Thursday, November 21, 2024
11/21/2024
Project Summary Pair bonds play critical roles in the human experience and profoundly influence our physical and emotional health. For a bond to be beneficial and the pair to accomplish shared goals, partners must work together through reciprocal action where each person acts and the other responds in turn. Despite the dyadic nature of pair bonds, the vast majority of studies on pair bonding focus on only one member of a pair, leaving us with an impoverished view of the dynamics between partners that facilitate relationship success. To fill this knowledge gap, I will use pair bonding prairie voles to examine the behavioral and biological basis of pair bonding in both partners of bonded pairs. My preliminary data show that in prairie voles, partners organize their affiliative behavior as bonds mature. In this proposal, I will use computational techniques to examine the discrete elements that underlie organized intra-pair behavior at two levels of biological organization: behavior and transcription. In my first Aim, I will leverage machine learning algorithms to decipher the within-animal and between-animal behavioral sequences that partners exhibit when allowed to interact freely with each other. This will reveal the behavioral components that contribute to intra-pair behavioral organization. To determine the neuromolecular basis of this behavior, in my second Aim, I will use single nucleus RNA sequencing (snRNA-seq) to map the transcriptional landscape of the prairie vole nucleus accumbens (NAc) and medial prefrontal cortex (mPFC), two brain regions critical for pair bonding. snRNA-seq will enable me to identify changes to discrete cellular populations upon bonding and will allow me to compare the similarity of transcriptional landscapes between bonded partners, potentially revealing a role for transcriptional convergence in the organization of intra-pair behavior. Together, these Aims will provide a new, dual- individual lens through which we can understand pair bonding and will provide me with training in the computational analysis of behavior and transcriptomics, invaluable skills for my career as an independent researcher.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
