Biological State Reconstruction through Continuous Multimodal Phenotyping in Preclinical Research

Abstract

Preclinical behavioral research has undergone remarkable technological development over recent decades. Automated video tracking, ultrasonic vocalization recording, electrophysiological monitoring, home-cage observation systems, refined animal handling protocols and artificial intelligence have substantially expanded the ability to observe laboratory animals while improving experimental reproducibility and animal welfare. Despite these advances, the conceptual organization of preclinical research has remained largely unchanged. Experimental observations continue to be interpreted primarily through discrete behavioral tests, although biological responses evolve continuously throughout the entire experimental period. This paper proposes a conceptual framework that extends, rather than replaces, existing behavioral paradigms. I argue that standardized behavioral tests should be regarded as reproducible observational events embedded within the continuously evolving biological state of the organism rather than as independent representations of biological response. To support this conceptual transition, I introduce continuous multimodal phenotyping as an integrative framework that synchronizes behavioral, acoustic, physiological, environmental and experimental observations acquired throughout the entire duration of an experiment. Within this framework, individual measurements are interpreted as complementary manifestations of the same underlying biological state, enabling its continuous reconstruction over time. The proposed concept shifts the objective of preclinical observation from the analysis of isolated behavioral endpoints toward the reconstruction of biological state as the principal framework for experimental interpretation. This approach establishes a conceptual basis for systems-oriented preclinical research and provides the foundation for future computational animal models capable of integrating multimodal experimental observations into dynamic representations of biological processes.