Economic and Social Modulations of Innate Decision-Making in Mice Exposed to Visual Threats

When confronted by predators, animals make innate decisions with rapid reaction times—a trait shaped by natural selection to maximize survival. However, rapid reactions are effective only when grounded in accurate judgments and appropriate choices, which often require cognitive control. To address how such choices are shaped, we developed a behavioral paradigm to investigate how threat intensity, reward value, and social hierarchy influence decision-making in foraging mice exposed to overhead visual threats. Using a machine learning-based approach, we classified defensive responses into four distinct decision types. We observed rapid habituation to repeated looming threats, with substantial inter-individual variability in the rate of habituation. Across both early and late phases of habituation, threat intensity is the primary determinant of decision-making, strongly driving behavior towards escape. In contrast, the influence of reward is context-dependent and emerges primarily in the late phase: under low-threat conditions, higher rewards suppress defensive responses, consistent with value-based decision theory, whereas under high-threat conditions, higher rewards promote escape, potentially reflecting heightened vigilance. Innate decision-making is further modulated by social hierarchy, with dominant mice showing greater vigilance and a stronger bias towards risk-averse behaviors, while subordinates are more reward-driven. To understand the underlying decision-making process, we developed a drift-diffusion leaky integrator model that successfully captures how threat intensity, reward value, and vigilance are integrated. Together, these findings reveal the economic and social modulation of innate decisions, offering insights into the computational mechanisms underlying the interplay between instinctive reactions and cognitive control.