Michael Sheehan

Michael Sheehan is an assistant professor and Nancy and Peter Meinig Investigator in the Life Science in Neurobiology and Behavior at Cornell University. His lab examines the reciprocal relationships between social behavior and diversity. Much of his work has focused on the ecology and evolution of individual recognition. Previous studies in paper wasps, mice and humans have demonstrated that individual recognition can drive the evolution of extreme phenotypic variability, allowing for efficient recognition. Additionally, Sheehan has demonstrated that paper wasps use face-specific processing mechanisms to recognize individuals, analogous to facial processing in humans and primates. Ongoing work in the lab integrates approaches from behavioral ecology, population genomics and increasingly neuroscience to address a range of mechanistic and evolutionary questions regarding recognition systems in both paper wasps and house mice.


Sheehan received his PhD in 2012 in Ecology and Evolutionary Biology from the University of Michigan and received and NIH NRSA postdoctoral fellowship to purse training in population genomics at the University of California at Berkely. Sheehan’s work has been recognized with the Allee Award from the Animal Behavior Society (2011) and the Young Investigator Award from the American Society of Naturalists (2014). Recently Sheehan was awarded an NIH Director’s New Innovator Award (2017) for examine the genetic basis of facial processing in paper wasps.

Genomic insights into the evolution of social intelligence and phenotypic diversity

Individual recognition is the most specific and precise form of recognition. It requires that individuals have distinctive phenotypes to allow for recognition, which itself requires flexible learning and memory. Here I report insights into how individual recognition is driving the evolution of phenotypic diversity and social intelligence in a unique species of paper wasp. The Northern paper wasp, Polistes fuscatus, displays a wide diversity of color facial color pattering, which they use to recognize individuals within their nests. By combining comparative, population and functional genomic approaches we are describing the genetic mechanisms and selective pressures maintaining extreme phenotypic diversity in this species. Individual recognition and extreme diversity is in P. fuscatus is especially notable since its close relatives lack color pattern variation and do not recognize individuals. We have taken advantage of the recent evolution of recognition in P. fuscatus to examine patterns of selection on genes associated with learning and memory. Population genomic analyses reveal that the strongest selective events in the recent history of P. fuscatus have been associated with selection on learning, memory and vision. We do not find these same patterns in closely related species, suggesting that social behavior and recognition in particular can be extreme potent forces driving the rapid evolution of diversity and cognition.