| Autor: |
Uhlirova H; Department of Radiology, University of California, San Diego; Central European Institute of Technology, Brno University of Technology; huhlirova1@gmail.com., Tian P; Department of Neurosciences, University of California, San Diego; Department of Physics, John Carroll University., Kılıç K; Department of Neurosciences, University of California, San Diego; Department of Biomedical Engineering, Boston University., Thunemann M; Department of Radiology, University of California, San Diego., Sridhar VB; Bioengineering Undergraduate Program, University of California, San Diego., Chmelik R; Central European Institute of Technology, Brno University of Technology; Institute of Physical Engineering, Faculty of Mechanical Engineering, Brno University of Technology., Bartsch H; Department of Radiology, University of California, San Diego., Dale AM; Department of Radiology, University of California, San Diego; Department of Neurosciences, University of California, San Diego., Devor A; Department of Radiology, University of California, San Diego; Department of Neurosciences, University of California, San Diego; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School., Saisan PA; Department of Neurosciences, University of California, San Diego. |
| Abstrakt: |
The importance of sharing experimental data in neuroscience grows with the amount and complexity of data acquired and various techniques used to obtain and process these data. However, the majority of experimental data, especially from individual studies of regular-sized laboratories never reach wider research community. A graphical user interface (GUI) engine called Neurovascular Network Explorer 2.0 (NNE 2.0) has been created as a tool for simple and low-cost sharing and exploring of vascular imaging data. NNE 2.0 interacts with a database containing optogenetically-evoked dilation/constriction time-courses of individual vessels measured in mice somatosensory cortex in vivo by 2-photon microscopy. NNE 2.0 enables selection and display of the time-courses based on different criteria (subject, branching order, cortical depth, vessel diameter, arteriolar tree) as well as simple mathematical manipulation (e.g. averaging, peak-normalization) and data export. It supports visualization of the vascular network in 3D and enables localization of the individual functional vessel diameter measurements within vascular trees. NNE 2.0, its source code, and the corresponding database are freely downloadable from UCSD Neurovascular Imaging Laboratory website 1 . The source code can be utilized by the users to explore the associated database or as a template for databasing and sharing their own experimental results provided the appropriate format. |
