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Lévy statistics define anxiety and depression in mice subjected to chronic stress
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DOI：10.3389/fnbeh.2026.1757347.png)
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Abstract
En 中文
IntroductionCurrent rodent models for anxiety and depression assessment face methodological challenges compromising both scientific rigor and animal welfare.MethodsThis study introduced a novel approach using the Lévy flight (LF) statistical method to analyze spontaneous movement in open spaces. We employed three models: Chronic unpredictable mild stress (CUMS); Electric shock stress (ES); and Chronic Restraint Stress (CRS)—utilizing a total of 540 mice for LF fitting. A support vector machine algorithm was applied to distinguish each model group based on the two-dimensional distribution of the variables γ and μ in the LF. Statistical analysis was performed using a two-dimensional Kolmogorov-Smirnov test before and after drug administration.ResultsWe found that the ES model primarily exhibited anxiety-like behaviors; the CRS model predominantly exhibited depression-like behaviors; and the CUMS model displayed both depression-like and anxiety-like behaviors. All three stress models were suitable for LF fitting; with the distribution of CUMS in the γ-μ plane lying between the ES and CRS groups. To assess the therapeutic effect of fluoxetine (FXT) on CUMS; we excluded the CUMS-resistant mice and performed LF analysis. Following FXT treatment; the mice gradually shifted toward the normal area in the γ-μ plane; with a more pronounced shift toward the depression area observed as the modeling time increased.DiscussionThis study identifies a previously unrecognized statistical locomotor pattern in mice with anxiety and depression. By integrating scientific rigor with ethical considerations; this approach also presents a humane paradigm shift in preclinical assessment; accelerating translational breakthroughs in neuroscience research.
Keywords:
stress
depression
behavior
anxiety
Lévy flight
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