TY  - JOUR
A1  - Farmer, Adam D.
A1  - Strzelczyk, Adam
A1  - Finisguerra, Alessandra
A1  - Gourine, Alexander V.
A1  - Gharabaghi, Alireza
A1  - Hasan, Alkomiet
A1  - Burger, Andreas M.
A1  - Jaramillo, Andrés M.
A1  - Mertens, Ann
A1  - Majid, Arshad
A1  - Verkuil, Bart
A1  - Badran, Bashar W.
A1  - Ventura-Bort, Carlos
A1  - Gaul, Charly
A1  - Beste, Christian
A1  - Warren, Christopher M.
A1  - Quintana, Daniel S.
A1  - Hämmerer, Dorothea
A1  - Freri, Elena
A1  - Frangos, Eleni
A1  - Tobaldini, Eleonora
A1  - Kaniusas, Eugenijus
A1  - Rosenow, Felix
A1  - Capone, Fioravante
A1  - Panetsos, Fivos
A1  - Ackland, Gareth L.
A1  - Kaithwas, Gaurav
A1  - O'Leary, Georgia H.
A1  - Genheimer, Hannah
A1  - Jacobs, Heidi I. L.
A1  - Van Diest, Ilse
A1  - Schoenen, Jean
A1  - Redgrave, Jessica
A1  - Fang, Jiliang
A1  - Deuchars, Jim
A1  - Széles, Jozsef C.
A1  - Thayer, Julian F.
A1  - More, Kaushik
A1  - Vonck, Kristl
A1  - Steenbergen, Laura
A1  - Vianna, Lauro C.
A1  - McTeague, Lisa M.
A1  - Ludwig, Mareike
A1  - Veldhuizen, Maria G.
A1  - De Couck, Marijke
A1  - Casazza, Marina
A1  - Keute, Marius
A1  - Bikson, Marom
A1  - Andreatta, Marta
A1  - D'Agostini, Martina
A1  - Weymar, Mathias
A1  - Betts, Matthew
A1  - Prigge, Matthias
A1  - Kaess, Michael
A1  - Roden, Michael
A1  - Thai, Michelle
A1  - Schuster, Nathaniel M.
A1  - Montano, Nicola
A1  - Hansen, Niels
A1  - Kroemer, Nils B.
A1  - Rong, Peijing
A1  - Fischer, Rico
A1  - Howland, Robert H.
A1  - Sclocco, Roberta
A1  - Sellaro, Roberta
A1  - Garcia, Ronald G.
A1  - Bauer, Sebastian
A1  - Gancheva, Sofiya
A1  - Stavrakis, Stavros
A1  - Kampusch, Stefan
A1  - Deuchars, Susan A.
A1  - Wehner, Sven
A1  - Laborde, Sylvain
A1  - Usichenko, Taras
A1  - Polak, Thomas
A1  - Zaehle, Tino
A1  - Borges, Uirassu
A1  - Teckentrup, Vanessa
A1  - Jandackova, Vera K.
A1  - Napadow, Vitaly
A1  - Koenig, Julian
T1  - International Consensus Based Review and Recommendations for Minimum Reporting Standards in Research on Transcutaneous Vagus Nerve Stimulation (Version 2020)
JF  - Frontiers in Human Neuroscience
N2  - Given its non-invasive nature, there is increasing interest in the use of transcutaneous vagus nerve stimulation (tVNS) across basic, translational and clinical research. Contemporaneously, tVNS can be achieved by stimulating either the auricular branch or the cervical bundle of the vagus nerve, referred to as transcutaneous auricular vagus nerve stimulation(VNS) and transcutaneous cervical VNS, respectively. In order to advance the field in a systematic manner, studies using these technologies need to adequately report sufficient methodological detail to enable comparison of results between studies, replication of studies, as well as enhancing study participant safety. We systematically reviewed the existing tVNS literature to evaluate current reporting practices. Based on this review, and consensus among participating authors, we propose a set of minimal reporting items to guide future tVNS studies. The suggested items address specific technical aspects of the device and stimulation parameters. We also cover general recommendations including inclusion and exclusion criteria for participants, outcome parameters and the detailed reporting of side effects. Furthermore, we review strategies used to identify the optimal stimulation parameters for a given research setting and summarize ongoing developments in animal research with potential implications for the application of tVNS in humans. Finally, we discuss the potential of tVNS in future research as well as the associated challenges across several disciplines in research and clinical practice.
KW  - transcutaneous vagus nerve stimulation
KW  - minimum reporting standards
KW  - guidelines & recommendations
KW  - transcutaneous auricular vagus nerve stimulation
KW  - transcutaneous cervical vagus nerve stimulation
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-234346
SN  - 1662-5161
VL  - 14
ER  - 
TY  - JOUR
A1  - Ziegler, Alice
A1  - Meyer, Hanna
A1  - Otte, Insa
A1  - Peters, Marcell K.
A1  - Appelhans, Tim
A1  - Behler, Christina
A1  - Böhning-Gaese, Katrin
A1  - Classen, Alice
A1  - Detsch, Florian
A1  - Deckert, Jürgen
A1  - Eardley, Connal D.
A1  - Ferger, Stefan W.
A1  - Fischer, Markus
A1  - Gebert, Friederike
A1  - Haas, Michael
A1  - Helbig-Bonitz, Maria
A1  - Hemp, Andreas
A1  - Hemp, Claudia
A1  - Kakengi, Victor
A1  - Mayr, Antonia V.
A1  - Ngereza, Christine
A1  - Reudenbach, Christoph
A1  - Röder, Juliane
A1  - Rutten, Gemma
A1  - Schellenberger Costa, David
A1  - Schleuning, Matthias
A1  - Ssymank, Axel
A1  - Steffan-Dewenter, Ingolf
A1  - Tardanico, Joseph
A1  - Tschapka, Marco
A1  - Vollstädt, Maximilian G. R.
A1  - Wöllauer, Stephan
A1  - Zhang, Jie
A1  - Brandl, Roland
A1  - Nauss, Thomas
T1  - Potential of airborne LiDAR derived vegetation structure for the prediction of animal species richness at Mount Kilimanjaro
JF  - Remote Sensing
N2  - The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.
KW  - biodiversity
KW  - species richness
KW  - LiDAR
KW  - elevation
KW  - partial least square regression
KW  - arthropods
KW  - birds
KW  - bats
KW  - predictive modeling
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262251
SN  - 2072-4292
VL  - 14
IS  - 3
ER  -