In researching the causes and potential treatments for degenerative conditions such as Alzheimer's or Parkinson's disease, neuroscientists frequently struggle to accurately identify cells needed to understand brain activity that gives rise to behavior changes such as declining memory or impaired balance and tremors. A multidisciplinary team of Georgia Institute of Technology neuroscience researchers, borrowing from existing tools such as graphical models, have uncovered a better way to identify cells and understand the mechanisms of the diseases, potentially leading to better understanding, diagnosis, and treatment. Their research findings were reported Feb. 24 in the journal eLife. The research was supported by the National Institutes of Health and the National Science Foundation. By using new technologies to understand natural and dysfunctional states of biological systems, neuroscientists hope to ultimately bring cures to diseases.

Their work is published in Science. Cell sorting is a technique used in laboratories to separate complex mixtures of cells into their component cell types. Because certain cell types are very similar in size and shape, existing cell sorting methods may struggle with distinguishing one group of cells from another. In the present study, scientists at the University of Tokyo have invented a new cell identification and sorting system called ghost cytometry. In ghost cytometry, cells flow one at a time though a narrow channel underneath a single-pixel detector camera that senses the fluorescent light waves emitted by each cell.