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Behavioral assessment of pain in rodents: advances from evoked responses to spontaneous states and multimodal approaches

Year: 2026
Type: article
Abstract: Pain is widely recognized as a leading global health problem that markedly diminishes quality of life. Although assessment lies at the core of pain medicine, robust quantification remains difficult. In preclinical research, commonly used behavioral assays often blur the distinction between spontaneous pain and stimulus-evoked responses. Here, we review recent advances, clarify the conceptual and operational boundaries between spontaneous and evoked pain, and provide a multidimensional comparison of major traditional behavioral paradigms. To address shortcomings in objectivity and reproducibility, we also summarize emerging evaluation strategies. Finally, leveraging bioinformatics and machine learning, we identify pain-associated metrics and propose building multimodal datasets and AI-driven feature-extraction pipelines to enhance the translational value of animal data for clinical pain research.
Language: English
Subfield: Physiology
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,077
OpenAlex ID: W7128437530
FWCI: 8.318
Cites: 206
Cited by: 2
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