A professor in the Department of Mathematics will play a key role in a groundbreaking new international research network dubbed Odor2Action starting this fall. The work is aimed at understanding how animals use information from odors in their environment to guide behavior, with far-ranging implications for our understanding of the human brain.
Over the next five years Distinguished University Professor G. Bard Ermentrout will work with scientists from 16 prestigious institutions around the world to better understand the brain and its evolution by reverse-engineering how it interprets odors. The network was announced Monday as part of the Next Generation Networks for Neuroscience (NeuroNex) Program.
The project is funded by a $20.2 million award from the National Science Foundation, the Canadian Institutes of Health Research and the UK Research and Innovation Medical Research Council.
The network will examine all the steps involved in how an odor stimulus gets encoded by the brain and then activates the motor circuits to produce a behavioral response in an animal. The model species they will work with to do this, like fruit flies and mice, will make headway in understanding these same steps in humans.
Ermentrout’s role involves creating algorithms to model odor guided behavior for how the animals find food, mates or predators and figuring out how those algorithms fit into their overall neural circuitry network.
“Odor landscapes are quite complicated and turbulent, so these algorithms must work in very noisy environments,” he explained. “I will develop equations that govern how the circuits act when provided with different types of sensory input.”
John Crimaldi, lead principal investigator on the network and professor in the Department of Civil, Environmental and Architectural Engineering at Colorado University said, “The chemical sensing process (i.e. smell) evolved in the very earliest life forms on Earth.”
“The idea here is that all brain evolution has taken place in the presence of chemical sensing. And so it's thought to be a primal portal from which to view brain function.”
Crimaldi said smell is the least understood sense and that humans have struggled to replicate odor-based searches with machines. Doing so, however, would allow robots to take over treacherous duties instead of humans or dogs, unlocking a new area of advancement for autonomous systems. These robots could one day rescue a person buried in an avalanche, locate valuable natural resources, or find chemical weapons and explosives on their own, for example.
Ermentrout said the models will, “provide motivation and predictions for various experimental manipulations of the animals.”
“Mathematical models allow us to ask questions that could not easily be addressed by experiments. For example, a model can determine if the known circuits in a network are sufficient to generate a specific behavior. If not, then we know that there must be other parts of the brain that are needed. Conversely, models can suggest, as yet unknown mechanisms, which could then be tested for experimentally. Finally models can often distill complex neural interactions in to simplified circuits that could be used to guide robots searching for odors in difficult or dangerous environments.”
The network is composed of three interdisciplinary research groups (IRGs) that form a loop in animal sensing and behavior. The first is focused on theoretical mathematics and genetic mapping to better understand how the characteristics of smells are encoded in the brain. The second builds on this and will determine how the encoded odors produce a behavioral response. The third group will investigate how this behavioral response alters the animals’ perception of the odor it is sensing.
Partners include Caltech, Penn State University, Duke University, Salk Institute, University of Utah, NYU School of Medicine, McGill University, Scripps Research Institution, Arizona State University, Francis Crick Institute, University of Hertfordshire, Yale University and Weill Cornell.