Watching a football game on a glitchy internet stream can be frustrating: The screen freezes during a scoring drive, and by the time the picture returns, the touchdown has already happened. You saw the snap and the celebration, but you missed the play that made the difference.
Neuroscientists face a similar problem. The brain makes critical decisions in mere milliseconds, but current imaging tools are often too slow to capture the process. Because they can only see the before and after, the crucial steps in between remain a mystery—forcing researchers to guess the "plays" the brain is running.
A Johns Hopkins team led by Adam Charles, an assistant professor of biomedical engineering, has received a $2.7 million National Institutes of Health grant to change that. Over the next four years, Charles will collaborate with co-investigators Ji Yi, associate professor of biomedical engineering, and Dwight Bergles, professor of neuroscience, to develop an imaging system that can capture brain activity 20 to 50 times faster than current tools.
By combining streamlined optics with powerful artificial intelligence, the project aims to provide a slow-motion replay of the brain's rapid-fire conversations.
"We view this project as the next step in the evolution of neural recording," Charles says. "This technology will allow us to decipher how neurons interact to create perception, action, and thought at the brain's true speed. By recording every electrical 'spike' across the entire brain, we can finally see exactly how biological circuits pick up the slack as other cells die off during disease."
The new system hinges on capturing the lightning-fast way neurons communicate. It's a chain reaction: When a neuron fires, an electrical pulse travels along nerves and triggers the release of glutamate—the chemical messenger that activates the next cell in the line.
This signaling program runs nonstop. When it works well, we learn and form memories. But when these signals fall out of sync or lose their timing, brain function can suffer, contributing to mental illness and neurodegenerative diseases.
The traditional way to track these signals requires inserting tiny wires into the brain. While effective, these wires can only "hear" the neurons close to them. This narrow focus makes it difficult to understand how the entire brain works to process information, Charles explains.
Image caption: From left, Dwight Bergles, Adam Charles, and Ji Yi
To overcome the limitations of wires, the team is turning to imaging with light. The researchers will deploy specialized fluorescent sensors that convert voltage fluctuations and glutamate release into light. By using a microscope to capture these flashes, the team can monitor brain activity across large areas simultaneously.
According to the team, this optical approach is also a game changer for studying neurodegeneration. Unlike wires, which provide a limited snapshot, imaging allows researchers to track individual neurons over long time periods—revealing the subtle, early changes that occur as conditions like Alzheimer's and dementia take hold.
"Our goal is to create a high-resolution map that shows exactly where these signals fall out of sync," Charles says. "By tracking both the electrical pulses and the chemical links between cells, we can see how the brain's connections change as it moves from a healthy state to a diseased one."
The team will validate the system using zebrafish and mice—models whose biology makes it possible to image large areas of the brain, or even the entire organ, at once.
Charles emphasizes that the true catalyst for this project is the unique collaborative environment at Johns Hopkins. The effort brings together optical engineering, neuroscience, biology, and data science—powered by resources like the Kavli Neuroscience Discovery Institute and the university's growing strength in AI through the Data Science and AI Institute.
"Learning about the brain now requires the combined expertise of neuroscientists, engineers, and data scientists to build the devices and analyze the increasingly complex data they produce," Charles says. "The brain is extraordinarily complex and challenging to study. It takes a community of scientists to reveal its secrets."
