Virginia Tech engineers are forging new computational tools to shed light on the role of vitally important cells in the human brain called astrocytes. Increasing evidence suggests defects in astrocyte-neuron communication are associated with a number of diseases, including Alzheimer’s, stroke, epilepsy, and schizophrenia.
Guoqiang Yu, an assistant professor in the Bradley Department of Electrical and Computer Engineering in the College of Engineering, is leading a project, “Decoding astrocyte signaling in neural circuitry with novel computational modeling and analytical tools.” Yu is collaborating with experimental neuroscientists from the University of California, Davis, and Yue (Joseph) Wang, the Grant A. Dove Professor of Electrical and Computer Engineering.
The collaborative team has been awarded a $2.5 million National Institutes of Health grant for the project.
Astrocytes, from the Greek “star cells” in reference to their shape, are workhorses of the central nervous system. They wrap around neurons, nursing and protecting them; help to repair damaged tissue; maintain ion balance; and provide nutrients to the nervous tissue.
The nature of the intimate relationship between neurons and astrocytes has long been a subject of interest for researchers, who have been trying to tease out the functional role of astrocytes in brain information processing for decades.
Unlike neurons, astrocytes do not generate electrical impulses. They communicate among themselves and with neurons through chemical signals — including waves of calcium ions (Ca2+) — which aid the formation and function of synapses throughout the brain.
“A deeper understanding of the back-and-forth signaling between astrocytes and neurons in health and disease could lead to novel therapies for brain disorders,” said Yu.
The lag has jeopardized a deeper understanding of the functional roles of astrocytes, which has slowed the progress of brain disorder therapies along this avenue.
The Virginia Tech research collaboration seeks to address this discrepancy by developing novel computational tools, drawing strength from an arsenal of advanced machine learning techniques like graph-structured tensor decomposition and analyzing the cellular properties of calcium signaling in a single astrocyte.
Then, because so much of an astrocyte’s function depends on how it operates within a network, the team will develop computational tools to analyze the properties of calcium signaling in a population of the cells.
“The study of astrocytes at the network level has been unduly ignored so far,” said Yu. “But we can gain insight into these inner workings by leveraging our experience in network biology and probabilistic modeling.”
Finally, the team will package the developed computational tools into a user-friendly software program to reach and benefit experimental scientists. All source code will also be disseminated through public open-source hosting websites so that anyone can modify and tailor the code to their specific application and need.
Written by Kelly Izlar