Browsing by Subject "Neurobehaviour"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Association of exposure to manganese and fine motor skills in welders - Results from the WELDOX II study
    (Elsevier, 2021) Lotz, Anne; Pesch, Beate; Casjens, Swaantje; Lehnert, Martin; Zschiesche, Wolfgang; Taeger, Dirk; Yeh, Chien-Lin; Weiss, Tobias; Schmidt-Wilcke, Tobias; Quetscher, Clara; Gabriel, Stefan; Samis Zella, Maria Angela; Woitalla, Dirk; Dydak, Ulrike; van Thriel, Christoph; Brüning, Thomas; Behrens, Thomas; Radiology and Imaging Sciences, School of Medicine
    The aim of this study was to evaluate the effect of exposure to manganese (Mn) on fine motor functions. A total of 48 welders and 30 unexposed workers as controls completed questionnaires, underwent blood examinations, and a motor test battery. The shift exposure of welders to respirable Mn was measured with personal samplers. For all subjects accumulations of Mn in the brain were assessed with T1-weighted magnetic resonance imaging. Welders showed normal motor functions on the Movement Disorder Society-Sponsored Revision of the Unified Parkinson Disease Rating Scale part III. Furthermore welders performed excellent on a steadiness test, showing better results than controls. However, welders were slightly slower than controls in motor tests. There was no association between fine motor test results and the relaxation rates R1 in globus pallidus and substantia nigra as MRI-based biomarkers to quantify Mn deposition in the brain.
  • Thumbnail Image
    Item
    Normalization of large-scale behavioural data collected from zebrafish
    (Public Library of Science, 2019-02-15) Xie, Rui; Zhang, Mengrui; Venkatraman, Prahatha; Zhang, Xinlian; Zhang, Gaonan; Carmer, Robert; Kantola, Skylar A.; Pang, Chi Pui; Ma, Ping; Zhang, Mingzhi; Zhong, Wenxuan; Leung, Yuk Fai; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine
    Many contemporary neuroscience experiments utilize high-throughput approaches to simultaneously collect behavioural data from many animals. The resulting data are often complex in structure and are subjected to systematic biases, which require new approaches for analysis and normalization. This study addressed the normalization need by establishing an approach based on linear-regression modeling. The model was established using a dataset of visual motor response (VMR) obtained from several strains of wild-type (WT) zebrafish collected at multiple stages of development. The VMR is a locomotor response triggered by drastic light change, and is commonly measured repeatedly from multiple larvae arrayed in 96-well plates. This assay is subjected to several systematic variations. For example, the light emitted by the machine varies slightly from well to well. In addition to the light-intensity variation, biological replication also created batch-batch variation. These systematic variations may result in differences in the VMR and must be normalized. Our normalization approach explicitly modeled the effect of these systematic variations on VMR. It also normalized the activity profiles of different conditions to a common baseline. Our approach is versatile, as it can incorporate different normalization needs as separate factors. The versatility was demonstrated by an integrated normalization of three factors: light-intensity variation, batch-batch variation and baseline. After normalization, new biological insights were revealed from the data. For example, we found larvae of TL strain at 6 days post-fertilization (dpf) responded to light onset much stronger than the 9-dpf larvae, whereas previous analysis without normalization shows that their responses were relatively comparable. By removing systematic variations, our model-based normalization can facilitate downstream statistical comparisons and aid detecting true biological differences in high-throughput studies of neurobehaviour.