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DOI 10.1016/j.jneumeth.2016.07.015

Медицинская библиотека · Journal of neuroscience methods · 2016

An automated whisker tracking tool for the rat facial nerve injury paradigm.

Dorschner Benjamin, Süße Herbert, Ortmann Wolfgang, Irintchev Andrey, Denzler Joachim, Guntinas-Lichius Orlando

СтатьяВалидационное исследованиеПеревод в очереди

Аннотация

BACKGROUND

The two-dimensional videographic analysis of vibrissal movements in behaving rodents has become a standard method to estimate the degree of functional impairment and recovery after facial nerve injuries quantitatively. The main limitation of the method is the time consuming, uneconomic process of manually tracking the vibrissae in video sequences.

NEW METHOD: We developed a novel tool allowing automated detection of untagged vibrissae (two on each side of the snout). To compare the new method with the standard manual tracking approach, we used videos of unrestrained rats with unilateral section and immediate suture of the facial nerve performed two months earlier.

RESULTS

Measurement agreement analyses showed that the two methods are equivalent for both "normal" high-amplitude vibrissal movements (non-operated side) and low-amplitude whisking (reinnervated side). Spectral analysis revealed a significant deviation in the power spectra on the control and injured side, indicating that bilaterally coordinated whisker movements are not present two months after surgery.

COMPARISON WITH EXISTING METHOD(S): The novel method yields results equal to those of the manual tracking approach. An advantage of our tool is the possibility to significantly increase sample size without additional labor cost.

CONCLUSIONS

The novel tool can increase the efficacy and spectrum of functional measures used in facial nerve regeneration research.

Для цитирования: Dorschner Benjamin, Süße Herbert, Ortmann Wolfgang, Irintchev Andrey, Denzler Joachim, Guntinas-Lichius Orlando. An automated whisker tracking tool for the rat facial nerve injury paradigm.. Journal of neuroscience methods. 2016. DOI: 10.1016/j.jneumeth.2016.07.015.

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