| Literature DB >> 25280919 |
Benjamin Risse1, Dimitri Berh1, Nils Otto2, Xiaoyi Jiang3, Christian Klämbt4.
Abstract
Quantitative analysis of behavioral traits requires precise image acquisition and sophisticated image analysis to detect subtle locomotion phenotypes. In the past, we have established Frustrated Total Internal Reflection (FTIR) to improve the measurability of small animals like insects. This FTIR-based Imaging Method (FIM) results in an excellent foreground/background contrast and even internal organs and other structures are visible without any complicated imaging or labeling techniques. For example, the trachea and muscle organizations are detectable in FIM images. Here these morphological details are incorporated into phenotyping by performing cluster analysis using histogram-based statistics for the first time. We demonstrate that FIM enables the precise quantification of locomotion features namely rolling behavior or muscle contractions. Both were impossible to quantify automatically before. This approach extends the range of FIM applications by enabling advanced automatic phenotyping for particular locomotion patterns.Entities:
Keywords: Clustering; Drosophila larva; FTIR-based Imaging Method (FIM); Frustrated Total Internal Reflection (FTIR); Histogram analysis; Internal organs; Neuroscience; Peristalsis; Rolling behavior; Trachea
Mesh:
Year: 2014 PMID: 25280919 DOI: 10.1016/j.compbiomed.2014.08.026
Source DB: PubMed Journal: Comput Biol Med ISSN: 0010-4825 Impact factor: 4.589