Spurred on by technological advances, the last several years have seen an explosion of studies of behavioral, genomic, and neurophysiological mechanisms of social behaviors. Yet these empirical studies and the vast amount of data they produce are typically disconnected from well-established social evolution theory. We argue that unlocking the transformative potential of the emerging empirical approaches to social behavior requires new kinds of theoretical approaches that integrate proximate behavioral, genomic, and neurophysiological mechanisms with evolutionary dynamics. We review recent efforts in this direction that show how proximate mechanisms are important for evolutionary dynamics. However, we argue that these frameworks are still too distant from empirical systems to interface with emerging datasets. As an example of improved approaches that can be developed, we focus on the evolution of social gene regulatory networks, and discuss how integrating dynamics of gene regulatory networks with social evolution theory can result in rigorous hypotheses that are testable with sociogenomic data.
|Number of pages||6|
|Journal||Current Opinion in Behavioral Sciences|
|State||Published - Dec 1 2015|
Bibliographical noteFunding Information:
This work was in part supported by a National Academies Keck Futures Initiatives grant to JVC, TAL and EA. EA was funded by NSF award EF-1137894, and TAL by NSF award IOS-1452520.
© 2015 Elsevier Ltd.
ASJC Scopus subject areas
- Cognitive Neuroscience
- Psychiatry and Mental health
- Behavioral Neuroscience