A new method for vibration-based neurophenotyping of zebrafish

Jingtao Wang, Dongmei Wang, Guojun Hu, Long En Yang, Dongni Yan, Mengyao Wang, Nazar Serikuly, Erik Alpyshov, Tamara G. Amstislavskaya, Konstantin A. Demin, Murilo S. de Abreu, Konstantin N. Zabegalov, Allan V. Kalueff*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Background: The zebrafish (Danio rerio) is rapidly emerging as an important model species in neuroscience research. Neurobehavioral studies in zebrafish are typically based on automated video-tracking of individual or group fish responses to various stressors, drug treatments and genetic manipulations. However, moving zebrafish also emit vibration signals that can be recorded and characterized. New method: Here, we present the first evidence that vibration-based analyses can be used to assess zebrafish behaviors. Utilizing a free accelerometer smartphone application, we developed a simple inexpensive custom-made setup to detect vibration signals in adult zebrafish. Results: We demonstrate that moving zebrafish generate detectable, reproducible vibration power frequency spectra that may be sensitive to various experimental manipulations, including sedative and anxiolytic treatments. Comparison with existing methods: The present study is the first report describing vibration-based behavioral characterization in zebrafish. Conclusions: The present proof-of-concept study expands the toolkit of zebrafish neurophenotyping methods to include vibration data, which may not only reflect major global changes in zebrafish locomotion (e.g., sedation or hyperactivity), but can also eventually help detect more nuanced, behavior- or context-specific changes in zebrafish phenotypes.

Original languageEnglish
Article number108563
JournalJournal of Neuroscience Methods
Publication statusPublished - 1 Mar 2020
Externally publishedYes


  • Behavioral analyses
  • Drug screening
  • Neurophenotyping
  • Vibration signals
  • Zebrafish


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