Article

The multilevel exploration test, a novel paradigm to measure exploratory behavior in depression animal models and the involvement of the PL-ZI circuit

Jun-nan Xu1,2, Jing-ting Li1, Ru-xia Xu1, Yun-feng Wang1, He-wei Gao2, Hao-tian He2, Han Guo3, Yu Liang1, Yong-dan Zhu1, Xiao-wen Li1, Jian-ming Yang1, Xiao-ming Li2, Yi-hua Chen1, Tian-ming Gao1
1 State Key Laboratory of Multi-organ Injury Prevention and Treatment, Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong-Hong Kong Joint Laboratory for Psychiatric Disorders, Guangdong Province Key Laboratory of Psychiatric Disorders, Guangdong Basic Research Center of Excellence for Integrated Traditional and Western Medicine for Qingzhi Diseases, Department of Neurobiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
2 MOE Frontier Science Center for Brain Science & Brain-Machine Integration, NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang Key Laboratory of Precision Psychiatry, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou 310012, China
3 Department of Applied Mathematics, Waseda University, Waseda, Japan
Correspondence to: Yi-hua Chen: chenyihua@smu.edu.cn, Tian-ming Gao: tgao@smu.edu.cn,
DOI: 10.1038/s41401-026-01812-x
Received: 15 December 2025
Accepted: 23 March 2026
Advance online: 19 May 2026

Abstract

Diminished drive is one of the core symptoms of major depressive disorder (MDD) diagnosis, yet its underlying neural mechanisms remain elusive, primarily due to a lack of appropriate animal models. We developed a novel Multilevel Exploration Test (MET) apparatus to evaluate exploratory behavior, which is captured as a dynamic, stage-dependent process involving “search”, “attend/ investigate”, and “approach” phases. We employed fiber photometry to measure real-time dopamine dynamics in the nucleus accumbens. We further combined cFos staining and neural circuit tracing to identify relevant brain regions and circuits, and employed chemogenetics to selectively modulate prelimbic cortex (PL) inputs to zona incerta (ZI). The MET tests were conducted across five depression models, with ketamine administration to evaluate rescue effects. Machine learning algorithms were utilized to analyze MET data and predict individual emotional states (normal, anxiety-like, depression-like). Here, we developed a novel paradigm to assess exploratory behavior, which demonstrates etiological validity, face validity and predictive validity. Depressed mice exhibited reduced motivation for exploration in this paradigm, while stimulation of the PL-ZI circuit not only restored exploratory deficits but also alleviated other depression-like behaviors in these mice. Furthermore, we established a machine learning-based model to predict individual animals’ emotional states by integrating data from the new paradigm, achieving a prediction accuracy of over 92%. The MET provides a functional, high-throughput paradigm for dissecting motivation-related pathology. It facilitates the assessment of depressive-like behaviors, enables the prediction of emotional states, and supports the discovery of novel targets for antidepressant development.
Keywords: multilevel exploration test; motivation; depression; anxiety; ethology

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