Understanding the neural principles of interacting multiple internal states

Abstract

In dynamic ethological environments, animals are constantly confronted with conflicting choices driven by interacting internal motivations. This intricate dance between internal states prompts the question: How do these states interact to determine the optimal innate behavior at any given moment? Specifically, when hungry animals encounter food and potential intruders, how do they navigate between feeding, attack, and mating behaviors? Despite extensive neuroscience research on instinctive behaviors, our understanding of the mechanisms governing adaptive behavioral decisions in the face of competing internal signals remains limited. This research aims to shed light on the complex interplay of internal physiological homeostasis in modulating defensive, aggressive, and sexual behaviors. Our focus lies on exploring the intricate network between the body and the brain to unravel the most adaptive responses within a concise time window. Currently, our investigations center around the hypothalamus, a crucial region known for representing emotional states upon encountering conspecifics or predators. Intriguingly, this same hypothalamic nucleus plays a pivotal role in regulating homeostatic metabolic states, including glucose homeostasis. Here, I will share the observation from innate behaviors of animals and the associated neural activity patterns in the hypothalamus. We will explore the current understanding of how these behaviors are modulated by internal physiological states and discuss the future directions of our research. Additionally, we aim to highlight the significance of combining the measurement of physiological signals to comprehensively address how multiple internal states interact with each other. By unraveling the complexities of these interactions, our research contributes to a deeper comprehension of the adaptive decision-making processes that animals employ in the face of conflicting choices. Helen Hay Whitney Foundation, HHMI. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.