Cortical Estrogen Signaling as a Modulator of Behavioral Persistence: Testing the Necessity and Sufficiency of Estrogen Receptor α in the Medial Prefrontal Cortex

Abstract

Fluctuations in estradiol are known to modulate social behavior, cognition, and affect, yet the circuit-level mechanisms through which estrogen shapes behavioral output remain poorly understood. This thesis investigates the role of estrogen receptor alpha (ERα) signaling in the medial prefrontal cortex (mPFC) in regulating behavior and behavioral persistence. Using a combination of ovariectomy with estradiol replacement in mice, region-specific ERα knockdown, and ERα overexpression, this work tests the necessity and sufficiency of mPFC estrogen receptor signaling across social and non-social behavioral domains. Baseline experiments demonstrate that estradiol enhances behavioral persistence and structured engagement across both social interaction and exploratory contexts. ERα knockdown in the mPFC reveals that while local receptor signaling contributes to the organization of social behavior, estradiol-dependent increases in persistence in the non-social domain are largely preserved, suggesting that estrogen-dependent behavioral persistence may be mediated by distinct circuit mechanisms, with mPFC ERα signaling preferentially regulating social behavior, and other circuits supporting persistence in non-social contexts. In contrast, ERα overexpression in mPFC selectively enhances the temporal stability of behavior without significantly altering social preference, indicating that increased receptor availability is sufficient to modulate behavioral persistence but not social preference. Together, these findings support a model in which estrogen acts as a domain-general modulator of behavioral stability, with mPFC ERα signaling contributing specifically to flexibility of behavior and behavioral persistence. These results further suggest that estrogenic modulation of prefrontal circuits may operate within a nonlinear, potentially inverted U-shaped framework, providing new insight into how hormonal state dynamically shapes neural computation and behavior.