, days or even weeks. Yet modern imaging tools are designed to continuously probe only a small fraction of this time window,” says Janaka Senarathna, Ph.D., assistant professor of radiology and lead author of the study. “We developed a device to break this time barrier.”

In addition to advancing neuroimaging research, the investigators say they have also demonstrated a promising application involving artificial intelligence (AI). By combining the first-ever 24-hour brain imaging dataset with video recordings of the lab animals’ behavior, the team successfully trained an AI framework to predict whether an animal was minimally mobile, moderately active or running based solely on neuronal activity measurements made with the device. The researchers believe this approach could help scientists better understand the neurological effects of conditions such as stroke or Parkinson’s disease and potentially reveal new insights into the relationship between brain activity and behavior. Additionally, researchers say the device enables time-shared imaging from anywhere in the world, and it creates a pathway to reduce animal use while enabling neuroscientific and neuropathological insights.

Pathak emphasized the collaborative nature of the project, which involved researchers from multiple Johns Hopkins departments and schools, including the Department of Neuroscience (David Linden, Ph.D., Julia Brill, Ph.D., Devorah VanNess), the Department of Biomedical Engineering (Nitish Thakor, Ph.D., Claudia Ren, Ph.D.), the Department of Chemical and Biomolecular Engineering (Darren Yang, Shruthi Bare), the Department of Electrical Engineering (Subhrajit Das), the Department of Radiology (Vu Dinh), Kennedy Krieger Institute (Mingyao Ying, Ph.D.) and the Johns Hopkins University Applied Physics Laboratory (Amit Banerjee, Ph.D.).

To explore the effect of disease on different brain regions, the team plans to continue expanding the platform’s capabilities, such as imaging larger regions of the animals’ brains and leveraging AI to accelerate brain imaging and cancer cell tracking.

The research was supported by grants from the National Cancer Institute (5R01CA237597, 5R01CA196701) and the National Institute of Neurological Disorders and Stroke (5R21NS138938).

The authors affiliated with The Johns Hopkins University have no conflicts of interest to declare under Johns Hopkins University policies.