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Updated: Apr 28, 2026

Fat Preference: A Novel Model of Eating Behavior in Rats
Published on: June 27, 2014
State-Level Organization of Spontaneous Behavior and Its Association with Plasma Fatty-Acid Profiles in Healthy Rats
Ahmed S A Ali Agha1, Sara Khaleel2, Nidal A Qinna3
1Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman 11942, Jordan.
Abstract:
Individual variability in spontaneous behavior emerges from coordinated physiological states, yet the organization of baseline behavioral dimensions and their systemic metabolic correlations remains insufficiently characterized in healthy animals. Here, exploratory activity and self-directed grooming were quantified during a standardized Y-maze session and integrated with plasma fatty-acid profiles measured by orthogonal dual-column GC-MS in 30 healthy male Sprague-Dawley rats distributed across four independent cohorts. Correlation structure and principal component analysis showed that plasma lipid profiles exhibit non-random, low-dimensional organization, resolving into coherent compositional states dominated by coordinated shifts between shorter-chain (C14-C16) and longer-chain (C18) fatty-acid species. Behavioral variables are similarly organized into constrained dimensions capturing exploratory engagement and grooming expression or timing. Integrated correlation analysis indicated that plasma fatty-acid-derived lipid states aligned systematically with behavioral organization at the multivariate level across cohorts, with C18-enriched profiles generally aligned with higher behavioral engagement and earlier grooming expression at the state level, while C14/C16-enriched profiles associated with reduced exploration and delayed grooming initiation, although the direction of individual lipid-behavior correlations showed cohort dependence consistent with the context-dependent behavior of compositional lipid variables within distinct but physiologically normal lipidomic states. These findings demonstrate that state-level, correlation-based multivariate analysis can reveal structured plasma lipidomic configurations and their correspondence to behavioral organization under physiological conditions, without inferring causal directionality or pathway activation.

