Changyang Linghu

Changyang Linghu, 33, is inspired by the concept of emergence: the idea that complex systems can take on properties that cannot be explained by their component parts alone. Understanding how this works in the human brain, which has 86 billion neurons, would entail recording cellular activity at a massive scale. Existing ways of measuring neural activity through electrical or light signals could never work with the brain as a whole, whereas brain-wide imaging tools like CT scans or fMRI lack single-cell precision.

Linghu devised a new approach. Instead of measuring cellular activity with an external interface, he sought to “trick” neurons into recording their activity themselves. To do so, he genetically engineered a set of two proteins that work like a ticker tape. When genes encoding them are delivered to a cell, the cell produces one of the proteins in a continually growing chain and the other only during cellular events, such as activities known to drive memory formation. Later, researchers can view that protein ticker tape under a microscope to get a timeline of the cell’s activity, similar to the way scientists study the rings of a tree.

Linghu has tested this method with both neurons cultured in a lab and in the brains of mice.  He and colleagues at the University of Michigan Neuroscience Institute, where he’s a professor of cell and developmental biology, have begun using AI to look for patterns in this data.  

Linghu hopes his technique could unpack one of the scientific world’s great mysteries: how the brain achieves high-level functions such as learning, memory, and consciousness.